The Great Lakes Runoff Intercomparison Project Phase 4: the Great Lakes (GRIP-GL) - Mai, Juliane; Shen, Hongren; Tolson, Bryan A.; Gaborit, Étienne; Arsenault, Richard; Craig, James R.; Fortin, Vincent; Fry, Lauren M.; Gauch, Martin; Klotz, Daniel; Kratzert, Frederik; O'Brien, Nicole; et al. (Hydrology and Earth System Sciences, 2022)
Abstract. Model intercomparison studies are carried out to test and compare the simulated outputs of various model setups over the same study domain. The Great Lakes region is such a domain of high public interest as it not only resembles a challenging region to model with its transboundary location, strong lake effects, and regions of strong human impact but is also one of the most densely populated areas in the USA and Canada. This study brought together a wide range of researchers setting up their models of choice in a highly standardized experimental setup using the same geophysical datasets, forcings, common routing product, and locations of performance evaluation across the 1×106 km2 study domain. The study comprises 13 models covering a wide range of model types from machine-learning-based, basin-wise, subbasin-based, and gridded models that are either locally or globally calibrated or calibrated for one of each of the six predefined regions of the watershed. Unlike most hydrologically focused model intercomparisons, this study not only compares models regarding their capability to simulate streamflow (Q) but also evaluates the quality of simulated actual evapotranspiration (AET), surface soil moisture (SSM), and snow water equivalent (SWE). The latter three outputs are compared against gridded reference datasets. The comparisons are performed in two ways – either by aggregating model outputs and the reference to basin level or by regridding all model outputs to the reference grid and comparing the model simulations at each grid-cell. The main results of this study are as follows: The comparison of models regarding streamflow reveals the superior quality of the machine-learning-based model in the performance of all experiments; even for the most challenging spatiotemporal validation, the machine learning (ML) model outperforms any other physically based model. While the locally calibrated models lead to good performance in calibration and temporal validation (even outperforming several regionally calibrated models), they lose performance when they are transferred to locations that the model has not been calibrated on. This is likely to be improved with more advanced strategies to transfer these models in space. The regionally calibrated models – while losing less performance in spatial and spatiotemporal validation than locally calibrated models – exhibit low performances in highly regulated and urban areas and agricultural regions in the USA. Comparisons of additional model outputs (AET, SSM, and SWE) against gridded reference datasets show that aggregating model outputs and the reference dataset to the basin scale can lead to different conclusions than a comparison at the native grid scale. The latter is deemed preferable, especially for variables with large spatial variability such as SWE. A multi-objective-based analysis of the model performances across all variables (Q, AET, SSM, and SWE) reveals overall well-performing locally calibrated models (i.e., HYMOD2-lumped) and regionally calibrated models (i.e., MESH-SVS-Raven and GEM-Hydro-Watroute) due to varying reasons. The machine-learning-based model was not included here as it is not set up to simulate AET, SSM, and SWE. All basin-aggregated model outputs and observations for the model variables evaluated in this study are available on an interactive website that enables users to visualize results and download the data and model outputs.

The sensitivity of simulated streamflow to individual hydrologic processes across North America - Mai, Juliane; Craig, James R.; Tolson, Bryan A.; Arsenault, Richard (Nature Communications, 2022)
Abstract Streamflow sensitivity to different hydrologic processes varies in both space and time. This sensitivity is traditionally evaluated for the parameters specific to a given hydrologic model simulating streamflow. In this study, we apply a novel analysis over more than 3000 basins across North America considering a blended hydrologic model structure, which includes not only parametric, but also structural uncertainties. This enables seamless quantification of model process sensitivities and parameter sensitivities across a continuous set of models. It also leads to high-level conclusions about the importance of water cycle components on streamflow predictions, such as quickflow being the most sensitive process for streamflow simulations across the North American continent. The results of the 3000 basins are used to derive an approximation of sensitivities based on physiographic and climatologic data without the need to perform expensive sensitivity analyses. Detailed spatio-temporal inputs and results are shared through an interactive website.

Evaluating Hydrologic Response in Tile‐Drained Landscapes: Implications for Phosphorus Transport - Macrae, M. L.; Ali, G. A.; King, K. W.; Plach, J. M.; Pluer, W. T.; Williams, M.; Morison, M. Q.; Tang, W. (Journal of Environmental Quality, 2019)
Phosphorus (P) loss in agricultural discharge has typically been associated with surface runoff; however, tile drains have been identified as a key P pathway due to preferential transport. Identifying when and where these pathways are active may establish high‐risk periods and regions that are vulnerable for P loss. A synthesis of high‐frequency, runoff data from eight cropped fields across the Great Lakes region of North America over a 3‐yr period showed that both surface and tile flow occurred year‐round, although tile flow occurred more frequently. The relative timing of surface and tile flow activation was classified into four response types to infer runoff‐generation processes. Response types were found to vary with season and soil texture. In most events across all sites, tile responses preceded surface flow, whereas the occurrence of surface flow prior to tile flow was uncommon. The simultaneous activation of pathways, indicating rapid connectivity through the vadose zone, was seldom observed at the loam sites but occurred at clay sites during spring and summer. Surface flow at the loam sites was often generated as saturation‐excess, a phenomenon rarely observed on the clay sites. Contrary to expectations, significant differences in P loads in tiles were not apparent under the different response types. This may be due to the frequency of the water quality sampling or may indicate that factors other than surface‐tile hydrologic connectivity drive tile P concentrations. This work provides new insight into spatial and temporal differences in runoff mechanisms in tile‐drained landscapes. Core Ideas Activation of surface runoff and tile flow differ with soil texture and season. Timing of flow path activation was used to infer hydrological processes. Connectivity between the surface and tiles exists on clay soil during growing season. Rapid connectivity between the surface and tiles occurs less frequently on loam.

Assessing the potential impacts of dam operation on daily flow at ungauged river reaches - Mailhot, A.; Talbot, G.; Ricard, S.; Turcotte, R.; Guinard, K. (Journal of Hydrology: Regional Studies, 2018)

Improved historical reconstruction of daily flows and annual maxima in gauged and ungauged basins - Martel, Jean-Luc; Arsenault, Richard; Lachance-Cloutier, Simon; Castaneda-Gonzalez, Mariana; Turcotte, Richard; Poulin, Annie (Journal of Hydrology, 2023)

CMIP5 and CMIP6 Model Projection Comparison for Hydrological Impacts Over North America - Martel, J.‐L.; Brissette, F.; Troin, M.; Arsenault, R.; Chen, J.; Su, T.; Lucas‐Picher, P. (Geophysical Research Letters, 2022)
Abstract A warmer climate impacts streamflows and these changes need to be quantified to assess future risk, vulnerability, and to implement efficient adaptation measures. The climate simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), which have been the basis of most such assessments over the past decade, are being gradually superseded by the more recent Coupled Model Intercomparison Project Phase 6 (CMIP6). Our study portrays the added value of the CMIP6 ensemble over CMIP5 in a first North America wide comparison using 3,107 catchments. Results show a reduced spread of the CMIP6 ensemble compared to the CMIP5 ensemble for temperature and precipitation projections. In terms of flow indicators, the CMIP6 driven hydrological projections result in a smaller spread of future mean and high flow values, except for mountainous areas. Overall, we assess that the CMIP6 ensemble provides a narrower band of uncertainty of future climate projections, bringing more confidence for hydrological impact studies. , Plain Language Summary Greenhouse gas emissions are causing the climate to warm significantly, which in turn impacts flows in rivers worldwide. To adapt to these changes, it is essential to quantify them and assess future risk and vulnerability. Climate models are the primary tools used to achieve this. The main data set that provides scientists with state‐of‐the‐art climate model simulations is known as the Coupled Model Intercomparison Project (CMIP). The fifth phase of that project (CMIP5) has been used over the past decade in multiple hydrological studies to assess the impacts of climate change on streamflow. The more recent sixth phase (CMIP6) has started to generate projections, which brings the following question: is it necessary to update the hydrological impact studies performed using CMIP5 with the new CMIP6 models? To answer this question, a comparison between CMIP5 and CMIP6 using 3,107 catchments over North America was conducted. Results show that there is less spread in temperature and precipitation projections for CMIP6. This translates into a smaller spread of future mean, high and low flow values, except for mountainous areas. Overall, we assess that using the CMIP6 data set would provide a more concerted range of future climate projections, leading to more confident hydrological impact studies. , Key Points A comparison of hydrological impacts using Coupled Model Intercomparison Project version 5 (CMIP5) and Coupled Model Intercomparison Project Phase 6 (CMIP6) ensembles is performed over 3,107 catchments in North America The CMIP6 ensembles provide a narrower band of uncertainty for hydrological indicators in the future It is recommended to update hydrological impact studies performed using CMIP5 with the CMIP6 ensemble

Quantification of uncertainty in the assessment of future streamflow under changing climate conditions - Mandal, Sohom; Simonovic, Slobodan P. (Hydrological Processes, 2017)
Climate change has a significant influence on streamflow variation. The aim of this study is to quantify different sources of uncertainties in future streamflow projections due to climate change. For this purpose, 4 global climate models, 3 greenhouse gas emission scenarios (representative concentration pathways), 6 downscaling models, and a hydrologic model (UBCWM) are used. The assessment work is conducted for 2 different future time periods (2036 to 2065 and 2066 to 2095). Generalized extreme value distribution is used for the analysis of the flow frequency. Strathcona dam in the Campbell River basin, British Columbia, Canada, is used as a case study. The results show that the downscaling models contribute the highest amount of uncertainty to future streamflow predictions when compared to the contributions by global climate models or representative concentration pathways. It is also observed that the summer flows into Strathcona dam will decrease, and winter flows will increase in both future time periods. In addition to these, the flow magnitude becomes more uncertain for higher return periods in the Campbell River system under climate change.

Distribution of impacts of natural disasters across income groups: A case study of New Orleans - Masozera, Michel; Bailey, Melissa; Kerchner, Charles D. (Ecological Economics, 2007)

Calibration of a 3D hydrodynamic model for a hypertidal estuary with complex irregular bathymetry using adaptive parametrization of bottom roughness and eddy viscosity - Mohammadian, Abdolvahid; Morse, Brian; Robert, Jean-Loup (Estuarine, Coastal and Shelf Science, 2022)

Investigation of an Arctic hypertidal estuary under summer and winter conditions : cryo-hydrodynamic and hydrokinetic implications - Mohammadian, Abdolvahid (2021)
La modélisation numérique des estuaires hypertidaux intéresse particulièrement les ingénieurs impliqués dans la navigation maritime et le développement de projets d'énergie marémotrice. Au Québec (Canada), la majorité de ces estuaires à marée extrême sont situés dans des régions isolée de l'Arctique canadien et sont souvent des lieux de résidence des communautés autochtones du Nord canadien. La présente thèse vise à mieux comprendre les processus se manifestent dans ces environnements, avec une emphase particulière sur l'importance (1) de la forte dominance des marées, (2) de l'extrême variabilité bathymétrique et (3) de l'immense forçage climatique. La thèse tente de démontrer comment les modèles numériques peuvent être utilisés pour traiter ces particularités et peuvent être la meilleure méthode disponible pour étudier leurs effets dans des environnements éloignés peu étudies. Premièrement, dans le but d'évaluer le potentiel de courant de marée en eau libre (sans glace) de l'estuaire hypertidal de la rivière Koksoak (KRE), nous avons modélisé le débit de marée en utilisant un model numérique hydrodynamique réputé (Delft3D). Différents aspects de l'hydrodynamique côtière ont été étudiés grâce à la modélisation numérique 1D2D-3D. La variabilité spatio-temporelle de la densité de puissance hydrocinétique disponible a ensuite été quantifiée. Les résultats ont révélé l'énorme potentiel (1000 MW) d'énergie marémotrice présente à plusieurs endroits le long de l'estuaire, ce qui nécessite des études numériques plus approfondies. En mettant davantage l'accent sur la modélisation numérique du site, par exemple la publication d'un Atlas des courants de marée pour aider à la navigation maritime dans le KRE, nous avons constaté que certains problèmes de modélisation des estuaires n'étaient pas abordés. Compte tenu des conditions limites précises et des mesures in situ recueillies au cours de l'hiver 2017-2018, nous avons constaté que les meilleurs résultats pour l'étalonnage du modèle (niveau d'eau) en utilisant les paramètres/options disponibles conduisaient encore à certains ordres d'imprécision. sur les conditions aux limites de formse qualité (campagnes 2017-2018) qui ont effectivement amélioré les résultats numériques, nous avons constaté que les meilleurs résultats pour l'étalonnage du modèle (niveau d'eau) en utilisant les paramètres/options disponibles étaient encore associés à certains ordres d'imprécision. Par conséquent, l'objectif du deuxième travail était d'améliorer l'efficacité de la modélisation hydrodynamique pour les environnements de marée peu profonde. Nous avons introduit quelques hypothèses décrivant pourquoi les modèles de turbulence et de rugosité disponibles ne sont pas bien adaptés à la modélisation des estuaires avec de fortes variabilités spatiales et temporelles des profondeurs de marée. En conséquence (i) un modèle de turbulence k-ε étendu pour la paramétrisation adaptative de la viscosité turbulente en fonction de la profondeur, et une approche basée sur la direction de l'écoulement pour la paramétrisation de la rugosité du lit ont été développés, incorporés dans le modèle hydrodynamique employé (Delft3D). Le modèle modifié a montré une amélioration constante des prévisions du modèle dans les stations de champ proche et de champ lointain, par rapport aux schémas de paramétrage classiques. Enfin, un aspect manquant et mal compris des estuaires de latitude nordique est l'immense impact de l'hiver sur le flux des marées. Situé à la latitude 58°, le KRE subit l'effet intensif du climat arctique pendant la majeure partie de l'année, ce qui entraîne la formation de glace estuarienne rapide sur une grande partie de sa longueur. Plus précisément, et ce qui est le plus pertinent pour cette recherche, il est important de savoir comment le long hiver affecte les potentiels hydrocinétiques des estuaires des régions froides. Ainsi, la surfusion entraîne la formation de frasil et de glace de fond qui peuvent adhérer aux pales des turbines et provoquer leur dysfonctionnement. Dans les estuaires, la surfusion a une nature transitoire complexe car le point de congélation de l'eau salée est une fonction de la salinité et de la profondeur qui est changée par les marées au cours des cycles de marée. En raison du manque de données de terrain en hiver, nous avons collecté des paramètres hydrodynamiques en utilisant de nouvelles campagne de mesures en hiver 2018. Les observations ont montré que le risque de surfusion diminue à l'intérieur de l'estuaire, car en l'absence de débit fluvial, la salinité peut s'infiltrer beaucoup plus loin dans le fleuve. À l'intérieur, une modulation apparente de ∆T (la différence entre la température de l'eau et la température de congélation de l'eau), dépendant de la marée, a été observée avec une augmentation de la température pendant des marées montantes. Cette augmentation retarderait la surfusion, ce qui est un avantage majeur pour turbines. En réglant le module Delft3D-Ice, différents scénarios ont été définis pour l'étendue et l'épaisseur de la couvert de glace, et leurs réponses hydrodynamiques ont été analysées. Il a été démontré que la glace a des impacts complexes et non uniformes sur les caractéristiques hydrodynamiques de la KRE. Surtout, le débit des prismes de marée, qui est la principale source d'élan, peut être modifiée de manière démonstrative par la couverture de glace et la glace de marée plate. Les résultats suggèrent que les zones énergétiques sont légèrement affectées par la glace pendant la plus grande partie de l'hiver. Pendant l'hiver de pointe seulement, la glace pourrait considérablement diminuer densité moyenne de puissance des courants (par exemple, la puissance moyenne est égale ou supérieure à 7 kW m-2). Ces implications cryohydrodynamiques indiquent que l'hiver arctique n'est pas un obstacle à la production d'électricité dans le fleuve Koksoak, et l'énergie marémotrice serait un avantage annuel pour Kuujjuaq

Regional Frequency Analysis at Ungauged Sites with Multivariate Adaptive Regression Splines. - Msilini, A.; Masselot, Pierre; Ouarda, Taha B. M. J. (Journal of Hydrometeorology, 2020)
Hydrological systems are naturally complex and nonlinear. A large number of variables, many of which not yet well considered in regional frequency analysis (RFA), have a significant impact on hydrological dynamics and consequently on flood quantile estimates. Despite the increasing number of statistical tools used to estimate flood quantiles at ungauged sites, little attention has been dedicated to the development of new regional estimation (RE) models accounting for both nonlinear links and interactions between hydrological and physio-meteorological variables. The aim of this paper is to simultaneously take into account nonlinearity and interactions between variables by introducing the multivariate adaptive regression splines (MARS) approach in RFA. The predictive performances of MARS are compared with those obtained by one of the most robust RE models: the generalized additive model (GAM). Both approaches are applied to two datasets covering 151 hydrometric stations in the province of Quebec (Canada): a standard dataset (STA) containing commonly used variables and an extended dataset (EXTD) combining STA with additional variables dealing with drainage network characteristics. Results indicate that RE models using MARS with the EXTD outperform slightly RE models using GAM. Thus, MARS seems to allow for a better representation of the hydrological process and an increased predictive power in RFA.

Coupling the maximum overlap discrete wavelet transform and long short-term memory networks for irrigation flow forecasting - Mouatadid, Soukayna; Adamowski, Jan F.; Tiwari, Mukesh K.; Quilty, John M. (Agricultural Water Management, 2019)

Canadian snow and sea ice: historical trends and projections - Mudryk, Lawrence; Derksen, Chris; Howell, Stephen E. L.; Laliberté, Frédéric; Thackeray, Chad W.; Sospedra-Alfonso, Reinel; Vionnet, Vincent; Kushner, Paul J.; Brown, Ross (The Cryosphere, 2018)
The Canadian Sea Ice and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state of the art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. Here, we present an assessment from the CanSISE Network on trends in the historical record of snow cover (fraction, water equivalent) and sea ice (area, concentration, type, and thickness) across Canada. We also assess projected changes in snow cover and sea ice likely to occur by mid-century, as simulated by the Coupled Model Intercomparison Project Phase 5 (CMIP5) suite of Earth system models. The historical datasets show that the fraction of Canadian land and marine areas covered by snow and ice is decreasing over time, with seasonal and regional variability in the trends consistent with regional differences in surface temperature trends. In particular, summer sea ice cover has decreased significantly across nearly all Canadian marine regions, and the rate of multi-year ice loss in the Beaufort Sea and Canadian Arctic Archipelago has nearly doubled over the last 8 years. The multi-model consensus over the 2020–2050 period shows reductions in fall and spring snow cover fraction and sea ice concentration of 5–10% per decade (or 15–30% in total), with similar reductions in winter sea ice concentration in both Hudson Bay and eastern Canadian waters. Peak pre-melt terrestrial snow water equivalent reductions of up to 10% per decade (30% in total) are projected across southern Canada.

Exploring disaster impacts on adaptation actions in 549 cities worldwide - Nohrstedt, Daniel; Hileman, Jacob; Mazzoleni, Maurizio; Di Baldassarre, Guiliano; Parker, Charles F. (Nature Communications, 2022)
Whether disasters influence adaptation actions in cities is contested. Yet, the extant knowledge base primarily consists of single or small-N case studies, so there is no global overview of the evidence on disaster impacts and adaptation. Here, we use regression analysis to explore the effects of disaster frequency and severity on four adaptation action types in 549 cities. In countries with greater adaptive capacity, economic losses increase city-level actions targeting recently experienced disaster event types, as well as actions to strengthen general disaster preparedness. An increase in disaster frequency reduces actions targeting hazard types other than those that recently occurred, while human losses have few effects. Comparisons between cities across levels of adaptive capacity indicate a wealth effect. More affluent countries incur greater economic damages from disasters, but also have higher governance capacity, creating both incentives and opportunities for adaptation measures. While disaster frequency and severity had a limited impact on adaptation actions overall, results are sensitive to which disaster impacts, adaptation action types, and adaptive capacities are considered.

Value and Quality in the Dialectics between Human and Urban Capital of the City Networks on the Land District Scale - Nasca, Ludovica; Giuffrida, Salvatore; Trovato, Maria Rosa (Land, 2021)
This contribution proposes an inter-scalar and multi-polar analysis evaluation model of the territory of the Enna district, aimed at providing a robust axiological representation of the salient aspects of the general issue of internal areas, and therefore of the set of criticalities affecting them from the perspective of the human and urban capital they express. In the prospect of investigating the relations between urban and life quality – corresponding to the “city effect” – in the territorial context of each of the 20 municipalities of the Enna district, a hierarchical descriptive-valuation model was created, which coordinates a relevant amount of information units (data) and the corresponding attributes, indicators and indices that have been turned in aggregate value judgments attributed to each administrative land unit, from the perspectives of the criteria referred to as the main forms of the territorial capital. This is a multi-dimensional valuation model based on the Multi-Attribute Value Theory. Each survey and processing is mapped with different levels of detail at the scale of municipalities, census sections and cadastral land units. The outcome of this complex process of analysis and assessment provides multiple comparisons, revealing unexpected and sometimes counter-intuitive aspects in several municipalities, some of which are characterised by innovative prospects and opportunities for redevelopment of their historic centers. Correlations between information units at the different levels of the dendrogram have also indicated interesting trends and attitudes, whose comparisons can address territorial policies on both a local and provincial scale. Furthermore, the focus on the “cities network” is here assumed and proposed as the privileged point of observation of territory and the related aspects of the quality of life.

Disaster risk reduction and the limits of truisms: Improving the knowledge and practice interface - Nohrstedt, Daniel; Parker, Charles F.; von Uexkull, Nina; Mård, Johanna; Nyberg, Lars; Petrova, Kristina; Albrecht, Frederike; Göteman, Malin; Hileman, Jacob; Messori, Gabriele; Di Baldassarre, Giuliano (International journal of disaster risk reduction, 2021)
Abstract Action toward strengthened disaster risk reduction (DRR) ideally builds from evidence-based policymaking to inform decisions and priorities. This is a guiding principle for the Sendai Framework for Disaster Risk Reduction (SFDRR), which outlines priorities for action to reduce disaster risk. However, some of these practical guidelines conceal oversimplified or unsubstantiated claims and assumptions, what we refer to as “truisms”, which, if not properly addressed, may jeopardize the long-term goal to reduce disaster risks. Thus far, much DRR research has focused on ways to bridge the gap between science and practice while devoting less attention to the premises that shape the understanding of DRR issues. In this article, written in the spirit of a perspective piece on the state of the DRR field, we utilize the SFDRR as an illustrative case to identify and interrogate ten selected truisms, from across the social and natural sciences, that have been prevalent in shaping DRR research and practice. The ten truisms concern forecasting, loss, conflict, migration, the local level, collaboration, social capital, prevention, policy change, and risk awareness. We discuss central claims associated with each truism, relate those claims to insights in recent DRR scholarship, and end with suggestions for developing the field through advances in conceptualization, measurement, and causal inference.

Exposure to natural hazard events unassociated with policy change for improved disaster risk reduction - Nohrstedt, Daniel; Mazzoleni, Maurizio; Parker, Charles F.; Di Baldassarre, Giuliano (Nature Communications, 2021)
Abstract Natural hazard events provide opportunities for policy change to enhance disaster risk reduction (DRR), yet it remains unclear whether these events actually fulfill this transformative role around the world. Here, we investigate relationships between the frequency (number of events) and severity (fatalities, economic losses, and affected people) of natural hazards and DRR policy change in 85 countries over eight years. Our results show that frequency and severity factors are generally unassociated with improved DRR policy when controlling for income-levels, differences in starting policy values, and hazard event types. This is a robust result that accounts for event frequency and different hazard severity indicators, four baseline periods estimating hazard impacts, and multiple policy indicators. Although we show that natural hazards are unassociated with improved DRR policy globally, the study unveils variability in policy progress between countries experiencing similar levels of hazard frequency and severity.

A multiscale and multivariate analysis of precipitation and streamflow variability in relation to ENSO, NAO and PDO - Nalley, D.; Adamowski, J.; Biswas, A.; Gharabaghi, B.; Hu, W. (Journal of Hydrology, 2019)

Spatio-temporal analysis of rainfall trends in Chhattisgarh State, Central India over the last 115 years - Nema, Manish K.; Khare, Deepak; Adamowski, Jan; Chandniha, Surendra K. (Journal of Water and Land Development, 2018)
Abstract A quantitative and qualitative understanding of the anticipated climate-change-driven multi-scale spatio-temporal shifts in precipitation and attendant river flows is crucial to the development of water resources management approaches capable of sustaining and even improving the ecological and socioeconomic viability of rain-fed agricultural regions. A set of homogeneity tests for change point detection, non-parametric trend tests, and the Sen’s slope estimator were applied to long-term gridded rainfall records of 27 newly formed districts in Chhattisgarh State, India. Illustrating the impacts of climate change, an analysis of spatial variability, multi-temporal (monthly, seasonal, annual) trends and inter-annual variations in rainfall over the last 115 years (1901–2015 mean 1360 mm·y −1 ) showed an overall decline in rainfall, with 1961 being a change point year (i.e., shift from rising to declining trend) for most districts in Chhattisgarh. Spatio-temporal variations in rainfall within the state of Chhattisgarh showed a coefficient of variation of 19.77%. Strong inter-annual and seasonal variability in regional rainfall were noted. These rainfall trend analyses may help predict future climate scenarios and thereby allow planning of effective and sustainable water resources management for the region.

Multi-method Modeling Framework for Support of Integrated Water Resources Management - Nikolic, Vladimir V.; Simonovic, Slobodan P. (Environmental Processes, 2015)
The contemporary definition of integrated water resources management (IWRM) is introduced to promote a holistic approach in water engineering practices. IWRM deals with planning, design and operation of complex systems in order to control the quantity, quality, temporal and spatial distribution of water with the main objective of meeting human and ecological needs and providing protection from water related disasters. This paper examines the existing decision making support in IWRM practice, analyses the advantages and limitations of existing tools, and, as a result, suggests a generic multi-method modeling framework that has the main goal to capture all structural complexities of, and interactions within, a water resources system. Since the traditional tools do not provide sufficient support, this framework uses multi-method simulation technique to examine the codependence between water resources system and socioeconomic environment. Designed framework consists of (i) a spatial database, (ii) a traditional process-based model to represent the physical environment and changing conditions, and (iii) an agent-based spatially explicit model of socio-economic environment. The multi-agent model provides for building virtual complex systems composed of autonomous entities, which operate on local knowledge, possess limited abilities, affect and are affected by local environment, and thus, enact the desired global system behavior. Agent-based model is used in the presented work to analyze spatial dynamics of complex physical-social-economic-biologic systems. Based on the architecture of the generic multi-method modeling framework, an operational model for the Upper Thames River basin, Southwestern Ontario, Canada, is developed in cooperation with the local conservation authority. Six different experiments are designed by combining three climate and two socio-economic scenarios to analyze spatial dynamics of a complex physical-social-economic system of the Upper Thames River basin. Obtained results show strong dependence between changes in hydrologic regime, in this case surface runoff and groundwater recharge rates, and regional socio-economic activities.

A critical review on the application of the National Sanitation Foundation Water Quality Index - Noori, Roohollah; Berndtsson, Ronny; Hosseinzadeh, Majid; Adamowski, Jan Franklin; Abyaneh, Maryam Rabiee (Environmental Pollution, 2019)

Temporal and depth variation of water quality due to thermal stratification in Karkheh Reservoir, Iran - Noori, Roohollah; Berndtsson, Ronny; Franklin Adamowski, Jan; Rabiee Abyaneh, Maryam (Journal of Hydrology: Regional Studies, 2018)

Gérer les risques climatiques et faire face aux pertes et aux dommages - OCDE (OECD, 2022)

Mapping SWE in near real time across a large territory using a particle filter - Odry, Jean; Boucher, Marie-Amélie; Lachance Cloutier, Simon; Turcotte, Richard; Saint-Louis, Pierre-Yves (2020)
In snow-prone regions, snowmelt is one of the main drivers of runoff. For operational flood forecasting and mitigation, the spatial distribution of snow water equivalent (SWE) in near real time is necessary. In this context, in situ observations of SWE provide a valuable information. Nonetheless, the high spatial variability of snowpack characteristics makes it necessary to implement some kind of snow modelling to get a spatially continuous estimation. Data assimilation is thus a useful approach to combine information from both observation and modeling in near real-time. For example, at the provincial government of Quebec (eastern Canada), the HYDROTEL Snowpack Model is applied on a daily basis over a 0.1 degree resolution mesh covering the whole province. The modelled SWE is corrected in real time by in situ manual snow survey which are assimilated using a spatial particles filter (Cantet et al., 2019). This assimilation method improves the reliability of SWE estimation at ungauged sites. The availability of manual snow surveys is however limited both in space and time. These measurements are conducted on a bi-weekly basis in a limited number of sites. In order to further improve the temporal and spatial observation coverage, alternative sources of data should be considered. In this research, it is hypothesized that data gathered by SR50 sonic sensors can be assimilated in the spatial particle filter to improve the SWE estimation. These automatic sensors provide hourly measurements of snow depth and have been deployed in Quebec since 2005. Beforehand, probabilistic SWE estimations were derived from the SR50 snow depth measurements using an ensemble of artificial neural networks (Odry et al. 2019). Considering the nature of the data and the conversion process, the uncertainty associated with this dataset is supposed larger than for the manual snow surveys. The objective of the research is to evaluate the potential interest of adding this lower-quality information in the assimilation framework. The addition of frequent but uncertain data in the spatial particle filter required some adjustments in term of assimilation frequency and particle resampling. A reordering of the particles was implemented to maintain the spatial coherence between the different particles. With these changes, the consideration of both manual snow surveys and SR50 data in the spatial particle filter reached performances that are comparable to the initial particle filter that combines only the model and manual snow survey for estimating SWE in ungauged sites. However, the addition of SR50 data in the particle filter allows for continuous information in time, between manual snow surveys. References: Cantet, P., Boucher, M.-A., Lachance-Coutier, S., Turcotte, R., Fortin, V. (2019). Using a particle filter to estimate the spatial distribution of the snowpack water equivalent. J. Hydrometeorol, 20. Odry, J., Boucher, M.-A., Cantet,P., Lachance-Cloutier, S., Turcotte, R., St-Louis, P.-Y. (2019). Using artificial neural networks to estimate snow water equivalent from snow depth. Canadian water ressources journal (under review)

Développement d'un test d'adéquation sur les modèles d'échelle pour les maxima d'intensité de précipitations. Application aux courbes Intensité-Durée-Fréquence - Paoli, Auguste (Polytechnique Montréal, 2024)
RÉSUMÉ: Les courbes Intensité-Durée-Fréquence (IDF) sont l’outil mathématique principalement utilisé par les ingénieur(-e)s pour la modélisation des précipitations extrêmes à un endroit donné. Pour obtenir des courbes IDF fiables, des méthodes statistiques robustes sont nécessaires. L’utilisation de modèles d’échelle est indiquée pour estimer de façon plus précise les courbes IDF en réduisant le nombre de paramètres nécessaires pour modéliser le comportement ex-trême du processus de pluie. Un modèle d’échelle suppose l’existence d’une relation entre les distributions des maxima annuels d’intensité pour les différentes durées d’accumulation. Il existe différentes relations d’échelle possibles, donnant naissance à une variété de modèles. Dans ce mémoire, une procédure de test statistique est développée pour décider si un modèle d’échelle fixé est pertinent pour construire les courbes IDF à un endroit donné, basé sur les observations des maxima annuels historiques d’intensité de précipitations à cet endroit. Le test développé est une extension du test d’adéquation d’Anderson-Darling. Il implique de séparer la base de données en ensembles d’entraînement et de validation. L’ensemble d’entraînement est utilisé pour estimer les paramètres du modèle d’intérêt, et l’ensemble de validation est utilisé dans le calcul de la statistique. La distribution asymptotique de la statistique de test sous l’hypothèse nulle est établie dans un cadre général. Les quantiles de cette distribution théorique peuvent être approximés, ce qui permet de calculer analytiquement la région de rejet ainsi que la valeur-p pour le test. Dans le cas des courbes IDF, l’hypothèse nulle statue qu’un modèle d’échelle d’intérêt est adéquat. Les données sont des maxima d’intensité de précipitations. Les données correspondant à une durée d’accumulation fixée par l’utilisateur(trice) sont sélectionnées pour constituer l’ensemble de validation. Lorsque la durée choisie est la plus petite durée, les performances du test sont validées par une étude de simulation. Sous l’hypothèse nulle, le test rejette au taux nominal même pour des petits échantillons. Sous une hypothèse alternative (c’est-à-dire lorsque le modèle d’échelle utilisé pour générer les données s’écarte du modèle d’intérêt), le taux de rejet augmente avec la distance entre les modèles ainsi qu’avec la taille d’échantillon. Sur des données réelles, le test conduit à utiliser des modèles d’échelle différents à l’aéroport international Pierre-Elliott Trudeau de Montréal et à l’aérodrome Harbour de Vancouver. ABSTRACT: IDF curves are the primary mathematical tool used by engineers for modeling extreme precipitation at a given location. Reliable IDF curves require robust statistical methods. The use of scaling models allows for more precise estimations of IDF curves by reducing the num-ber of parameters needed to model the extreme behavior of the rainfall process. A scaling model assumes the existence of a relationship between the distributions of the annual inten-sity maxima accross the various accumulation durations. Diverse scaling relationships exist, giving rise to a variety of models. In this master thesis, a statistical testing procedure is developed to determine if a scaling model is suitable for constructing IDF curves at a given location, based on historical annual rain intensity maxima observed at that location. The developed test is an extension of the Anderson-Darling goodness-of-fit test. It involves splitting the database into training and validation sets. The training set is used to estimate the parameters of the model of interest, and the validation set is used in the calculation of the test statistic. The asymptotic distribution of the test statistic under the null hypothe-sis is established in a general framework. Quantiles of this theoretical distribution can be approximated, allowing for the analytical calculation of the rejection region as well as the p-value for the test. In the case of IDF curves, the null hypothesis states that a target scaling model is adequate. The data consist of precipitation intensity maxima. Data corresponding to a duration fixed by the user are selected to constitute the validation set. When the chosen duration is the smallest duration, the performances of the test are validated through a simulation study. Under the null hypothesis, the test maintains the nominal rejection rate even for small samples. Under an alternative hypothesis (i.e., when the scaling model used to generate the data deviates from the target model), the rejection rate increases with the discrepancy between the models as well as with the sample size. When applied to historical data, the test suggests the use of different scaling models at the Montréal Pierre-Elliott Trudeau international airport and at the Vancouver Harbour aerodrome.

Thermal exposure risk in different life stages of Chinook salmon in the Nechako River system, British Columbia - Oyinlola, Muhammed Alolade; Khorsandi, Mostafa; Mayer, Noa; Butler, Natalie; Wert, Jacey C. Van; Eliason, Erika J.; Arsenault, Richard; Brauner, Colin J.; Hinch, Scott G.; St-Hilaire, Andre (2024)
Abstract Climate change is affecting freshwater systems, leading to increased water temperatures, which is posing a threat to freshwater ecological communities. In the Nechako River, a water management program has been in place since the 1980s to maintain water temperatures at 20°C during the migration of Sockeye salmon. However, the program's effectiveness in mitigating the impacts of climate change on resident species like Chinook salmon's thermal exposure is uncertain. In this study, we utilised the CEQUEAU hydrological model and life stage-specific physiological data to evaluate the consequences of the current program on Chinook salmon's thermal exposure under two contrasting climate change and socio-economic scenarios (SSP2-4.5 and SSP5-8.5). The results indicate that the thermal exposure risk is projected to be above the optimal threshold for parr and adult life stages under both scenarios relative to the 1980s. These life stages could face an increase in thermal exposure ranging from up to 2 and 5 times by 2090s relative to the 1980s during the months they occurred under the SSP5-8.5 scenario, including when the program is active (July 20th to August 20th). Additionally, our study shows that climate change will result in a substantial rise in cumulative heat degree days, ranging from 1.9 to 5.8 times (2050s) and 2.9 to 12.9 times (2090s) in comparison to the 1980s under SSP5-8.5. Our study highlights the need for a holistic approach to review the current Nechako management plan and consider all species in the Nechako River system in the face of climate change.

Arctic precipitation and surface wind speed associated with cyclones in a changing climate - Oh, Seok-Geun; Sushama, Laxmi; Teufel, Bernardo (Climate Dynamics, 2020)

Introduction of the GAM model for regional low-flow frequency analysis at ungauged basins and comparison with commonly used approaches - Ouarda, Taha B. M. J.; Charron, Christian; Hundecha, Yeshewatesfa; St-Hilaire, André; Chebana, Fateh (Environmental Modelling and Software, 2018)
Generalized Additive Models (GAMs) are introduced in this study for the regional estimation of low-flow characteristics at ungauged basins and compared to other approaches commonly used for this purpose. GAMs provide more flexibility in the shape of the relationships between the response and explanatory variables in comparison to classical models such as multiple linear regression (MLR). Homogeneous regions are defined here using the methods of hierarchical cluster analysis, canonical correlation analysis and region of influence. GAMs and MLR are then used within the delineated regions and also for the whole study area. In addition, a spatial interpolation method is also tested. The different models are applied for the regional estimation of summer and winter low-flow quantiles at stations in Quebec, Canada. Results show that for a given regional delineation method, GAMs provide improved performances compared to MLR.

Applying the Theory of Reliability to the Assessment of Hazard, Risk and Safety in a Hydrologic System: A Case Study in the Upper Sola River Catchment, Poland - Ozga-Zielinski, Bogdan; Adamowski, Jan; Ciupak, Maurycy (Water, 2018)

Transparency on Underlying Values is Needed for Useful Equity Measurements - Pollack, Adam; Helgeson, Casey; Kousky, Carolyn; Keller, Klaus (2023)

Mercury, selenium and arsenic concentrations in Canadian freshwater fish and a perspective on human consumption intake and risk - Ponton, Dominic E.; Ruelas-Inzunza, Jorge; Lavoie, Raphael A.; Lescord, Gretchen L.; Johnston, Thomas A.; Graydon, Jennifer A.; Reichert, Megan; Donadt, Caitlyn; Poesch, Mark; Gunn, John M.; Amyot, Marc (Journal of Hazardous Materials Advances, 2022)

Evaluation of a Coupled CFD and Multi-Body Motion Model for Ice-Structure Interaction Simulation - Pourshahbaz, Hanif; Ghobrial, Tadros; Shakibaeinia, Ahmad (Water, 2024)
The interaction of water flow, ice, and structures is common in fluvial ice processes, particularly around Ice Control Structures (ICSs) that are used to manage and prevent ice jam floods. To evaluate the effectiveness of ICSs, it is essential to understand the complex interaction between water flow, ice and the structure. Numerical modeling is a valuable tool that can facilitate such understanding. Until now, classical Eulerian mesh-based methods have not been evaluated for the simulation of ice interaction with ICS. In this paper we evaluate the capability, accuracy, and efficiency of a coupled Computational Fluid Dynamic (CFD) and multi-body motion numerical model, based on the mesh-based FLOW-3D V.2023 R1 software for simulation of ice-structure interactions in several benchmark cases. The model’s performance was compared with results from meshless-based models (performed by others) for the same laboratory test cases that were used as a reference for the comparison. To this end, simulation results from a range of dam break laboratory experiments were analyzed, encompassing varying numbers of floating objects with distinct characteristics, both in the presence and absence of ICS, and under different downstream water levels. The results show that the overall accuracy of the FLOW-3D model under various experimental conditions resulted in a RMSE of 0.0534 as opposed to an overall RMSE of 0.0599 for the meshless methods. Instabilities were observed in the FLOW-3D model for more complex phenomena that involve open boundaries and a larger number of blocks. Although the FLOW-3D model exhibited a similar computational time to the GPU-accelerated meshless-based models, constraints on the processors speed and the number of cores available for use by the processors could limit the computational time.
Keywords: Infolettre; Infolettre_Octobre_2024

An Entropy-Based Approach to Fuzzy Multi-objective Optimization of Reservoir Water Quality Monitoring Networks Considering Uncertainties - Pourshahabi, Shokoufeh; Nikoo, Mohammad Reza; Raei, Ehsan; Adamowski, Jan Franklin (Water Resources Management, 2018)

Understanding the influence of “hot” models in climate impact studies: a hydrological perspective - Rahimpour Asenjan, Mehrad; Brissette, Francois; Martel, Jean-Luc; Arsenault, Richard (Hydrology and Earth System Sciences, 2023)
Abstract. Efficient adaptation strategies to climate change require the estimation of future impacts and the uncertainty surrounding this estimation. Over- or underestimating future uncertainty may lead to maladaptation. Hydrological impact studies typically use a top-down approach in which multiple climate models are used to assess the uncertainty related to the climate model structure and climate sensitivity. Despite ongoing debate, impact modelers have typically embraced the concept of “model democracy”, in which each climate model is considered equally fit. The newer Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations, with several models showing a climate sensitivity larger than that of Phase 5 (CMIP5) and larger than the likely range based on past climate information and understanding of planetary physics, have reignited the model democracy debate. Some have suggested that “hot” models be removed from impact studies to avoid skewing impact results toward unlikely futures. Indeed, the inclusion of these models in impact studies carries a significant risk of overestimating the impact of climate change. This large-sample study looks at the impact of removing hot models on the projections of future streamflow over 3107 North American catchments. More precisely, the variability in future projections of mean, high, and low flows is evaluated using an ensemble of 19 CMIP6 general circulation models (GCMs), 5 of which are deemed hot based on their global equilibrium climate sensitivity (ECS). The results show that the reduced ensemble of 14 climate models provides streamflow projections with reduced future variability for Canada, Alaska, the Southeast US, and along the Pacific coast. Elsewhere, the reduced ensemble has either no impact or results in increased variability in future streamflow, indicating that global outlier climate models do not necessarily provide regional outlier projections of future impacts. These results emphasize the delicate nature of climate model selection, especially based on global fitness metrics that may not be appropriate for local and regional assessments.

Time-Varying Univariate and Bivariate Frequency Analysis of Nonstationary Extreme Sea Level for New York City - Razmi, Ali; Mardani-Fard, Heydar Ali; Golian, Saeed; Zahmatkesh, Zahra (Environmental Processes, 2022)

Implementation of a Semi-Lagrangian Fully Implicit Time Integration of the Unified Soundproof System of Equations for Numerical Weather Prediction - Qaddouri, Abdessamad; Girard, Claude; Husain, Syed Zahid; Aider, Rabah (Monthly Weather Review, 2021)
Abstract An alternate dynamical core that employs the unified equations of A. Arakawa and C.S. Konor (2009) has been developed within Environment and Climate change Canada’s GEM (Global Environmental Multiscale) atmospheric model. As in the operational GEM dynamical core, the novel core utilizes the same fully-implicit two-time-level semi-Lagrangian scheme for time discretization while the log-pressure-based terrain-following vertical coordinate has been slightly adapted. Overall, the new dynamical core implementation required only minor changes to the existing informatics code of the GEM model and from a computational performance perspective, the new core does not incur any significant additional cost. A broad range of tests – that include both two-dimensional idealized theoretical cases and three-dimensional deterministic forecasts covering both hydrostatic and non-hydrostatic scales–have been carried out to evaluate the performance of the new dynamical core. For all the tested cases, when compared to the operational GEM model, the new dynamical core based on the unified equations has been found to produce statistically equivalent results. These results imply that the unified equations can be adopted for operational numerical weather prediction that would employ a single soundproof system of equations to produce reliable forecasts for all meteorological scales of interest with negligible changes for the computational overhead.

Asynchronous Hydroclimatic Modeling for the Construction of Physically Based Streamflow Projections in a Context of Observation Scarcity - Ricard, Simon; Sylvain, Jean-Daniel; Anctil, François (Frontiers in Earth Science, 2020)

A stochastic wavelet-based data-driven framework for forecasting uncertain multiscale hydrological and water resources processes - Quilty, John; Adamowski, Jan (Environmental Modelling & Software, 2020)

Forcing the Penman-Montheith Formulation with Humidity, Radiation, and Wind Speed Taken from Reanalyses, for Hydrologic Modeling - Ricard, Simon; Anctil, François (Water, 2019)
The Penman-Monteith reference evapotranspiration (ET0) formulation was forced with humidity, radiation, and wind speed (HRW) fields simulated by four reanalyses in order to simulate hydrologic processes over six mid-sized nivo-pluvial watersheds in southern Quebec, Canada. The resulting simulated hydrologic response is comparable to an empirical ET0 formulation based exclusively on air temperature. However, Penman-Montheith provides a sounder representation of the existing relations between evapotranspiration fluctuations and climate drivers. Correcting HRW fields significantly improves the hydrologic bias over the pluvial period (June to November). The latter did not translate into an increase of the hydrologic performance according to the Kling-Gupta Efficiency (KGE) metric. The suggested approach allows for the implementation of physically-based ET0 formulations where HRW observations are insufficient for the calibration and validation of hydrologic models and a potential reinforcement of the confidence affecting the projection of low flow regimes and water availability.

A Stochastic Data‐Driven Ensemble Forecasting Framework for Water Resources: A Case Study Using Ensemble Members Derived From a Database of Deterministic Wavelet‐Based Models - Quilty, John; Adamowski, Jan; Boucher, Marie‐Amélie (Water Resources Research, 2019)
Abstract In water resources applications (e.g., streamflow, rainfall‐runoff, urban water demand [UWD], etc.), ensemble member selection and ensemble member weighting are two difficult yet important tasks in the development of ensemble forecasting systems. We propose and test a stochastic data‐driven ensemble forecasting framework that uses archived deterministic forecasts as input and results in probabilistic water resources forecasts. In addition to input data and (ensemble) model output uncertainty, the proposed approach integrates both ensemble member selection and weighting uncertainties, using input variable selection and data‐driven methods, respectively. Therefore, it does not require one to perform ensemble member selection and weighting separately. We applied the proposed forecasting framework to a previous real‐world case study in Montreal, Canada, to forecast daily UWD at multiple lead times. Using wavelet‐based forecasts as input data, we develop the Ensemble Wavelet‐Stochastic Data‐Driven Forecasting Framework, the first multiwavelet ensemble stochastic forecasting framework that produces probabilistic forecasts. For the considered case study, several variants of Ensemble Wavelet‐Stochastic Data‐Driven Forecasting Framework, produced using different input variable selection methods (partial correlation input selection and Edgeworth Approximations‐based conditional mutual information) and data‐driven models (multiple linear regression, extreme learning machines, and second‐order Volterra series models), are shown to outperform wavelet‐ and nonwavelet‐based benchmarks, especially during a heat wave (first time studied in the UWD forecasting literature). , Key Points A stochastic data‐driven ensemble framework is introduced for probabilistic water resources forecasting Ensemble member selection and weighting uncertainties are explicitly considered alongside input data and model output uncertainties Wavelet‐based model outputs are used as input to the framework for an urban water demand forecasting study outperforming benchmark methods

Estimates of gridded relative changes in 24-h extreme rainfall intensities based on pooled frequency analysis - Requena, Ana I.; Burn, Donald H.; Coulibaly, Paulin (Journal of Hydrology, 2019)

A functional framework for flow-duration-curve and daily streamflow estimation at ungauged sites - Requena, Ana Isabel; Chebana, Fateh; Ouarda, Taha B. M. J. (Advances in Water Resources, 2018)
Abstract Flow duration curves (FDC) are used to obtain daily streamflow series at ungauged sites. In this study, functional multiple regression (FMR) is proposed for FDC estimation. Its natural framework for dealing with curves allows obtaining the FDC as a whole instead of a limited number of single points. FMR assessment is performed through a case study in Quebec, Canada. FMR provides a better mean FDC estimation when obtained over sites by considering simultaneously all FDC quantiles in the assessment of each given site. However, traditional regression provides a better mean FDC estimation when obtained over given FDC quantiles by considering all sites in the assessment of each quantile separately. Mean daily streamflow estimation is similar; yet FMR provides an improved estimation for most sites. Furthermore, FMR represents a more suitable framework and provides a number of practical advantages, such as insight into descriptor influence on FDC quantiles. Hence, traditional regression may be preferred if only few FDC quantiles are of interest; whereas FMR would be more suitable if a large number of FDC quantiles is of interest, and therefore to estimate daily streamflows.

Addressing the incorrect usage of wavelet-based hydrological and water resources forecasting models for real-world applications with best practices and a new forecasting framework - Quilty, John; Adamowski, Jan (Journal of Hydrology, 2018)

A New Approach to Predict Daily pH in Rivers Based on the “à trous” Redundant Wavelet Transform Algorithm - Rajaee, Taher; Ravansalar, Masoud; Adamowski, Jan F.; Deo, Ravinesh C. (Water, Air, & Soil Pollution, 2018)

Institutions and the losses from natural disasters - Raschky, Paul A. (Natural Hazards and Earth System Sciences, 2008)
Abstract. Natural hazards can be seen as a function of a specific natural process and human (economic) activity. Whereby the bulk of literature on natural hazard management has its focus on the natural process, an increasing number of scholars is emphasizing the importance of human activity in this context. Existing literature has identified certain socio-economic factors that determine the impact of natural disasters on society. The purpose of this paper is to highlight the effects of the institutional framework that influences human behavior by setting incentives and to point out the importance of institutional vulnerability. Results from an empirical investigation of large scale natural disasters between 1984 and 2004 show that countries with better institutions experience less victims and lower economic losses from natural disasters. In addition, the results suggest a non-linear relationship between economic development and economic disaster losses. The suggestions in this paper have implications for the discussion on how to deal with the adverse effects of natural hazards and how to develop efficient adaption strategies.

Recherche en Prévision Numérique Contributions to Numerical Weather Prediction - Ritchie, H.; Bélair, Stéphane; Bernier, Natacha B.; Buehner, Mark; Charron, Martin; Fortin, Vincent; Garand, L.; Houtekamer, P.; Husain, Syed Zahid; Laroche, Stéphane; Lemieux, Jean-Franois; Lin, Hai; et al. (Atmosphere-ocean, 2022)
This is a review article invited by Atmosphere-Ocean to document the contributions of Recherche en Prévision Numérique (RPN) to Numerical Weather Prediction (NWP). It is structured as a historical review and documents RPN’s contributions to numerical methods, numerical modelling, data assimilation, and ensemble systems, with a look ahead to potential future systems. Through this review, we highlight the evolution of RPN’s contributions. We begin with early NWP efforts and continue through to environmental predictions with a broad range of applications. This synthesis is intended to be a helpful reference, consolidating developments and generating broader interest for future work on NWP in Canada.

Assessing structural, functional and effective hydrologic connectivity with brain neuroscience methods: State-of-the-art and research directions - Rinderer, Michael; Ali, Genevieve; Larsen, Laurel G. (Earth-Science Reviews, 2018)

Exploring the effects of climatic variables on monthly precipitation variation using a continuous wavelet-based multiscale entropy approach - Roushangar, Kiyoumars; Alizadeh, Farhad; Adamowski, Jan (Environmental Research, 2018)

A novel method to estimate the maximization ratio of the Probable Maximum Precipitation (PMP) using regional climate model output - Rouhani, Hassan; Leconte, Robert (Water Resources Research, 2016)
The moisture maximization approach to estimate the Probable Maximum Precipitation (PMP) has a simple technique for controlling the risk of overestimating PMP: the maximization ratio is limited by an upper bound. The upper bound limit depends on storm records and watershed characteristics. However, it is not readily available in many watersheds. A robust scientific justification for limiting the maximization ratio is missing. In this paper, a novel approach is proposed to estimate the maximization ratio which does not impose an upper limit to the ratio. The new approach, which uses regional climate model data, is based on constructing annual maximum precipitable water time series with precipitable water values for which atmospheric variables are similar to the original event to be maximized. These time series are then used to estimate the 100-year return period precipitable water value required to calculate the maximization ratio. The new approach was tested in three watersheds in the province of Quebec, Canada. Results showed that maximization ratio values were lower than the proposed upper bound value for these watersheds. In comparison to the approach using an upper bound, this proposed approach reduced PMP in these watersheds by 11%. This article is protected by copyright. All rights reserved.

Comparing a long short-term memory (LSTM) neural network with a physically-based hydrological model for streamflow forecasting over a Canadian catchment - Sabzipour, Behmard; Arsenault, Richard; Troin, Magali; Martel, Jean-Luc; Brissette, François; Brunet, Frédéric; Mai, Juliane (Journal of Hydrology, 2023)
Keywords: Brunet_Alain

Metadata record for: A comprehensive, multisource database for hydrometeorological modeling of 14,425 North American watersheds - Scientific Data Curation Team (2020)
This dataset contains key characteristics about the data described in the Data Descriptor A comprehensive, multisource database for hydrometeorological modeling of 14,425 North American watersheds. Contents: 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format

Metadata record for: A global database of Holocene paleotemperature records - Scientific Data Curation Team (2020)
This dataset contains key characteristics about the data described in the Data Descriptor A global database of Holocene paleotemperature records. Contents: 1. human readable metadata summary table in CSV format 2. machine readable metadata file in JSON format

Laboratory study of the properties of frazil ice particles and flocs in water of different salinities - Schneck, Christopher C.; Ghobrial, Tadros R.; Loewen, Mark R. (The Cryosphere, 2019)
Abstract. Measurements of the size and shape of frazil ice particles and flocs in saline water and of frazil ice flocs in freshwater are limited. This study consisted of a series of laboratory experiments producing frazil ice at salinities of 0 ‰, 15 ‰, 25 ‰ and 35 ‰ to address this lack of data. The experiments were conducted in a large tank in a cold room with bottom-mounted propellers to create turbulence. A high-resolution camera system was used to capture images of frazil ice particles and flocs passing through cross-polarizing lenses. The high-resolution images of the frazil ice were processed using a computer algorithm to differentiate particles from flocs and determine key properties including size, concentration and volume. The size and volume distributions of particles and flocs at all four salinities were found to fit log-normal distributions closely. The concentration, mean size, and standard deviation of flocs and particles were assessed at different times during the supercooling process to determine how these properties evolve with time. Comparisons were made to determine the effect of salinity on the properties of frazil ice particles and flocs. The overall mean size of frazil ice particles in saline water and freshwater was found to range between 0.52 and 0.45 mm, with particles sizes in freshwater ∼13 % larger than in saline water. However, qualitative observations showed that frazil ice particles in saline water tend to be more irregularly shaped. The overall mean size of flocs in freshwater was 2.57 mm compared to a mean size of 1.47 mm for flocs in saline water. The average growth rate of frazil particles was found to be 0.174, 0.070, 0.033, and 0.024 mm min−1 and the average floc growth rate was 0.408, 0.118, 0.089, and 0.072 mm min−1 for the 0 ‰, 15 ‰, 25 ‰, and 35 ‰, respectively. Estimates for the porosity of frazil ice flocs were made by equating the estimated volume of ice produced based on thermodynamic conditions to the estimated volume of ice determined from the digital images. The estimated porosities of frazil ice flocs were determined to be 0.86, 0.82, 0.8 and 0.75 for 0 ‰, 15 ‰, 25 ‰ and 35 ‰ saline water, respectively.

Coupling large-scale climate indices with a stochastic weather generator to improve long-term streamflow forecasts in a Canadian watershed - Sohrabi, Samaneh; Brissette, François P.; Arsenault, Richard (Journal of Hydrology, 2021)

Hydrological modeling of freshwater discharge into Hudson Bay using HYPE - Stadnyk, Tricia A.; MacDonald, Matthew K.; Tefs, Andrew; Déry, Stephen J.; Koenig, Kristina A.; Gustafsson, David; Isberg, Kristina; Arheimer, Berit (2020)
This study details the enhancement and calibration of the Arctic implementation of the HYdrological Predictions for the Environment (HYPE) hydrological model established for the BaySys group of projects to produce freshwater discharge scenarios for the Hudson Bay Drainage Basin (HBDB). The challenge in producing estimates of freshwater discharge for the HBDB is that it spans over a third of Canada’s continental landmass and is 40% ungauged. Scenarios for BaySys require the separation between human and climate interactions, specifically the separation of regulated river discharge from a natural, climate-driven response. We present three key improvements to the modelling system required to support the identification of natural from anthropogenic impacts: representation of prairie disconnected landscapes (i.e., non-contributing areas), a method to generalize lake storage-discharge parameters across large regions, and frozen soil modifications. Additionally, a unique approach to account for irregular hydrometric gauge density across the basins during model calibration is presented that avoids overfitting parameters to the densely gauged southern regions. We summarize our methodologies used to facilitate improved separation of human and climate driven impacts to streamflow within the basin and outline the baseline discharge simulations used for the BaySys group of projects. Challenges remain for modeling the most northern reaches of the basin, and in the lake-dominated watersheds. The techniques presented in this work, particularly the lake and flow signature clusters, may be applied to other high latitude, ungauged Arctic basins. Discharge simulations are subsequently used as input data for oceanographic, biogeochemical, and ecosystem studies across the HBDB.

Roadmap towards justice in urban climate adaptation research - Shi, Linda; Chu, Eric; Anguelovski, Isabelle; Aylett, Alexander; Debats, Jessica; Goh, Kian; Schenk, Todd; Seto, Karen C.; Dodman, David; Roberts, Debra; Roberts, J. Timmons; VanDeveer, Stacy D. (Nature Climate Change, 2016)

Natural Disaster Impacts and Fiscal Decentralization - Skidmore, Mark; Toya, Hideki (Land Economics, 2013)
In recent years, many developing countries have sought to implement more decentralized governmental systems. Despite efforts toward fiscal federalism, assessment of decentralization activity has been hampered by lack of consistent cross-country measures of effectiveness. Since governments play a central role in the management of catastrophic events, disaster impact data provide an opportunity to evaluate whether government structure is important in limiting disaster losses. We use cross-country data over the 1970–2005 period to estimate the relationship between decentralization and disaster casualties; countries with more decentralized governments experience fewer disaster-induced fatalities.

Climate Gentrification: Risk, Rent, and Restructuring in Greater Miami - Taylor, Zac J.; Aalbers, Manuel B. (Annals of the American Association of Geographers, 2022)

Human–water research: discussion of “guiding principles for hydrologists conducting interdisciplinary research and fieldwork with participants” - Thaler, Thomas (Hydrological Sciences Journal-journal Des Sciences Hydrologiques, 2022)
Rangecroft et al. provide an important and interesting paper on the challenges of interdisciplinary research and fieldwork with participants in water resource management. The paper shows the challenges of interaction between their research areas and demonstrates the importance of how a researcher interacts with their selected study sites. My key points reflect the use of different methodologies within social and natural sciences and across them as well as the main challenge of who has the power to influence the research directions. Research is not value-free and is highly influenced by one’s own training and knowledge, which needs to be addressed in the research activities. Finally, an option might be to move beyond interdisciplinary constraints and to work within a stronger transdisciplinary framework. Water research very much needs to interact with non-academic people to understand the challenges and possible solutions.

Catchment Scale Evaluation of Multiple Global Hydrological Models from ISIMIP2a over North America - Troin, Magali; Arsenault, Richard; Fournier, Elyse; Brissette, François (Water, 2021)
A satisfactory performance of hydrological models under historical climate conditions is considered a prerequisite step in any hydrological climate change impact study. Despite the significant interest in global hydrological modeling, few systematic evaluations of global hydrological models (gHMs) at the catchment scale have been carried out. This study investigates the performance of 4 gHMs driven by 4 global observation-based meteorological inputs at simulating weekly discharges over 198 large-sized North American catchments for the 1971–2010 period. The 16 discharge simulations serve as the basis for evaluating gHM accuracy at the catchment scale within the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a). The simulated discharges by the four gHMs are compared against observed and simulated weekly discharge values by two regional hydrological models (rHMs) driven by a global meteorological dataset for the same period. We discuss the implications of both modeling approaches as well as the influence of catchment characteristics and global meteorological forcing in terms of model performance through statistical criteria and visual hydrograph comparison for catchment-scale hydrological studies. Overall, the gHM discharge statistics exhibit poor agreement with observations at the catchment scale and manifest considerable bias and errors in seasonal flow simulations. We confirm that the gHM approach, as experimentally implemented through the ISIMIP2a, must be used with caution for regional studies. We find the rHM approach to be more trustworthy and recommend using it for hydrological studies, especially if findings are intended to support operational decision-making.

Generating Ensemble Streamflow Forecasts: A Review of Methods and Approaches Over the Past 40 Years - Troin, Magali; Arsenault, Richard; Wood, Andrew W.; Brissette, François; Martel, Jean‐Luc (Water Resources Research, 2021)
Abstract Ensemble forecasting applied to the field of hydrology is currently an established area of research embracing a broad spectrum of operational situations. This work catalogs the various pathways of ensemble streamflow forecasting based on an exhaustive review of more than 700 studies over the last 40 years. We focus on the advanced state of the art in the model‐based (dynamical) ensemble forecasting approaches. Ensemble streamflow prediction systems are categorized into three leading classes: statistics‐based streamflow prediction systems, climatology‐based ensemble streamflow prediction systems and numerical weather prediction‐based hydrological ensemble prediction systems. For each ensemble approach, technical information, as well as details about its strengths and weaknesses, are provided based on a critical review of the studies listed. Through this literature review, the performance and uncertainty associated with the ensemble forecasting systems are underlined from both operational and scientific viewpoints. Finally, the remaining key challenges and prospective future research directions are presented, notably through hybrid dynamical ‐ statistical learning approaches, which obviously present new challenges to be overcome in order to allow the successful employment of ensemble streamflow forecasting systems in the next decades. Targeting students, researchers and practitioners, this review provides a detailed perspective on the major features of an increasingly important area of hydrological forecasting. , Key Points This work summarizes the 40 years of research in the generation of streamflow forecasts based on an exhaustive review of studies Ensemble prediction systems are categorized into three classes: statistics‐based, climatology‐based and numerical weather prediction‐based hydrological ensemble prediction systems For each ensemble forecasting system, thorough technical information is provided

Comparing statistical post-processing of regional and global climate scenarios for hydrological impacts assessment: a case study of two canadian catchments - Troin, Magali; Velázquez, Juan Alberto; Caya, Daniel; Brissette, François (Journal of Hydrology, 2015)
Summary Projected climate change effects on streamflow are investigated for the 2041–2070 horizon following the SRES A2 emissions scenario over two snowmelt-dominated catchments in Canada. A 16-member ensemble of SWAT hydrological model (HM) simulations, based on a comprehensive ensemble of the Canadian Regional Climate Model (CRCM) simulations driven by two global climate models (GCMs), with five realizations of the Canadian CGCM3 and three realizations of the German ECHAM5 is established per catchment. This study aims to evaluate, once model bias has been removed by statistical post-processing (SP), how the RCM-simulated climate changes differ from those of the parent GCMs, and how they affect the assessment of climate change-induced hydrological impacts at the catchment scale. The variability of streamflow caused by the use of different SP methods (mean-based versus distribution-based) within each statistical post-processing pathway of climate model outputs (bias correction versus perturbation) is also evaluated, as well as the uncertainty of natural climate variability. The simulations cover 1971–2000 in the reference period and 2041–2070 in the future period. For a set of criteria, results based on raw and statistically post-processed model outputs for the reference climate are compared with observations. This process demonstrates that SP is important not only for GCMs outputs, but also for CRCM outputs. SP leads to a high level of agreement between the CRCM and the driving GCMs in reproducing patterns of observed climate. The ensemble spread of the climate change signal on streamflow is large and varies with catchments and hydrological periods (winter/summer flows). The results of various hydrological indicators show that most of the uncertainty arises from the natural climate variability followed by the statistical post-processing. The uncertainty linked to the choice of statistical pathway is much larger than that associated with the choice of the method in quantifying the hydrological impacts. We find that the incorporation of dynamical downscaling of global models through the CRCM as an intermediate step in the GCM–RCM–SP–HM model chain does not lead to considerable differences in the assessment of the climate change impacts on streamflow for the study catchments.

Satellite-Based Human Settlement Datasets Inadequately Detect Refugee Settlements: A Critical Assessment at Thirty Refugee Settlements in Uganda - Van Den Hoek, Jamon; Friedrich, Hannah K. (Remote Sensing, 2021)
Satellite-based broad-scale (i.e., global and continental) human settlement data are essential for diverse applications spanning climate hazard mitigation, sustainable development monitoring, spatial epidemiology and demographic modeling. Many human settlement products report exceptional detection accuracies above 85%, but there is a substantial blind spot in that product validation typically focuses on large urban areas and excludes rural, small-scale settlements that are home to 3.4 billion people around the world. In this study, we make use of a data-rich sample of 30 refugee settlements in Uganda to assess the small-scale settlement detection by four human settlement products, namely, Geo-Referenced Infrastructure and Demographic Data for Development settlement extent data (GRID3-SE), Global Human Settlements Built-Up Sentinel-2 (GHS-BUILT-S2), High Resolution Settlement Layer (HRSL) and World Settlement Footprint (WSF). We measured each product’s areal coverage within refugee settlement boundaries, assessed detection of 317,416 building footprints and examined spatial agreement among products. For settlements established before 2016, products had low median probability of detection and F1-score of 0.26 and 0.24, respectively, a high median false alarm rate of 0.59 and tended to only agree in regions with the highest building density. Individually, GRID3-SE offered more than five-fold the coverage of other products, GHS-BUILT-S2 underestimated the building footprint area by a median 50% and HRSL slightly underestimated the footprint area by a median 7%, while WSF entirely overlooked 8 of the 30 study refugee settlements. The variable rates of coverage and detection partly result from GRID3-SE and HRSL being based on much higher resolution imagery, compared to GHS-BUILT-S2 and WSF. Earlier established settlements were generally better detected than recently established settlements, showing that the timing of satellite image acquisition with respect to refugee settlement establishment also influenced detection results. Nonetheless, settlements established in the 1960s and 1980s were inconsistently detected by settlement products. These findings show that human settlement products have far to go in capturing small-scale refugee settlements and would benefit from incorporating refugee settlements in training and validating human settlement detection approaches.

A database of Holocene temperature records for north‐eastern North America and the north‐western Atlantic - Van Bellen, Simon; De Vernal, Anne; To, Anna; Ouellet‐Bernier, Marie‐Michèle; Roy, Natasha; ClimHuNor Members (Geoscience Data Journal, 2020)
Abstract Centennial‐to‐millennial temperature records of the past provide a context for the interpretation of current and future changes in climate. Quaternary climates have been relatively well studied in north‐east North America and the adjacent Atlantic Ocean over the last decades, and new research methods have been developed to improve reconstructions. We present newly inferred reconstructions of sea surface temperature for the north‐western Atlantic region, together with a compilation of published temperature records. The database thus comprises a total of 86 records from both marine and terrestrial sites, including lakes, peatlands, ice and tree rings, each covering at least part of the Holocene. For each record, we present details on seasons covered, chronologies and information on radiocarbon dates and analytical time steps. The 86 records contain a total of 154 reconstructions of temperature and temperature‐related variables. Main proxies include pollen and dinocysts, while summer was the season for which the highest number of reconstructions were available. Many records covered most of the Holocene, but many dinocyst records did not extend to the surface, due to sediment mixing, and dendroclimate records were limited to the last millennium. The database allows for the exploration of linkages between sea ice and climate and may be used in conjunction with other palaeoclimate and palaeoenvironmental records, such as wildfire records and peatland dynamics. This inventory may also aid the identification of gaps in the geographic distribution of past temperature records thus guiding future research efforts.
Keywords: Gachon_Philippe

A comparative study of fuzzy logic-based models for groundwater quality evaluation based on irrigation indices - Vadiati, Meysam; Nalley, Deasy; Adamowski, Jan; Nakhaei, Mohammad; Asghari-Moghaddam, Asghar (Journal of Water and Land Development, 2019)
Abstract Groundwater quality modelling plays an important role in water resources management decision making processes. Accordingly, models must be developed to account for the uncertainty inherent in the modelling process, from the sample measurement stage through to the data interpretation stages. Artificial intelligence models, particularly fuzzy inference systems (FIS), have been shown to be effective in groundwater quality evaluation for complex aquifers. In the current study, fuzzy set theory is applied to groundwater-quality related decision-making in an agricultural production context; the Mamdani, Sugeno, and Larsen fuzzy logic-based models (MFL, SFL, and LFL, respectively) are used to develop a series of new, generalized, rule-based fuzzy models for water quality evaluation using widely accepted irrigation indices and hydrological data from the Sarab Plain, Iran. Rather than drawing upon physiochemical groundwater quality parameters, the present research employs widely accepted agricultural indices (e.g., irrigation criteria) when developing the MFL, SFL and LFL groundwater quality models. These newly-developed models, generated significantly more consistent results than the United States Soil Laboratory (USSL) diagram, addressed the inherent uncertainty in threshold data, and were effective in assessing groundwater quality for agricultural uses. The SFL model is recommended as it outperforms both MFL and LFL in terms of accuracy when assessing groundwater quality using irrigation indices.

Groundwater Pollution Sources Apportionment in the Ghaen Plain, Iran - Vesali Naseh, Mohammad; Noori, Roohollah; Berndtsson, Ronny; Adamowski, Jan; Sadatipour, Elaheh (International Journal of Environmental Research and Public Health, 2018)

The Canadian land surface scheme (CLASS): Its history and future - Verseghy, Diana L. (Atmosphere-Ocean, 2000)

Human influence on Canadian temperatures - Wan, Hui; Zhang, Xuebin; Zwiers, Francis W. (Climate Dynamics, 2019)
Canada has experienced some of the most rapid warming on Earth over the past few decades with a warming rate about twice that of the global mean temperature since 1948. Long-term warming is observed in Canada’s annual, winter and summer mean temperatures, and in the annual coldest and hottest daytime and nighttime temperatures. The causes of these changes are assessed by comparing observed changes with climate model simulated responses to anthropogenic and natural (solar and volcanic) external forcings. Most of the observed warming of 1.7°C increase in annual mean temperature during 1948–2012 [90% confidence interval (1.1°, 2.2°C)] can only be explained by external forcing on the climate system, with anthropogenic influence being the dominant factor. It is estimated that anthropogenic forcing has contributed 1.0°C (0.6°, 1.5°C) and natural external forcing has contributed 0.2°C (0.1°, 0.3°C) to the observed warming. Up to 0.5°C of the observed warming trend may be associated with low frequency variability of the climate such as that represented by the Pacific decadal oscillation (PDO) and North Atlantic oscillation (NAO). Overall, the influence of both anthropogenic and natural external forcing is clearly evident in Canada-wide mean and extreme temperatures, and can also be detected regionally over much of the country.

Spatio-temporal variation of rainfall over Bihar State, India - Warwade, Pratibha; Tiwari, Shalini; Ranjan, Sunil; Chandniha, Surendra K.; Adamowski, Jan (Journal of Water and Land Development, 2018)
Abstract This study detected, for the first time, the long term annual and seasonal rainfall trends over Bihar state, India, between 1901 and 2002. The shift change point was identified with the cumulative deviation test (cumulative sum – CUSUM), and linear regression. After the shift change point was detected, the time series was subdivided into two groups: before and after the change point. Arc-Map 10.3 was used to evaluate the spatial distribution of the trends. It was found that annual and monsoon rainfall trends decreased significantly; no significant trends were observed in pre-monsoon, monsoon, post-monsoon and winter rainfall. The average decline in rainfall rate was –2.17 mm·year −1 and –2.13 mm·year −1 for the annual and monsoon periods. The probable change point was 1956. The number of negative extreme events were higher in the later period (1957–2002) than the earlier period (1901–1956).

The Human Cost of Weather Related Disasters - 1995 - 2015 - Wallemacq, Pascaline; Debarati Guha-Sapir; McClean, Denis; CRED; UNISDR (2015)

Delineation of homogeneous regions for regional frequency analysis using statistical depth function - Wazneh, H.; Chebana, F.; Ouarda, T.B.M.J. (Journal of Hydrology, 2015)

Effect of Land Use Change on Soil Carbon Storage over the Last 40 Years in the Shi Yang River Basin, China - Yang, Shurong; Sheng, Danrui; Adamowski, Jan; Gong, Yifan; Zhang, Jian; Cao, Jianjun (Land, 2018)

Human losses due to climate-related disasters: an urgent call for quality control - Enenkel, Markus; Guha-Sapir, Debarati; Zaitchik, Benjamin (Environmental Research Letters, 2024)

Hydrological ensemble forecasting using a multi-model framework - Dion, Patrice; Martel, Jean-Luc; Arsenault, Richard (Journal of Hydrology, 2021)

Climate justice and home-buyout programs: renters as a forgotten population in managed retreat actions - Dundon, Leah A.; Camp, Janey S. (Journal of Environmental Studies and Sciences, 2021)

Analysis of trends in annual streamflow to the Arctic Ocean - Durocher, Martin; Requena, Ana I.; Burn, Donald H.; Pellerin, Jennifer (Hydrological Processes, 2019)
Abstract There is increasing interest in the magnitude of the flow of freshwater to the Arctic Ocean due to its impacts on the biogeophysical and socio‐economic systems in the north and its influence on global climate. This study examines freshwater flow based on a dataset of 72 rivers that either directly or indirectly contribute flow to the Arctic Ocean or reflect the hydrologic regime of areas contributing flow to the Arctic Ocean. Annual streamflow for the 72 rivers is categorized as to the nature and location of the contribution to the Arctic Ocean, and composite series of annual flows are determined for each category for the period 1975 to 2015. A trend analysis is then conducted for the annual discharge series assembled for each category. The results reveal a general increase in freshwater flow to the Arctic Ocean with this increase being more prominent from the Eurasian rivers than from the North American rivers. A comparison with trends obtained from an earlier study ending in 2000 indicates similar trend response from the Eurasian rivers, but dramatic differences from some of the North American rivers. A total annual discharge increase of 8.7 km 3 /y/y is found, with an annual discharge increase of 5.8 km 3 /y/y observed for the rivers directly flowing to the Arctic Ocean. The influence of annual or seasonal climate oscillation indices on annual discharge series is also assessed. Several river categories are found to have significant correlations with the Arctic Oscillation, the North Atlantic Oscillation, or the Pacific Decadal Oscillation. However, no significant association with climate indices is found for the river categories leading to the largest freshwater contribution to the Arctic Ocean.

Snow-atmosphere coupling and its impact on temperature variability and extremes over North America - Diro, G. T.; Sushama, Laxmi; Huziy, O. (Climate Dynamics, 2018)
The impact of snow-atmosphere coupling on climate variability and extremes over North America is investigated using modeling experiments with the fifth generation Canadian Regional Climate Model (CRCM5). To this end, two CRCM5 simulations driven by ERA-Interim reanalysis for the 1981–2010 period are performed, where snow cover and depth are prescribed (uncoupled) in one simulation while they evolve interactively (coupled) during model integration in the second one. Results indicate systematic influence of snow cover and snow depth variability on the inter-annual variability of soil and air temperatures during winter and spring seasons. Inter-annual variability of air temperature is larger in the coupled simulation, with snow cover and depth variability accounting for 40–60% of winter temperature variability over the Mid-west, Northern Great Plains and over the Canadian Prairies. The contribution of snow variability reaches even more than 70% during spring and the regions of high snow-temperature coupling extend north of the boreal forests. The dominant process contributing to the snow-atmosphere coupling is the albedo effect in winter, while the hydrological effect controls the coupling in spring. Snow cover/depth variability at different locations is also found to affect extremes. For instance, variability of cold-spell characteristics is sensitive to snow cover/depth variation over the Mid-west and Northern Great Plains, whereas, warm-spell variability is sensitive to snow variation primarily in regions with climatologically extensive snow cover such as northeast Canada and the Rockies. Furthermore, snow-atmosphere interactions appear to have contributed to enhancing the number of cold spell days during the 2002 spring, which is the coldest recorded during the study period, by over 50%, over western North America. Additional results also provide useful information on the importance of the interactions of snow with large-scale mode of variability in modulating temperature extreme characteristics.

Evaluation of CORDEX-Arctic daily precipitation and temperature-based climate indices over Canadian Arctic land areas - Diaconescu, Emilia Paula; Mailhot, Alain; Brown, Ross; Chaumont, Diane (Climate Dynamics, 2018)
This study focuses on the evaluation of daily precipitation and temperature climate indices and extremes simulated by an ensemble of 12 Regional Climate Model (RCM) simulations from the ARCTIC-CORDEX experiment with surface observations in the Canadian Arctic from the Adjusted Historical Canadian Climate Dataset. Five global reanalyses products (ERA-Interim, JRA55, MERRA, CFSR and GMFD) are also included in the evaluation to assess their potential for RCM evaluation in data sparse regions. The study evaluated the means and annual anomaly distributions of indices over the 1980–2004 dataset overlap period. The results showed that RCM and reanalysis performance varied with the climate variables being evaluated. Most RCMs and reanalyses were able to simulate well climate indices related to mean air temperature and hot extremes over most of the Canadian Arctic, with the exception of the Yukon region where models displayed the largest biases related to topographic effects. Overall performance was generally poor for indices related to cold extremes. Likewise, only a few RCM simulations and reanalyses were able to provide realistic simulations of precipitation extreme indicators. The multi-reanalysis ensemble provided superior results to individual datasets for climate indicators related to mean air temperature and hot extremes, but not for other indicators. These results support the use of reanalyses as reference datasets for the evaluation of RCM mean air temperature and hot extremes over northern Canada, but not for cold extremes and precipitation indices.

Toward an Operational Water Cycle Prediction System for the Great Lakes and St. Lawrence River - Durnford, Dorothy; Fortin, Vincent; Smith, Gregory C.; Archambault, B.; Deacu, Daniel; Dupont, Frédéric; Dyck, Sarah; Martinez, Y.; Klyszejko, Erika; MacKay, M.; Liu, L.; Pellerin, Pierre; et al. (Bulletin of the American Meteorological Society, 2017)
AbstractIn this time of a changing climate, it is important to know whether lake levels will rise, potentially causing flooding, or river flows will dry up during abnormally dry weather. The Great Lakes region is the largest freshwater lake system in the world. Moreover, agriculture, industry, commerce, and shipping are active in this densely populated region. Environment and Climate Change Canada (ECCC) recently implemented the Water Cycle Prediction System (WCPS) over the Great Lakes and St. Lawrence River watershed (WCPS-GLS version 1.0) following a decade of research and development. WCPS, a network of linked models, simulates the complete water cycle, following water as it moves from the atmosphere to the surface, through the river network and into lakes, and back to the atmosphere. Information concerning the water cycle is passed between the models. WCPS is the first short-to-medium-range prediction system of the complete water cycle to be run on an operational basis anywhere. It currently produces ...

The Role of Soil Moisture–Atmosphere Interaction on Future Hot Spells over North America as Simulated by the Canadian Regional Climate Model (CRCM5) - Diro, G. T.; Sushama, Laxmi (Journal of Climate, 2017)
AbstractSoil moisture–atmosphere interactions play a key role in modulating climate variability and extremes. This study investigates how soil moisture–atmosphere coupling may affect future extreme events, particularly the role of projected soil moisture in modulating the frequency and maximum duration of hot spells over North America, using the fifth-generation Canadian Regional Climate Model (CRCM5). With this objective, CRCM5 simulations, driven by two coupled general circulation models (MPI-ESM and CanESM2), are performed with and without soil moisture–atmosphere interactions for current (1981–2010) and future (2071–2100) climates over North America, for representative concentration pathways (RCPs) 4.5 and 8.5. Analysis indicates that, in future climate, the soil moisture–temperature coupling regions, located over the Great Plains in the current climate, will expand farther north, including large parts of central Canada. Results also indicate that soil moisture–atmosphere interactions will play an imp...

Prediction of frost resistance and multiobjective optimisation of low-carbon concrete on the basis of machine learning - Dai, Jinpeng; Zhang, Zhijie; Dong, Xuwei; He, Jie; Yang, Xiaoyuan; Wang, Qicai (Materials Today Communications, 2024)
Keywords: Infolettre; Infolettre_Ete_2024

Designing a green-resilient closed-loop supply chain to preserve business continuity under interrelated disruptions (a case study of the automotive battery industry) - Dehghani Sadrabadi, Mohammad Hossein; Makui, Ahmad; Ghousi, Rouzbeh; Jabbarzadeh, Armin (Computers & Chemical Engineering, 2024)

Integrating Multiple Research Methods to Unravel the Complexity of Human‐Water Systems - Di Baldassarre, Giuliano; Cloke, Hannah; Lindersson, Sara; Mazzoleni, Maurizio; Mondino, Elena; Mård, Johanna; Odongo, Vincent; Raffetti, Elena; Ridolfi, Elena; Rusca, Maria; Savelli, Elisa; Tootoonchi, Faranak (AGU Advances, 2021)
Abstract Predicting floods and droughts is essential to inform the development of policy in water management, climate change adaptation and disaster risk reduction. Yet, hydrological predictions are highly uncertain, while the frequency, severity and spatial distribution of extreme events are further complicated by the increasing impact of human activities on the water cycle. In this commentary, we argue that four main aspects characterizing the complexity of human‐water systems should be explicitly addressed: feedbacks, scales, tradeoffs and inequalities. We propose the integration of multiple research methods as a way to cope with complexity and develop policy‐relevant science. , Plain Language Summary Several governments today claim to be following the science in addressing crises caused by the occurrence of extreme events, such as floods and droughts, or the emergence of global threats, such as climate change and COVID‐19. In this commentary, we show that there are no universal answers to apparently simple questions such as: Do levees reduce flood risk? Do reservoirs alleviate droughts? We argue that the best science we have consists of a plurality of legitimate interpretations and a range of foresights, which can be enriched by integrating multiple disciplines and research methods. , Key Points Accounting for both power relations and cognitive heuristics is key to unravel the interplay of floods, droughts and human societies Flood and drought predictions are complicated by the increasing impact of human activities on the water cycle We propose the integration of multiple research methods as a way to cope with uncertainty and develop policy‐relevant science

A Canadian River Ice Database from National Hydrometric Program Archives - De Rham, Laurent; Dibike, Yonas; Beltaos, Spyros; Peters, Daniel; Bonsal, Barrie; Prowse, Terry (Hydrology and Soil Science – Hydrology, 2020)
Abstract. River ice is a common occurrence in cold climate hydrological systems. The annual cycle of river ice formation, growth, decay and clearance can include low flows and ice jams, as well as mid-winter and spring break-up events. Reports and associated data on river ice occurrence are often limited to site and season-specific studies. Within Canada, the National Hydrometric Program (NHP) operates a network of gauging stations with water level as the primary measured variable to derive discharge. In the late 1990s, the Water Science and Technology Directorate of Environment and Climate Change Canada initiated a long-term effort to compile, archive and extract river ice related information from NHP hydrometric records. This data article describes the original research data set produced by this near 20-year effort: the Canadian River Ice Database (CRID). The CRID holds almost 73,000 variables from a network of 196 NHP stations throughout Canada that were in operation within the period 1894 to 2015. Over 100,000 paper and digital files were reviewed representing 10,378 station-years of active operation. The task of compiling this database involved manual extraction and input of more than 460,000 data entries on water level, discharge, date, time and data quality rating. Guidelines on the data extraction, rating procedure and challenges are provided. At each location, a time series of up to 15 variables specific to the occurrence of freeze-up and winter-low events, mid-winter break-up, ice thickness, spring break-up and maximum open-water level were compiled. This database follows up on several earlier efforts to compile information on river ice, which are summarized herein, and expands the scope and detail for use in Canadian river ice research and applications. Following the Government of Canada Open Data initiative, this original river ice data set is available at: https://doi.org/10.18164/c21e1852-ba8e-44af-bc13-48eeedfcf2f4 (de Rham et al., 2020).

Regional hydrological frequency analysis at ungauged sites with random forest regression - Desai, Shitanshu; Ouarda, Taha B. M. J. (Journal of Hydrology, 2020)
Abstract Flood quantile estimation at sites with little or no data is important for the adequate planning and management of water resources. Regional Hydrological Frequency Analysis (RFA) deals with the estimation of hydrological variables at ungauged sites. Random Forest (RF) is an ensemble learning technique which uses multiple Classification and Regression Trees (CART) for classification, regression, and other tasks. The RF technique is gaining popularity in a number of fields because of its powerful non-linear and non-parametric nature. In the present study, we investigate the use of Random Forest Regression (RFR) in the estimation step of RFA based on a case study represented by data collected from 151 hydrometric stations from the province of Quebec, Canada. RFR is applied to the whole data set and to homogeneous regions of stations delineated by canonical correlation analysis (CCA). Using the Out-of-bag error rate feature of RF, the optimal number of trees for the dataset is calculated. The results of the application of the CCA based RFR model (CCA-RFR) are compared to results obtained with a number of other linear and non-linear RFA models. CCA-RFR leads to the best performance in terms of root mean squared error. The use of CCA to delineate neighborhoods improves considerably the performance of RFR. RFR is found to be simple to apply and more efficient than more complex models such as Artificial Neural Network-based models.

Flow alteration impacts on Hudson Bay river discharge - Déry, Stephen J.; Stadnyk, Tricia A.; MacDonald, Matthew K.; Koenig, Kristina A.; Guay, Catherine (Hydrological Processes, 2018)

Efficient Implementation of Sampling Stochastic Dynamic Programming Algorithm for Multireservoir Management in the Hydropower Sector - Côté, Pascal; Arsenault, Richard (Journal of Water Resources Planning and Management, 2019)

Quantifying the evolution of ensemble water temperature forecasts as a function of weather forecast lead-time: case study on the Nechako River watershed - Charles, Paul; Arsenault, Richard; Martel, Jean-Luc; Gatien, Philippe; St-Hilaire, André (Canadian Water Resources Journal / Revue canadienne des ressources hydriques, 2023)

Correcting Satellite Precipitation Data and Assimilating Satellite-Derived Soil Moisture Data to Generate Ensemble Hydrological Forecasts within the HBV Rainfall-Runoff Model - Ciupak, Maurycy; Ozga-Zielinski, Bogdan; Adamowski, Jan; Deo, Ravinesh C; Kochanek, Krzysztof (Water, 2019)
An implementation of bias correction and data assimilation using the ensemble Kalman filter (EnKF) as a procedure, dynamically coupled with the conceptual rainfall-runoff Hydrologiska Byråns Vattenbalansavdelning (HBV) model, was assessed for the hydrological modeling of seasonal hydrographs. The enhanced HBV model generated ensemble hydrographs and an average stream-flow simulation. The proposed approach was developed to examine the possibility of using data (e.g., precipitation and soil moisture) from the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility for Support to Operational Hydrology and Water Management (H-SAF), and to explore its usefulness in improving model updating and forecasting. Data from the Sola mountain catchment in southern Poland between 1 January 2008 and 31 July 2014 were used to calibrate the HBV model, while data from 1 August 2014 to 30 April 2015 were used for validation. A bias correction algorithm for a distribution-derived transformation method was developed by exploring generalized exponential (GE) theoretical distributions, along with gamma (GA) and Weibull (WE) distributions for the different data used in this study. When using the ensemble Kalman filter, the stochastically-generated ensemble of the model states generally induced bias in the estimation of non-linear hydrologic processes, thus influencing the accuracy of the Kalman analysis. In order to reduce the bias produced by the assimilation procedure, a post-processing bias correction (BC) procedure was coupled with the ensemble Kalman filter (EnKF), resulting in an ensemble Kalman filter with bias correction (EnKF-BC). The EnKF-BC, dynamically coupled with the HBV model for the assimilation of the satellite soil moisture observations, improved the accuracy of the simulated hydrographs significantly in the summer season, whereas, a positive effect from bias corrected (BC) satellite precipitation, as forcing data, was observed in the winter. Ensemble forecasts generated from the assimilation procedure are shown to be less uncertain. In future studies, the EnKF-BC algorithm proposed in the current study could be applied to a diverse array of practical forecasting problems (e.g., an operational assimilation of snowpack and snow water equivalent in forecasting models).

Inconsistent linear Trends in Senegalese rainfall data indices from 1950 to 2007. - Comby, Jacques; Sarr, Mamadou (Hydrological Sciences Journal, 2014)

Future change in amplitude and timing of high-flow events in a Canadian subarctic watershed - Champagne, Olivier; Arain, Altaf; Wang, Shusen; Leduc, Martin (Cold Regions Science and Technology, 2023)
The Hudson Bay basin is a large contributor of freshwater input in the Arctic Ocean and is also an area affected by destructive spring floods. In this study, the hydrological model MESH (Modelisation Environmentale Communautaire - Surface and hydrology) was set up for the Groundhog River watershed situated in the Hudson Bay basin, to simulate the future evolution of streamflow and annual maximum streamflow. MESH was forced by meteorological data from ERA5 reanalyses in the historical period (1979–2018) and 12 models of the Coupled model intercomparison Project Phase 5 (CMIP5) downscaled with the Canadian Regional Climate model version 5 (CRCM5) in historical (1979–2005) and scenario period (2006–2098). The projections consistently indicate an earlier spring flow and a reduction in the amount of annual maximum streamflow by the end of the 21st century. Under the RCP8.5 scenario, the annual maximum streamflow occurring in the spring is expected to be advanced by 2 weeks and reduced on average from 852 m3/s (±265) in the historical period (1979–2018) to 717m3/s (±250) by the end of the 21st century (2059–2098). Because the seasonal projection of streamflow was not investigated in previous studies, this work is an important first step to assess the seasonal change of streamflow in the Hudson Bay region under climate change.

Interdecadal variability of streamflow in the Hudson Bay Lowlands watersheds driven by atmospheric circulation - Champagne, Olivier; Arain, M. Altaf; Wang, Shusen; Leduc, Martin; Russell, Hazen A. J. (Journal of Hydrology: Regional Studies, 2021)
Study region Hudson Bay Lowlands watersheds, Ontario, Canada. Study Focus The rivers in the Hudson Bay Lowlands are a major source of freshwater entering the Arctic Ocean and they also cause major floods. In recent decades, this region has been affected by major changes in hydroclimatic processes attributed to climate change and natural climate variability. In this study, we used ERA5 reanalysis data, hydrometric observations, and the hydrological model MESH, to investigate the impact of atmospheric circulation on the inter-decadal variability of streamflow between 1979 and 2018 in the Hudson Bay Lowlands. The natural climate variability was assessed using a weather regimes approach based on the discretization of daily geopotential height anomalies (Z500) from ERA5 reanalysis, as well as large scale oceanic and atmospheric variability modes. New hydrological insights The results showed an anomalous convergence of atmospheric moisture flux between 1995–2008 that enhanced precipitation and increased streamflow in the western part of the region. This moisture convergence was likely driven by the combination of (i) low pressure anomalies in the East Coast of North America and (ii) low pressure anomalies in western regions of Canada, associated with the cold phase of the pacific decadal oscillation (PDO). Since 2009, streamflow remains high, likely due to more groundwater discharge associated with the degradation of permafrost.

Future shift in winter streamflow modulated by the internal variability of climate in southern Ontario - Champagne, Olivier; Arain, M. Altaf; Leduc, Martin; Coulibaly, Paulin; McKenzie, Shawn (Hydrology and Earth System Sciences, 2020)
Fluvial systems in southern Ontario are regularly affected by widespread early-spring flood events primarily caused by rain-on-snow events. Recent studies have shown an increase in winter floods in this region due to increasing winter temperature and precipitation. Streamflow simulations are associated with uncertainties mainly due to the different scenarios of greenhouse gas emissions, global climate models (GCMs) or the choice of the hydrological model. The internal variability of climate, defined as the chaotic variability of atmospheric circulation due to natural internal processes within the climate system, is also a source of uncertainties to consider. Uncertainties of internal variability can be assessed using hydrological models fed by downscaled data of a global climate model large ensemble (GCM-LE), but GCM outputs have too coarse of a scale to be used in hydrological modeling. The Canadian Regional Climate Model Large Ensemble (CRCM5-LE), a 50-member ensemble downscaled from the Canadian Earth System Model version 2 Large Ensemble (CanESM2-LE), was developed to simulate local climate variability over northeastern North America under different future climate scenarios. In this study, CRCM5-LE temperature and precipitation projections under an RCP8.5 scenario were used as input in the Precipitation Runoff Modeling System (PRMS) to simulate streamflow at a near-future horizon (2026–2055) for four watersheds in southern Ontario. To investigate the role of the internal variability of climate in the modulation of streamflow, the 50 members were first grouped in classes of similar projected change in January–February streamflow and temperature and precipitation between 1961–1990 and 2026–2055. Then, the regional change in geopotential height (Z500) from CanESM2-LE was calculated for each class. Model simulations showed an average January–February increase in streamflow of 18 % (±8.7) in Big Creek, 30.5 % (±10.8) in Grand River, 29.8 % (±10.4) in Thames River and 31.2 % (±13.3) in Credit River. A total of 14 % of all ensemble members projected positive Z500 anomalies in North America's eastern coast enhancing rain, snowmelt and streamflow volume in January–February. For these members the increase of streamflow is expected to be as high as 31.6 % (±8.1) in Big Creek, 48.3 % (±11.1) in Grand River, 47 % (±9.6) in Thames River and 53.7 % (±15) in Credit River. Conversely, 14 % of the ensemble projected negative Z500 anomalies in North America's eastern coast and were associated with a much lower increase in streamflow: 8.3 % (±7.8) in Big Creek, 18.8 % (±5.8) in Grand River, 17.8 % (±6.4) in Thames River and 18.6 % (±6.5) in Credit River. These results provide important information to researchers, managers, policymakers and society about the expected ranges of increase in winter streamflow in a highly populated region of Canada, and they will help to explain how the internal variability of climate is expected to modulate the future streamflow in this region.

Using a Particle Filter to Estimate the Spatial Distribution of the Snowpack Water Equivalent - Cantet, Philippe; Boucher, Marie-Amélie; Lachance-Coutier, S.; Turcotte, Richard; Fortin, Vincent (Journal of Hydrometeorology, 2019)
AbstractA snow model forced by temperature and precipitation is used to simulate the spatial distribution of snow water equivalent (SWE) over a 600,000 km2 portion of the province of Quebec, Canada. We propose to improve model simulations by assimilating SWE data from sporadic manual snow surveys with a particle filter. A temporally and spatially correlated perturbation of the meteorological forcing is used to generate the set of particles. The magnitude of the perturbations is fixed objectively. First, the particle filter and direct insertion were both applied on 88 sites for which measured SWE consist of more or less five values per year over a period of 17 years. The temporal correlation of perturbations enables to improve the accuracy and the ensemble dispersion of the particle filter, while the spatial correlation lead to a spatial coherence in the particle weights. The spatial estimates of SWE obtained with the particle filter are compared with those obtained through optimal interpolation of the sno...

Influences of afforestation policies on soil moisture content in China’s arid and semi-arid regions - Cao, Jianjun; Tian, Hong; Adamowski, Jan F.; Zhang, Xiaofang; Cao, Zijian (Land Use Policy, 2018)

Multi-household grazing management pattern maintains better soil fertility - Cao, Jianjun; Xu, Xueyun; Deo, Ravinesh C.; Holden, Nicholas M.; Adamowski, Jan F.; Gong, Yifan; Feng, Qi; Yang, Shurong; Li, Mengtian; Zhou, Junju; Zhang, Jian; Liu, Minxia (Agronomy for Sustainable Development, 2018)

The Canadian Land Data Assimilation System (CaLDAS): Description and Synthetic Evaluation Study - Carrera, Marco L.; Bélair, Stéphane; Bilodeau, Bernard (Journal of Hydrometeorology, 2015)
AbstractThe Canadian Land Data Assimilation System (CaLDAS) has been developed at the Meteorological Research Division of Environment Canada (EC) to better represent the land surface initial states in environmental prediction and assimilation systems. CaLDAS is built around an external land surface modeling system and uses the ensemble Kalman filter (EnKF) methodology. A unique feature of CaLDAS is the use of improved precipitation forcing through the assimilation of precipitation observations. An ensemble of precipitation analyses is generated by combining numerical weather prediction (NWP) model precipitation forecasts with precipitation observations. Spatial phasing errors to the NWP first-guess precipitation forecasts are more effective than perturbations to the precipitation observations in decreasing (increasing) the exceedance ratio (uncertainty ratio) scores and generating flatter, more reliable ranked histograms. CaLDAS has been configured to assimilate L-band microwave brightness temperature TB ...

Empowering marginalized communities in water resources management: Addressing inequitable practices in Participatory Model Building - Butler, Cameron; Adamowski, Jan (2015)

The Roles of Climate Risk Dynamics and Adaptation Limits in Adaptation Assessment - Bouwer, Laurens M. (Springer climate, 2022)
Abstract The performance of adaptation measures depends on their robustness against various possible futures, with varying climate change impacts. Such impacts are driven by both climatic as well as non-climatic drivers. Risk dynamics are then important, as the avoided risk will determine the benefits of adaptation actions. It is argued that the integration of information on changing exposure and vulnerability is needed to make projections of future climate risk more realistic. In addition, many impact and vulnerability studies have used a top-down rather a technical approach. Whether adaptation action is feasible is determined by technical and physical possibilities on the ground, as well as local capacities, governance and preference. These determine the hard and soft limits of adaptation. Therefore, it is argued that the risk metrics outputs alone are not sufficient to predict adaptation outcomes, or predict where adaptation is feasible or not; they must be placed in the local context. Several of the current climate risk products would fall short of their promise to inform adaptation decision-making on the ground. Some steps are proposed to improve adaptation modelling in order to better incorporate these aspects.

Streamflow variability over the 1881–2011 period in northern Québec: comparison of hydrological reconstructions based on tree rings and geopotential height field reanalysis - Brigode, Pierre; Brissette, François; Nicault, Antoine; Perreault, Luc; Kuentz, Anna; Mathevet, Thibault; Gailhard, Joël (Climate of The Past, 2016)
Over the last decades, different methods have been used by hydrologists to extend observed hydro-climatic time series, based on other data sources, such as tree rings or sedimentological datasets. For example, tree ring multi-proxies have been studied for the Caniapiscau Reservoir in northern Quebec (Canada), leading to the reconstruction of flow time series for the last 150 years. In this paper, we applied a new hydro-climatic reconstruction method on the Caniapiscau Reservoir and compare the obtained streamflow time series against time series derived from dendrohydrology by other authors on the same catchment and study the natural streamflow variability over the 1881–2011 period in that region. This new reconstruction is based not on natural proxies but on a historical reanalysis of global geopotential height fields, and aims firstly to produce daily climatic time series, which are then used as inputs to a rainfall–runoff model in order to obtain daily streamflow time series. The performances of the hydro-climatic reconstruction were quantified over the observed period, and showed good performances, in terms of both monthly regimes and interannual variability. The streamflow reconstructions were then compared to two different reconstructions performed on the same catchment by using tree ring data series, one being focused on mean annual flows and the other on spring floods. In terms of mean annual flows, the interannual variability in the reconstructed flows was similar (except for the 1930–1940 decade), with noteworthy changes seen in wetter and drier years. For spring floods, the reconstructed interannual variabilities were quite similar for the 1955–2011 period, but strongly different between 1880 and 1940. The results emphasize the need to apply different reconstruction methods on the same catchments. Indeed, comparisons such as those above highlight potential differences between available reconstructions and, finally, allow a retrospective analysis of the proposed reconstructions of past hydro-climatological variabilities.

The quantification of water storage capacity of peatlands across different hydroclimatic settings using a simple rainfall event to water-table response ratio method - Bourgault, Marc-André; Bechtold, Michel; Holden, Joseph; Blundell, Antony; Dettman, Ullrich; Garneau, Michelle; Howson, Tim; Jutras, Sylvain; Kløve, Bjørn; Larocque, Marie; Marttila, Hannu; McKendrick-Smith, Kathryn; et al. (2021)
In wetlands, the water budget is traditionally quantified by measuring the hydrologic components including precipitation, evapotranspiration and surface water-groundwater inflows and outflows. However, the reliability of measurements is often questioned due to the difficulty of rigorously monitoring all components of the water budget. Quantifying the rainfall event to water table response ratio is an alternative approach with minimal need for data commonly collected in peatland studies. However, the method has been used only in a limited number of biophysical settings including different microforms, hydroclimatic and hydrogeological settings. The objectives of this study are to quantify the reactivity of the water table to precipitation for different pristine peatlands located in different hydroclimatic conditions and to provide quantitative assessments of water storage of as many peatlands as possible. To do so, site-specific hourly water table and precipitation measurements was collected from northern peatlands worldwide. In total, data from more than 30 sites were retrieved from 8 research groups. For all peatlands, water-table depths varied between 80 cm below the peat surface and 10 cm above the peat surface. The results highlight that the hydrology of all peatlands is characterized by a shift from an environment that can store water to an environment that contributes to rapid outflow, and this is a uniform feature across sites. However, for peatlands with the lowest water storage capacities, this shift occurs during relatively moderate rainfall events (40 mm) or successive small rainfall events. Blanket peat bog best embodied this type of hydrological response. For peatlands with the highest water storage capacity, this shift occurs following multiple moderate to large precipitation events (40 mm – 80 mm) and it is strongly enhanced by the shift from high to low evaporative periods. The peatlands with the highest storage capacity are raised bogs with deep water-table. These conditions are best observed in peatlands located in geographical settings with high evaporation rates. Among all the peatlands, maximum water storage capacity for given rainfall events was equal to ≈150 mm. These analyses also confirm that the water table rise caused by precipitation events contain sufficient information to constrain water storage variations around monitored wells peatlands for a wide array of biophysical settings.

How do hydrogeological setting and meteorological conditions influence water table depth and fluctuations in ombrotrophic peatlands? - Bourgault, Marc-André; Larocque, Marie; Garneau, Michelle (Journal of Hydrology X, 2019)

Relationship between water quality and macro-scale parameters (land use, erosion, geology, and population density) in the Siminehrood River Basin - Bostanmaneshrad, Farshid; Partani, Sadegh; Noori, Roohollah; Nachtnebel, Hans-Peter; Berndtsson, Ronny; Adamowski, Jan Franklin (Science of The Total Environment, 2018)

Three‐dimensional turbulent structures at a medium‐sized confluence with and without an ice cover - Biron, Pascale M.; Buffin‐Bélanger, Thomas; Martel, Nancy (Earth Surface Processes and Landforms, 2019)
Abstract River confluences are characterized by a complex mixing zone with three‐dimensional (3D) turbulent structures which have been described as both streamwise‐oriented structures and Kelvin–Helmholtz (KH) vertical‐oriented structures. The latter are visible where there is a turbidity difference between the two tributaries, whereas the former are usually derived from mean velocity measurements or numerical simulations. Few field studies recorded turbulent velocity fluctuations at high frequency to investigate these structures, particularly at medium‐sized confluences where logistical constraints make it difficult to use devices such as acoustic doppler velocimeter (ADV). This study uses the ice cover present at the confluence of the Mitis and Neigette Rivers in Quebec (Canada) to obtain long‐duration, fixed measurements along the mixing zone. The confluence is also characterized by a marked turbidity difference which allows to investigate the mixing zone dynamics from drone imagery during ice‐free conditions. The aim of the study is to characterize and compare the flow structure in the mixing zone at a medium‐sized (~40 m) river confluence with and without an ice cover. Detailed 3D turbulent velocity measurements were taken under the ice along the mixing plane with an ADV through eight holes at around 20 positions on the vertical. For ice‐free conditions, drone imagery results indicate that large (KH) coherent structures are present, occupying up to 50% of the width of the parent channel. During winter, the ice cover affects velocity profiles by moving the highest velocities towards the centre of the profiles. Large turbulent structures are visible in both the streamwise and lateral velocity components. The strong correlation between these velocity components indicates that KH vortices are the dominating coherent structures in the mixing zone. A spatio‐temporal conceptual model is presented to illustrate the main differences on the 3D flow structure at the river confluence with and without the ice cover. © 2019 John Wiley & Sons, Ltd.

Control mechanisms of photosynthetic epibionts on zooplankton: an experimental approach - Bertolo, Andrea; Rodríguez, Marco A.; Lacroix, Gérard (Ecosphere, 2015)
Several top‐down and bottom‐up forces have been put forward to explain variable infestation rates of zooplankton by epibionts. Among top‐down forces, fish predation affects epibiont prevalence on zooplanktonic organisms, either by eliminating more conspicuous, heavily burdened individuals, or by reducing population size of zooplankton hosts, with consequences for substrate availability for epibionts. However, detailed experimental‐based information on the effects of top‐down forces is still lacking. Among bottom‐up forces, light can potentially control populations of photosynthetic epibionts. Therefore, both changes in light penetration in the water column and the vertical position of hosts in the water column could affect the photic conditions in which epibionts live and could thus control their population growth. We tested experimentally the hypothesis that both light limitation and fish predation affect epibiont burden on zooplankton. Moreover, we also tested the hypothesis that zooplanktivorous fish affect the prevalence and burden of the epibiotic alga Colacium sp. (Euglenida) on zooplankton not only by direct predation, but also by affecting the vertical distribution of zooplankton. We analyzed Colacium burden on two zooplankton genera that responded differently to the presence of zooplanktivorous fish by altering their daytime vertical distributions, thus exposing photosynthetic epibionts to different light conditions. Colacium burden on the two zooplankton genera was also compared between enclosures with different degrees of light limitation. Our results suggest that (1) ambient light limitation has the potential to reduce the burden of photosynthetic epibionts on zooplankton in natural conditions, and (2) zooplankton behavior (e.g., daytime refuge use to escape fish predation) can reduce the burden by exposing photosynthetic epibionts to suboptimal light conditions.

Mechanisms of Co enrichment in the Zhubu Ni–Co–PGE deposit in the Emeishan LIP, SW China: Constraints from mineral geochemistry and Fe–S isotopes of sulfides - Bao, Yawen; Zhang, Mingjie; Zhang, Hongfu; Feng, Yantong; Li, Xiaofei; He, Jie (Ore Geology Reviews, 2024)
Keywords: Infolettre; Infolettre_Octobre_2024

Impact hydrologique des épisodes de pluie hivernale sur un couvert de neige - Beaudoin, Geneviève (Université Laval, 2022)

Short-term water quality variable prediction using a hybrid CNN–LSTM deep learning model - Barzegar, Rahim; Aalami, Mohammad Taghi; Adamowski, Jan (Stochastic Environmental Research and Risk Assessment, 2020)

Exploring the hydrogeochemical evolution of cold and thermal waters in the Sarein-Nir area, Iran using stable isotopes (δ18O and δD), geothermometry and multivariate statistical approaches - Barzegar, Rahim; Asghari Moghaddam, Asghar; Tziritis, Evangelos; Adamowski, Jan; Bou Nassar, Jessica; Noori, Mohammad; Aalami, Mohammad Taghi; Kazemian, Naeimeh (Geothermics, 2020)

Streamwater ages in nested, seasonally cold Canadian watersheds - Bansah, Samuel; Ali, Genevieve (Hydrological Processes, 2019)
Abstract The mean transit time (MTT) is an important descriptor of water storage and release dynamics in watersheds. Although MTT studies are numerous for many regions around the world, they are rare for prairie watersheds where seasonally cold or dry conditions require adequate methodological choices towards MTT estimation, especially regarding the handling of sparse data records and tracer selection. To examine the impact of such choices, we used timeseries of δ 18 O and δ 2 H from two contrasted years (2014 and 2015) and relied on two metrics and two modelling methods to infer MTTs in prairie watersheds. Our focus was on nested outlets with different drainage areas, geologies, and known run‐off generation mechanisms. The damping ratio and young water fraction (i.e., the fraction of streamflow with transit times lesser than 3 months) metrics, as well as the sine‐wave modelling and time‐based convolution modelling methods, were applied to year‐specific data. Results show that young water fractions and modelled MTT values were, respectively, larger and smaller in 2014, which was a wet year, compared with that in 2015. In 2014, most outlets had young water fractions larger than 0.5 and MTT values lesser than 6 months. The damping ratio, young water fraction, and sine‐wave modelling methods led to convergent conclusions about watershed water storage and release dynamics for some of the monitored sites. Contrasting results were, however, obtained when the same method was applied using δ 2 H instead of δ 18 O, due to differing evaporation fractionation, or when the time‐based convolution modelling method was used. Some methods also failed to provide any robust results during the dry year (i.e., 2015), highlighting the difficulty in inferring MTTs when data are sparse due to intermittent streamflow. This study therefore allowed the formulation of empirical recommendations for MTT estimation in prairie environments as a function of data availability and antecedent wetness conditions.

Delimitation of groundwater zones under contamination risk using a bagged ensemble of optimized DRASTIC frameworks - Barzegar, Rahim; Asghari Moghaddam, Asghar; Adamowski, Jan; Nazemi, Amir Hossein (Environmental Science and Pollution Research, 2019)

Multi-step water quality forecasting using a boosting ensemble multi-wavelet extreme learning machine model - Barzegar, Rahim; Asghari Moghaddam, Asghar; Adamowski, Jan; Ozga-Zielinski, Bogdan (Stochastic Environmental Research and Risk Assessment, 2018)

Evidence for the occurrence of hydrogeochemical processes in the groundwater of Khoy plain, northwestern Iran, using ionic ratios and geochemical modeling - Barzegar, Rahim; Asghari Moghaddam, Asghar; Nazemi, Amir Hossein; Adamowski, Jan (Environmental Earth Sciences, 2018)

Science of Lakes - Multidisciplinary Approach - Summers, J. Kevin; Assani, A. Ali (Environmental Sciences, 2024)
Keywords: Site_internet_RIISQ

Assessment of 30 gridded precipitation datasets over different climates on a country scale - Araghi, Alireza; Adamowski, Jan F. (Earth Science Informatics, 2024)

A Hybrid Multi-Model Approach for Hydrological Ensemble Forecasting: The Added Value of Deep Learning Models - Armstrong, William; Arsenault, Richard; Martel, Jean-Luc; Troin, Magali; Dion, Patrice; Sabzipour, Behmard; Brissette, François; Mai, Juliane (2024)

The PAVICS-Hydro platform: A virtual laboratory for hydroclimatic modelling and forecasting over North America - Arsenault, Richard; Huard, David; Martel, Jean-Luc; Troin, Magali; Mai, Juliane; Brissette, François; Jauvin, Christian; Vu, Long; Craig, James R.; Smith, Trevor J.; Logan, Travis; Tolson, Bryan A.; et al. (Environmental Modelling & Software, 2023)

Comparison of wavelet-based hybrid models for the estimation of daily reference evapotranspiration in different climates - Araghi, Alireza; Adamowski, Jan; Martinez, Christopher J. (Journal of Water and Climate Change, 2020)
Abstract Reference evapotranspiration (ETo) is one of the most important factors in the hydrologic cycle and water balance studies. In this study, the performance of three simple and three wavelet hybrid models were compared to estimate ETo in three different climates in Iran, based on different combinations of input variables. It was found that the wavelet-artificial neural network was the best model, and multiple linear regression (MLR) was the worst model in most cases, although the performance of the models was related to the climate and the input variables used for modeling. Overall, it was found that all models had good accuracy in terms of estimating daily ETo. Also, it was found in this study that large numbers of decomposition levels via the wavelet transform had noticeable negative effects on the performance of the wavelet-based models, especially for the wavelet-adaptive network-based fuzzy inference system and wavelet-MLR, but in contrast, the type of db wavelet function did not have a detectable effect on the performance of the wavelet-based models.

Streamflow prediction in ungauged basins: analysis of regionalization methods in a hydrologically heterogeneous region of Mexico - Arsenault, Richard; Breton-Dufour, Mélissa; Poulin, Annie; Dallaire, Gabrielle; Romero-Lopez, Rabindranarth (Hydrological Sciences Journal, 2019)

Continuous streamflow prediction in ungauged basins: The effects of equifinality and parameter set selection on uncertainty in regionalization approaches - Arsenault, Richard; Brissette, François P. (Water Resources Research, 2014)
Abstract This paper focuses on evaluating the uncertainty of three common regionalization methods for predicting continuous streamflow in ungauged basins. A set of 268 basins covering 1.6 million km 2 in the province of Quebec was used to test the regionalization strategies. The multiple linear regression, spatial proximity, and physical similarity approaches were evaluated on the catchments using a leave‐one‐out cross‐validation scheme. The lumped conceptual HSAMI hydrological model was used throughout the study. A bootstrapping method was chosen to further estimate uncertainty due to parameter set selection for each of the parameter set/regionalization method pairs. Results show that parameter set selection can play an important role in regionalization method performance depending on the regionalization methods (and their variants) used and that equifinality does not contribute significantly to the overall uncertainty witnessed throughout the regionalization methods applications. Regression methods fail to consistently assign behavioral parameter sets to the pseudoungauged basins (i.e., the ones left out). Spatial proximity and physical similarity score better, the latter being the best. It is also shown that combining either physical similarity or spatial proximity with the multiple linear regression method can lead to an even more successful prediction rate. However, even the best methods were shown to be unreliable to an extent, as successful prediction rates never surpass 75%. Finally, this paper shows that the selection of catchment descriptors is crucial to the regionalization strategies' performance and that for the HSAMI model, the optimal number of donor catchments for transferred parameter sets lies between four and seven. , Key Points Uncertainty can be limited in regionalization Physical similarity method is best, followed by spatial proximity Regression‐augmented methods can yield better performance

Hydrologie: cheminements de l'eau - Anctil, François; Rousselle, Jean; Lauzon, Nicolas (Presses internationales Polytechnique, 2012)
La quatrième de couverture indique : "L'hydrologie est la science qui étudie les eaux terrestres, leur origine, leur mouvement et leur répartition sur notre planète, leurs propriétés physiques et chimiques, leurs interactions avec l'environnement physique et biologique, et leur influence sur les activités humaines. Au sens plus strict, c'est la science qui étudie le cycle de l'eau dans la nature. Elle examine la distribution géographique et temporelle de l'eau dans l'atmosphère, en surface et dans le sol et le-sous-sol. Hydrologie - Cheminements de l'eau, deuxième édition, permet à l'hydrologue moderne d'explorer les volets scientifique et technique de l'hydrologie. Une description scientifique des phénomènes hydrologiques est offerte afin de proposer une motivation à leur étude, d'identifier les observations requises et d'assurer une compréhension de chaque étape du cycle de l'eau. Les éléments de chacune des situations d'apprentissage sont intégrés dans des modèles théoriques et d'application, et de nombreuses méthodes et techniques pour la résolution de problèmes hydrologiques sont présentées. En plus de fournir une description universelle de l'hydrologie, il couvre de multiples sujets dont l'estimation statistique des débits, l'exploitation des eaux, les systèmes d'information géographique et la télédétection. Il comporte, en outre, de nombreuses figures qui permettent d'en illustrer le propos, une bibliographie substantielle et quelque cent cinquante exercices. Ce livre s'adresse particulièrement aux étudiants de premier cycle universitaire en génie civil, forestier ou agricole, ainsi qu'à ceux de géographie physique, de géologie ou des sciences de l'environnement, mais aussi aux ingénieurs-conseils, au personnel des agences gouvernementales confronté à différents aspects de l'hydrologie et aux professeurs."

Field observations of stratification in stormwater wet ponds - Ahmed, Sherif S.; Loewen, Mark R.; Zhang, Wenming; Ghobrial, Tadros R.; Zhu, David Z.; Mahmood, Khizar; Van Duin, Bert (Journal of Environmental Management, 2022)

Photooxidation of arsenic in pristine and mine-impacted Canadian subarctic freshwater systems - Amyot, Marc; Bélanger, Dominic; Simon, Dana F.; Chételat, John; Palmer, Mike; Ariya, Parisa (Journal of Hazardous Materials Advances, 2021)

A century of observations reveals increasing likelihood of continental-scale compound dry-hot extremes - Alizadeh, Mohammad Reza; Adamowski, Jan; Nikoo, Mohammad Reza; AghaKouchak, Amir; Dennison, Philip; Sadegh, Mojtaba (Science Advances, 2020)
Compound dry-hot events enlarge homogenously due to teleconnected land-atmosphere feedbacks. , Using over a century of ground-based observations over the contiguous United States, we show that the frequency of compound dry and hot extremes has increased substantially in the past decades, with an alarming increase in very rare dry-hot extremes. Our results indicate that the area affected by concurrent extremes has also increased significantly. Further, we explore homogeneity (i.e., connectedness) of dry-hot extremes across space. We show that dry-hot extremes have homogeneously enlarged over the past 122 years, pointing to spatial propagation of extreme dryness and heat and increased probability of continental-scale compound extremes. Last, we show an interesting shift between the main driver of dry-hot extremes over time. While meteorological drought was the main driver of dry-hot events in the 1930s, the observed warming trend has become the dominant driver in recent decades. Our results provide a deeper understanding of spatiotemporal variation of compound dry-hot extremes.

Investigating monthly precipitation variability using a multiscale approach based on ensemble empirical mode decomposition - Alizadeh, Farhad; Roushangar, Kiyoumar; Adamowski, Jan (Paddy and Water Environment, 2019)

Analysis of deterministic and geostatistical interpolation techniques for mapping meteorological variables at large watershed scales - Amini, Mohammad Amin; Torkan, Ghazale; Eslamian, Saeid; Zareian, Mohammad Javad; Adamowski, Jan Franklin (Acta Geophysica, 2019)

Correction to: Analysis of deterministic and geostatistical interpolation techniques for mapping meteorological variables at large watershed scales - Amini, Mohammad Amin; Torkan, Ghazale; Eslamian, Saeid; Zareian, Mohammad Javad; Adamowski, Jan Franklin (Acta Geophysica, 2019)

Warm Season Evaluation of Soil Moisture Prediction in the Soil, Vegetation, and Snow (SVS) Scheme - Alavi, Nasim; Bélair, Stéphane; Fortin, Vincent; Zhang, Shunli; Husain, Syed Zahid; Carrera, Marco L.; Abrahamowicz, Maria (Journal of Hydrometeorology, 2016)
AbstractA new land surface scheme has been developed at Environment and Climate Change Canada (ECCC) to provide surface fluxes of momentum, heat, and moisture for the Global Environmental Multiscale (GEM) atmospheric model. In this study, the performance of the Soil, Vegetation, and Snow (SVS) scheme in estimating the surface and root-zone soil moisture is evaluated against the Interactions between Soil, Biosphere, and Atmosphere (ISBA) scheme currently used operationally at ECCC within GEM for numerical weather prediction. In addition, the sensitivity of SVS soil moisture results to soil texture and vegetation data sources (type and fractional coverage) has been explored. The performance of SVS and ISBA was assessed against a large set of in situ observations as well as the brightness temperature data from the Soil Moisture Ocean Salinity (SMOS) satellite over North America. The results indicate that SVS estimates the time evolution of soil moisture more accurately, and compared to ISBA, results in highe...

Influence of instrumentation on long temperature time series - Acquaotta, Fiorella; Fratianni, Simona; Aguilar, Enric; Fortin, Guillaume (Climatic Change, 2019)
In time series of essential climatological variables, many discontinuities are created not by climate factors but changes in the measuring system, including relocations, changes in instrumentation, exposure or even observation practices. Some of these changes occur due to reorganization, cost-efficiency or innovation. In the last few decades, station movements have often been accompanied by the introduction of an automatic weather station (AWS). Our study identifies the biases in daily maximum and minimum temperatures using parallel records of manual and automated observations. They are selected to minimize the differences in surrounding environment, exposition, distance and difference in elevation. Therefore, the type of instrumentation is the most important biasing factor between both measurements. The pairs of weather stations are located in Piedmont, a region of Italy, and in Gaspe Peninsula, a region of Canada. They have 6years of overlapping period on average, and 5110 daily values. The approach implemented for the comparison is divided in four main parts: a statistical characterization of the daily temperature series; a comparison between the daily series; a comparison between the types of events, heat wave, cold wave and normal events; and a verification of the homogeneity of the difference series. Our results show a higher frequency of warm (+10%) and extremely warm (+35%) days in the automated system, compared with the parallel manual record. Consequently, the use of a composite record could significantly bias the calculation of extreme events.

Probabilistic Event Based Rainfall-Runoff Modeling Using Copula Functions - Abdollahi, Sajjad; Akhoond-Ali, Ali Mohammad; Mirabbasi, Rasoul; Adamowski, Jan Franklin (Water Resources Management, 2019)

A Mutual Catastrophe Insurance Framework for Horizontal Collaboration in Prepositioning Strategic Reserves - Zbib, Hani; Balcik, Burcu; Rancourt, Marie-Ève; Laporte, Gilbert (Operations Research, 2024)
Improving Disaster Preparedness Through Mutual Catastrophe Insurance In “A Mutual Catastrophe Insurance Framework for Horizontal Collaboration in Prepositioning Strategic Reserves,” H. Zbib, B. Balcik, M.-È. Rancourt, and G. Laporte present an innovative approach to collaborative disaster preparedness. The novel framework considers a risk-averse mutual insurer offering multiyear insurance contracts with coverage deductibles and limits to a portfolio of risk-averse policyholders. It is designed to foster horizontal collaboration among policyholders for joint disaster preparedness by effectively integrating operational and financial functions. The problem is modeled as a large-scale nonlinear multistage stochastic program and solved by using an effective Benders decomposition algorithm. The framework is validated with real data from 18 Caribbean countries focusing on hurricane preparedness. Given the predicted impacts of climate change, the proposed multiyear mutual catastrophe insurance framework promises to reshape global disaster preparedness and make a profound societal impact by providing a transparent disaster financing plan to protect vulnerable regions. The study’s findings stress the importance of long-term cooperation, prenegotiation of indemnification policies, and strategic setting of deductibles and limits by taking into account the correlation between policyholders. , We develop a mutual catastrophe insurance framework for the prepositioning of strategic reserves to foster horizontal collaboration in preparedness against low-probability high-impact natural disasters. The framework consists of a risk-averse insurer pooling the risks of a portfolio of risk-averse policyholders. It encompasses the operational functions of planning the prepositioning network in preparedness for incoming insurance claims, in the form of units of strategic reserves, setting coverage deductibles and limits of policyholders, and providing insurance coverage to the claims in the emergency response phase. It also encompasses the financial functions of ensuring the insurer’s solvency by efficiently managing its capital and allocating yearly premiums among policyholders. We model the framework as a very large-scale nonlinear multistage stochastic program, and solve it through a Benders decomposition algorithm. We study the case of Caribbean countries establishing a horizontal collaboration for hurricane preparedness. Our results show that the collaboration is more effective when established over a longer planning horizon, and is more beneficial when outsourcing becomes expensive. Moreover, the correlation of policyholders affected simultaneously under the extreme realizations and the position of their claims in their global claims distribution directly affects which policyholders get deductibles and limits. This underlines the importance of prenegotiating policyholders’ indemnification policies at the onset of collaboration. Funding: G. Laporte and M.-È. Rancourt were funded by the Canadian Natural Sciences and Engineering Research Council (NSERC) [Grants 2015-06189 and 2022-04846]. Funding was also provided by the Institute for Data Valorisation (IVADO) and the Canada Research Chair in Humanitarian Supply Chain Analytics. B. Balcik was partially supported by a grant from the Scientific and Technological Research Council of Turkey (TUBITAK) 2219 program. This support is gratefully acknowledged. Supplemental Material: The online appendix is available at https://doi.org/10.1287/opre.2021.0141 .
Keywords: Infolettre; Infolettre_Avril_2024

A global algorithm for identifying changing streamflow regimes: application to Canadian natural streams (1966–2010) - Zaerpour, Masoud; Hatami, Shadi; Sadri, Javad; Nazemi, Ali (Hydrology and Earth System Sciences, 2021)
Abstract. Climate change affects natural streamflow regimes globally. To assess alterations in streamflow regimes, typically temporal variations in one or a few streamflow characteristics are taken into account. This approach, however, cannot see simultaneous changes in multiple streamflow characteristics, does not utilize all the available information contained in a streamflow hydrograph, and cannot describe how and to what extent streamflow regimes evolve from one to another. To address these gaps, we conceptualize streamflow regimes as intersecting spectrums that are formed by multiple streamflow characteristics. Accordingly, the changes in a streamflow regime should be diagnosed through gradual, yet continuous changes in an ensemble of streamflow characteristics. To incorporate these key considerations, we propose a generic algorithm to first classify streams into a finite set of intersecting fuzzy clusters. Accordingly, by analyzing how the degrees of membership to each cluster change in a given stream, we quantify shifts from one regime to another. We apply this approach to the data, obtained from 105 natural Canadian streams, during the period of 1966 to 2010. We show that natural streamflow in Canada can be categorized into six regime types, with clear hydrological and geographical distinctions. Analyses of trends in membership values show that alterations in natural streamflow regimes vary among different regions. Having said that, we show that in more than 80 % of considered streams, there is a dominant regime shift that can be attributed to simultaneous changes in streamflow characteristics, some of which have remained previously unknown. Our study not only introduces a new globally relevant algorithm for identifying changing streamflow regimes but also provides a fresh look at streamflow alterations in Canada, highlighting complex and multifaceted impacts of climate change on streamflow regimes in cold regions.
Keywords: Infolettre; Infolettre_Janvier_2022; Site_internet_RIISQ

A dynamics model of the emergency medical supply chain in epidemic considering deprivation cost - Shi, Wenqiang; He, Jie; Wang, Mingyue; Yang, Fang (Socio-Economic Planning Sciences, 2024)
Keywords: Infolettre; Infolettre_Septembre_2024

On optimization of calibrations of a distributed hydrological model with spatially distributed information on snow - Tiwari, Dipti; Trudel, Mélanie; Leconte, Robert (2023)
Abstract. In northern cold-temperate countries, a large portion of annual streamflow is produced by spring snowmelt, which often triggers floods. It is important to have spatial information about snow parameters such as snow water equivalent (SWE), which can be incorporated into hydrological models, making them more efficient tools for improved decision-making. The future Terrestrial Snow Mass Mission (TSMM) aims to provide high-resolution spatially distributed SWE information; thus, spatial SWE calibration should be considered along with conventional streamflow calibration for model optimization since the overall water balance is often a key objective in the hydrological modelling. The present research implements a unique spatial pattern metric in a multi-objective framework for calibration approach of hydrological models and attempts to determine whether raw SNODAS data can be utilized for hydrological model calibration. The SPAtial Efficiency (SPAEF) metric is explored for spatially calibrating SWE. The HYDROTEL hydrological model is applied to the Au Saumon River Watershed (∽1120 km2) in Eastern Canada using MSWEP precipitation data and ERA-5 land reanalysis temperature data as input to generate high-resolution SWE and streamflow. Different calibration experiments are performed combining Nash-Sutcliffe efficiency (NSE) for streamflow and root-mean-square error (RMSE), and SPAEF for SWE, using the Dynamically Dimensioned Search (DDS) and Pareto Archived Multi-Objective Optimization (PADDS) algorithms. Results of the study demonstrate that multi-objective calibration outperforms sequential calibration in terms of model performance. Traditional model calibration involving only streamflow produced slightly higher NSE values; however, the spatial distribution of SWE could not be adequately maintained. This study indicates that utilizing SPAEF for spatial calibration of snow parameters improved streamflow prediction compared to the conventional practice of using RMSE for calibration. SPAEF is further implied to be a more effective metric than RMSE for both sequential and multi-objective calibration. During validation, the calibration experiment incorporating multi-objective SPAEF exhibits enhanced performance in terms of NSE and Kling-Gupta Efficiency (KGE) compared to calibration experiment solely based on NSE. This observation supports the notion that incorporating SPAEF computed on raw SNODAS data within the calibration framework results in a more robust hydrological model.
Keywords: Infolettre; Infolettre_Mai_2024

Failure mechanism, existing constitutive models and numerical modeling of landslides in sensitive clay: a review - Urmi, Zinan Ara; Saeidi, Ali; Chavali, Rama Vara Prasad; Yerro, Alba (Geoenvironmental Disasters, 2023)
Abstract Landslides involving sensitive clays are recurrent events in the world's northern regions and are especially notorious in eastern Canada. The two critical factors that separate sensitive clay landslides from traditional slope stability analysis are the highly brittle behavior in undrained conditions (strain-softening) characteristic of progressive or retrogressive failures and the large deformations associated with them. Conventional limit equilibrium analysis has numerous shortcomings in incorporating these characteristics when assessing landslides in sensitive clays. This paper presents an extensive literature review of the failure mechanics characteristics of landslides in sensitive clays and the existing constitutive models and numerical tools to analyze such slopes' stability and post-failure behavior. The advantages and shortcomings of the different techniques to incorporate strain-softening and large deformation in the numerical modeling of sensitive clay landslides are assessed. The literature review depicts that elastoviscoplastic soil models with non-linear strain-softening laws and rate effects represent the material behavior of sensitive clays. Though several numerical models have been proposed to analyze post-failure runouts, the amount of work performed in line with sensitive clay landslides is very scarce. That creates an urgent need to apply and further develop advanced numerical tools for better understanding and predicting these catastrophic events.
Keywords: Infolettre; Infolettre_Juin_2023

Hybrid forecasting: blending climate predictions with AI models - Slater, Louise J.; Arnal, Louise; Boucher, Marie-Amélie; Chang, Annie Y.-Y.; Moulds, Simon; Murphy, Conor; Nearing, Grey; Shalev, Guy; Shen, Chaopeng; Speight, Linda; Villarini, Gabriele; Wilby, Robert L.; et al. (Hydrology and Earth System Sciences, 2023)
Abstract. Hybrid hydroclimatic forecasting systems employ data-driven (statistical or machine learning) methods to harness and integrate a broad variety of predictions from dynamical, physics-based models – such as numerical weather prediction, climate, land, hydrology, and Earth system models – into a final prediction product. They are recognized as a promising way of enhancing the prediction skill of meteorological and hydroclimatic variables and events, including rainfall, temperature, streamflow, floods, droughts, tropical cyclones, or atmospheric rivers. Hybrid forecasting methods are now receiving growing attention due to advances in weather and climate prediction systems at subseasonal to decadal scales, a better appreciation of the strengths of AI, and expanding access to computational resources and methods. Such systems are attractive because they may avoid the need to run a computationally expensive offline land model, can minimize the effect of biases that exist within dynamical outputs, benefit from the strengths of machine learning, and can learn from large datasets, while combining different sources of predictability with varying time horizons. Here we review recent developments in hybrid hydroclimatic forecasting and outline key challenges and opportunities for further research. These include obtaining physically explainable results, assimilating human influences from novel data sources, integrating new ensemble techniques to improve predictive skill, creating seamless prediction schemes that merge short to long lead times, incorporating initial land surface and ocean/ice conditions, acknowledging spatial variability in landscape and atmospheric forcing, and increasing the operational uptake of hybrid prediction schemes.
Keywords: Infolettre; Infolettre_Juin_2023

Atmospheric and surface observations during the Saint John River Experiment on Cold Season Storms (SAJESS) - Thompson, Hadleigh D.; Thériault, Julie M.; Déry, Stephen J.; Stewart, Ronald E.; Boisvert, Dominique; Rickard, Lisa; Leroux, Nicolas R.; Colli, Matteo; Vionnet, Vincent (2023)
Abstract. The amount and phase of cold season precipitation accumulating in the upper Saint John River basin are critical factors in determining spring runoff, ice-jams, and flooding in downstream communities. To study the impact of winter and spring storms on the snowpack in the upper Saint John River (SJR) basin, the Saint John River Experiment on Cold Season Storms (SAJESS) utilized meteorological instrumentation, upper air soundings, human observations, and hydrometeor macrophotography during winter/spring 2020–21. Here, we provide an overview of the SAJESS study area, field campaign, and existing data networks surrounding the upper SJR basin. Initially, meteorological instrumentation was co-located with an Environment and Climate Change Canada station near Edmundston, New Brunswick, in early December 2020. This was followed by an intensive observation period that involved manual observations, upper-air soundings, a multi-angle snowflake camera, macrophotography of solid hydrometeors, and advanced automated instrumentation throughout March and April 2021. The resulting datasets include optical disdrometer size and velocity distributions of hydrometeors, micro rain radar output, near-surface meteorological observations, and wind speed, temperature, pressure and precipitation amounts from a K63 Hotplate precipitation gauge, the first one operating in Canada. These data are publicly available from the Federated Research Data Repository at https://doi.org/10.20383/103.0591 (Thompson et al., 2022). We also include a synopsis of the data management plan and data processing, and a brief assessment of the rewards and challenges of utilizing community volunteers for hydro-meteorological citizen science.
Keywords: Infolettre; Infolettre_Mars_2024

A Hydrograph-Based Approach to Improve Satellite-Derived Snow Water Equivalent at the Watershed Scale - Whittaker, Charles; Leconte, Robert (Water, 2022)
For the past few decades, remote sensing has been a valuable tool for deriving global information on snow water equivalent (SWE), where products derived from space-borne passive microwave radiometers are favoured as they respond to snow depth, an important component of SWE. GlobSnow, a novel SWE product, has increased the accuracy of global-scale SWE estimates by combining remotely sensed radiometric data with other physiographic characteristics, such as snow depth, as quantified by climatic stations. However, research has demonstrated that passive microwaves algorithms tend to underestimate SWE for deep snowpack. Approaches were proposed to correct for such underestimation; however, they are computer intensive and complex to implement at the watershed scale. In this study, SWEmax information from the near real time 5-km GlobSnow product, provided by Copernicus and the European Space Agency (ESA) and GlobSnow product at 25 km resolution were corrected using a simple bias correction approach for watershed scale applications. This method, referred to as the Watershed Scale Correction (WSC) approach, estimates the bias based on the direct runoff that occurs during the spring melt season. Direct runoff is estimated on the one hand from SWEmax information as main input. Infiltration is also considered in computing direct runoff. An independent estimation of direct runoff from gauged stations is also performed. Discrepancy between these estimates allows for estimating the bias correction factor. This approach is advantageous as it exploits data that commonly exists i.e., flow at gauged stations and remotely sensed/reanalysis data such as snow cover and precipitation. The WSC approach was applied to watersheds located in Eastern Canada. It was found that the average bias moved from 33.5% with existing GlobSnow product to 18% with the corrected product, using the recommended recursive filter coefficient β of 0.925 for baseflow separation. Results show the usefulness of integrating direct runoff for bias correction of existing GlobSnow product at the watershed scale. In addition, potential benefits are offered using the recursive filter approach for baseflow separation of watersheds with limited in situ SWE measurements, to further reduce overall uncertainties and bias. The WSC approach should be appealing for poorly monitored watersheds where SWE measurements are critical for hydropower production and where snowmelt can pose serious flood-related damages.
Keywords: Infolettre; Infolettre_Fevrier_2023

Citizens’ viewpoints on stormwater Beneficial Management Practices (BMPs) in Brazil - Sousa, Bruno José de Oliveira; Fialho, Hailton César Pimentel; Taffarello, Denise; Souza, Felipe Augusto Arguello; Hassanzadeh, Elmira; Mendiondo, Eduardo Mario; de Oliveira, Paulo Tarso Sanches (Journal of Cleaner Production, 2021)
Floods are among the most dangerous and destructive hazards in the world. Stormwater Beneficial Management Practices (BMPs) are a set of strategies that can assist in reducing urban floods and their damages by capturing surface runoff and promoting infiltration. Engagement of citizens in the selection of stormwater BMPs may facilitate the decision-making processes and increase the chance of adopting and maintaining them. Due to existence of catastrophic floods in Brazil, implementing BMPs is essential in the urban areas. The objective of this study is to understand the viewpoints of citizens about a set of stormwater BMPs in Brazil. Moreover, we aim to comprehend whether diverging viewpoints about the BMPs can be associated with existence of different layers in the society. For this purpose, online surveys were used to access wide and diverse groups of citizens from different ages, levels of education and income, as well as geographical location. The questions and descriptions of BMPs were prepared in an accessible language, and then disseminated through various platforms. The responses of more than 1000 participants were analyzed using descriptive and statistical methods. Our results show that the participants found the retention and detention basins, as well as permeable pavement as the most efficient BMPs. Moreover, considering the small-scale practices, although lot related BMPs are considered less efficient, citizens are willing to use green roof, bioretention, and rain barrels in their properties. In addition, most of the respondents support public investments on stormwater BMPs. Our analyses show that participants' age and level of education statistically influenced their choice of BMPs and willingness to pay for their maintenance and construction. These results can help Brazilian policy makers to prepare flood management plans by including stormwater BMPs that would be more accepted by the population. In addition, proposing practices that are aligned with citizens’ perceptions creates a sense of responsibility, and is in accordance with the Brazilian New Framework of Sanitation that includes public participation in policy making.
Keywords: Infolettre; Infolettre_Juillet_2022; Site_internet_RIISQ

Meteorological Analysis and Damage Survey Study of the Impact of Hurricane Elsa in Barbados - Sandiford, Sanola; Romanic, Djordje; Gyakum, John (Natural Hazards Review, 2024)
Keywords: Infolettre; Infolettre_Ete_2024

Experiencing Trauma During or Before Pregnancy: Qualitative Secondary Analysis After Two Disasters - Severson, Emily; Olson, Joanne K.; Hyde, Ashley; Brémault-Phillips, Suzette; Spiers, Jude; King, Suzanne; Bick, Johanna; Lipschutz, Rebecca; Verstraeten, Barbara S.E.; Olson, David M. (Maternal and Child Health Journal, 2023)
Keywords: Infolettre; Infolettre_Avril_2023

Extreme Sea Level Estimation Combining Systematic Observed Skew Surges and Historical Record Sea Levels - Saint Criq, Laurie; Gaume, Eric; Hamdi, Yasser; Ouarda, Taha B. M. J. (Water Resources Research, 2022)
Abstract The estimation of sea levels corresponding to high return periods is crucial for coastal planning and for the design of coastal defenses. This paper deals with the use of historical observations, that is, events that occurred before the beginning of the systematic tide gauge recordings, to improve the estimation of design sea levels. Most of the recent publications dealing with statistical analyses applied to sea levels suggest that astronomical high tide levels and skew surges should be analyzed and modeled separately. Historical samples generally consist of observed record sea levels. Some extreme historical skew surges can easily remain unnoticed if they occur at low or moderate astronomical high tides and do not generate extreme sea levels. The exhaustiveness of historical skew surge series, which is an essential criterion for an unbiased statistical inference, can therefore not be guaranteed. This study proposes a model combining, in a single Bayesian inference procedure, information of two different natures for the calibration of the statistical distribution of skew surges: measured skew surges for the systematic period and extreme sea levels for the historical period. A data‐based comparison of the proposed model with previously published approaches is presented based on a large number of Monte Carlo simulations. The proposed model is applied to four locations on the French Atlantic and Channel coasts. Results indicate that the proposed model is more reliable and accurate than previously proposed methods that aim at the integration of historical records in coastal sea level or surge statistical analyses. , Plain Language Summary Coastal facilities must be designed as to be protected from extreme sea levels. Sea levels at high tide are the combination of astronomical high tides, which can be predicted, and skew surges. The estimation of the statistical distribution of skew surges is usually based on the skew surges measured by tide gauges and can be improved with the use of historical information, observations that occurred before the beginning of the tide gauge recordings. Extreme skew surges combined with low or moderate astronomical high tides would not necessarily generate extreme sea levels, and consequently some extreme historical skew surges could be missed. The exhaustiveness of historical information is an essential criterion for an unbiased estimation, but it cannot be guaranteed in the case of historical skew surges. The present study proposes to combine skew surges for the recent period and extreme sea levels for the historical period. The proposed model is compared to previously published approaches and appears to be more reliable and accurate. The proposed model is applied to four case studies on the French Atlantic and Channel coasts. , Key Points The exhaustiveness of historical sea record information is demonstrated based on French Atlantic coast data A comparative analysis of approaches to integrate historical information is carried out The efficiency of a new method for the combination of systematic skew surges and historical records is verified
Keywords: Infolettre; Infolettre_Juillet_2022; Site_internet_RIISQ

Hydrological connectivity controls dissolved organic carbon exports in a peatland-dominated boreal catchment stream - Prijac, Antonin; Gandois, Laure; Taillardat, Pierre; Bourgault, Marc-André; Riahi, Khawla; Ponçot, Alex; Tremblay, Alain; Garneau, Michelle (Hydrology and Earth System Sciences, 2023)
The magnitudes of dissolved organic carbon (DOC) exports from boreal peatlands to streams through lateral subsurface flow vary during the ice-free season. Peatland water table depth and the alternation of low and high flow in peat-draining streams are thought to drive this DOC export variability. However, calculation of the specific DOC exports from a peatland can be challenging considering the multiple potential DOC sources within the catchment. A calculation approach based on the hydrological connectivity between the peat and the stream could help to solve this issue, which is the approach used in the present research. This study took place from June 2018 to October 2019 in a boreal catchment in northeastern Canada, with 76.7 % of the catchment being covered by ombrotrophic peatland. The objectives were to (1) establish relationships between DOC exports from a headwater stream and the peatland hydrology; (2) quantify, at the catchment scale, the amount of DOC laterally exported to the draining stream; and (3) define the patterns of DOC mobilization during high-river-flow events. At the peatland headwater stream outlet, the DOC concentrations were monitored at a high frequency (hourly) using a fluorescent dissolved organic matter (fDOM) sensor, a proxy for DOC concentration. Hydrological variables, such as stream outlet discharge and peatland water table depth (WTD), were continuously monitored at hourly intervals for 2 years. Our results highlight the direct and delayed control of subsurface flow from peat to the stream and associated DOC exports. Rain events raised the peatland WTD, which increased hydrological connectivity between the peatland and the stream. This led to increased stream discharge (Q) and a delayed DOC concentration increase, typical of lateral subsurface flow. The magnitude of the WTD increase played a crucial role in influencing the quantity of DOC exported. Based on the observations that the peatland is the most important contributor to DOC exports at the catchment scale and that other DOC sources were negligible during high-flow periods, we propose a new approach to estimate the specific DOC exports attributable to the peatland by distinguishing between the surfaces used for calculation during high-flow and low-flow periods. In 2018–2019, 92.6 % of DOC was exported during flood events despite the fact that these flood events accounted for 59.1 % of the period. In 2019–2020, 93.8 % of DOC was exported during flood events, which represented 44.1 % of the period. Our analysis of individual flood events revealed three types of events and DOC mobilization patterns. The first type is characterized by high rainfall, leading to an important WTD increase that favours the connection between the peatland and the stream and leading to high DOC exports. The second is characterized by a large WTD increase succeeding a previous event that had depleted DOC available to be transferred to the stream, leading to low DOC exports. The third type corresponds to low rainfall events with an insufficient WTD increase to reconnect the peatland and the stream, leading to low DOC exports. Our results suggest that DOC exports are sensitive to hydroclimatic conditions; moreover, flood events, changes in rainfall regime, ice-free season duration, and porewater temperature may affect the exported DOC and, consequently, partially offset the net carbon sequestration potential of peatlands.
Keywords: Infolettre; Infolettre_Mars_2024

Climate scenarios of extreme precipitation using a combination of parametric and non-parametric bias correction methods in the province of Québec - Roy, Philippe; Rondeau-Genesse, Gabriel; Jalbert, Jonathan; Fournier, Élyse (Canadian Water Resources Journal / Revue canadienne des ressources hydriques, 2023)
Keywords: Infolettre; Infolettre_Ete_2023

Multi-proxy paleohydrological and paleoecological reconstruction of a subaquatic cave in western Cuba - Peros, Matthew C.; Collins, Shawn; Martínez-López, Joao Gabriel; Viñola López, Lázaro W.; Sosa, Miguel Angel Pereira; Brisson, Laurence Forget; Hardy, François; Lamothe, Michel; Van Hengstum, Peter J.; Phillips, Bil; Broad, Kenneth; Heinerth, Jill; et al. (Palaeogeography, Palaeoclimatology, Palaeoecology, 2023)
Keywords: Infolettre; Infolettre_Septembre_2023

Critical factors for successful housing reconstruction projects following a major disaster Critical Factors for Successful Housing Reconstruction Projects Following a Major Disaster - Sadiqi Wardak, Zabihullah; Coffey, Vaughan; Trigunarsyah (2013)
Keywords: Infolettre; Infolettre_Septembre_2023

Planning for the Lake Izabal Basin Research Endeavor (LIBRE) continental scientific drilling project in eastern Guatemala - Obrist-Farner, Jonathan; Eckert, Andreas; Douglas, Peter M. J.; Perez, Liseth; Correa-Metrio, Alex; Konecky, Bronwen L.; Bauersachs, Thorsten; Zimmerman, Susan; Scheidt, Stephanie; Brenner, Mark; Kutterolf, Steffen; Maurer, Jeremy; et al. (Scientific Drilling, 2023)
As Earth's atmospheric temperatures and human populations increase, more people are becoming vulnerable to natural and human-induced disasters. This is particularly true in Central America, where the growing human population is experiencing climate extremes (droughts and floods), and the region is susceptible to geological hazards, such as earthquakes and volcanic eruptions, and environmental deterioration in many forms (soil erosion, lake eutrophication, heavy metal contamination, etc.). Instrumental and historical data from the region are insufficient to understand and document past hazards, a necessary first step for mitigating future risks. Long, continuous, well-resolved geological records can, however, provide a window into past climate and environmental changes that can be used to better predict future conditions in the region. The Lake Izabal Basin (LIB), in eastern Guatemala, contains the longest known continental records of tectonics, climate, and environmental change in the northern Neotropics. The basin is a pull-apart depression that developed along the North American and Caribbean plate boundary ∼ 12 Myr ago and contains > 4 km of sediment. The sedimentological archive in the LIB records the interplay among several Earth System processes. Consequently, exploration of sediments in the basin can provide key information concerning: (1) tectonic deformation and earthquake history along the plate boundary; (2) the timing and causes of volcanism from the Central American Volcanic Arc; and (3) hydroclimatic, ecologic, and geomicrobiological responses to different climate and environmental states. To evaluate the LIB as a potential site for scientific drilling, 65 scientists from 13 countries and 33 institutions met in Antigua, Guatemala, in August 2022 under the auspices of the International Continental Scientific Drilling Program (ICDP) and the US National Science Foundation (NSF). Several working groups developed scientific questions and overarching hypotheses that could be addressed by drilling the LIB and identified optimal coring sites and instrumentation needed to achieve the project goals. The group also discussed logistical challenges and outreach opportunities. The project is not only an outstanding opportunity to improve our scientific understanding of seismotectonic, volcanic, paleoclimatic, paleoecologic, and paleobiologic processes that operate in the tropics of Central America, but it is also an opportunity to improve understanding of multiple geological hazards and communicate that knowledge to help increase the resilience of at-risk Central American communities.
Keywords: Infolettre; Infolettre_Avril_2024

A Kriging Method for the Estimation of ALS Point-Cloud Accuracy without Ground Truth - Pashaei, Zahra; Guilbert, Éric; Badard, Thierry (Remote Sensing, 2023)
Airborne LiDAR scanning is a promising approach to providing high-resolution products that are appropriate for different applications, such as flood management. However, the vertical accuracy of airborne LiDAR point clouds is not constant and varies in space. Having a better knowledge of their accuracy will assist decision makers in more accurately estimating the damage caused by flood. Data producers often report the total estimation of errors by means of comparison with a ground truth. However, the reliability of such an approach depends on various factors including the sample size, accessibility to ground truth, distribution, and a large enough diversity of ground truth, which comes at a cost and is somewhat unfeasible in the larger scale. Therefore, the main objective of this article is to propose a method that could provide a local estimation of error without any third-party datasets. In this regard, we take advantage of geostatistical ordinary kriging as an alternative accuracy estimator. The challenge of considering constant variation across the space leads us to propose a non-stationary ordinary kriging model that results in the local estimation of elevation accuracy. The proposed method is compared with global ordinary kriging and a ground truth, and the results indicate that our method provides more reliable error values. These errors are lower in urban and semi-urban areas, especially in farmland and residential areas, but larger in forests, due to the lower density of points and the larger terrain variations.
Keywords: Infolettre

Convolutional neural network and long short-term memory models for ice-jam predictions - Madaeni, Fatemehalsadat; Chokmani, Karem; Lhissou, Rachid; Homayouni, Saeid; Gauthier, Yves; Tolszczuk-Leclerc, Simon (The Cryosphere, 2022)
In cold regions, ice jams frequently result in severe flooding due to a rapid rise in water levels upstream of the jam. Sudden floods resulting from ice jams threaten human safety and cause damage to properties and infrastructure. Hence, ice-jam prediction tools can give an early warning to increase response time and minimize the possible damages. However, ice-jam prediction has always been a challenge as there is no analytical method available for this purpose. Nonetheless, ice jams form when some hydro-meteorological conditions happen, a few hours to a few days before the event. Ice-jam prediction can be addressed as a binary multivariate time-series classification. Deep learning techniques have been widely used for time-series classification in many fields such as finance, engineering, weather forecasting, and medicine. In this research, we successfully applied convolutional neural networks (CNN), long short-term memory (LSTM), and combined convolutional–long short-term memory (CNN-LSTM) networks to predict the formation of ice jams in 150 rivers in the province of Quebec (Canada). We also employed machine learning methods including support vector machine (SVM), k-nearest neighbors classifier (KNN), decision tree, and multilayer perceptron (MLP) for this purpose. The hydro-meteorological variables (e.g., temperature, precipitation, and snow depth) along with the corresponding jam or no-jam events are used as model inputs. Ten percent of the data were excluded from the model and set aside for testing, and 100 reshuffling and splitting iterations were applied to 80 % of the remaining data for training and 20 % for validation. The developed deep learning models achieved improvements in performance in comparison to the developed machine learning models. The results show that the CNN-LSTM model yields the best results in the validation and testing with F1 scores of 0.82 and 0.92, respectively. This demonstrates that CNN and LSTM models are complementary, and a combination of both further improves classification.
Keywords: Infolettre; Infolettre_Juillet_2022; Site_internet_RIISQ

Regional estimation of river water temperature at ungauged locations - Ouarda, Taha B.M.J.; Charron, Christian; St-Hilaire, André (Journal of Hydrology X, 2022)
Keywords: Infolettre; Infolettre_Octobre_2022; Site_internet_RIISQ

Trend and teleconnection analysis of temperature extremes in New South Wales, Australia - Laz, Orpita U.; Rahman, Ataur; Ouarda, Taha B. M. J. (Natural Hazards, 2024)
Abstract This study investigates possible trends and teleconnections in temperature extremes in New South Wales (NSW), Australia. Daily maximum and minimum temperature data covering the period 1971–2021 at 26 stations located in NSW were used. Three indices, which focus on daily maximum temperature, daily minimum temperature, and average daily temperature in terms of Excessive Heat Factor (EHF) were investigated to identify the occurrence of heatwaves (HWs). The study considered HWs of different durations (1-, 5-, and 10-days) in relation to intensity, frequency, duration, and their first occurrence parameters. Finally, the influences of three global climate drivers, namely – the El Niño/Southern Oscillation (ENSO), the Southern Annular Mode (SAM), and the Indian Ocean Dipole (IOD) were investigated with associated heatwave attributes for extended Austral summers. In this study, an increasing trend in both hot days and nights was observed for most of the selected stations within the study area. The increase was more pronounced for the last decade (2011–2021) of the investigated time period. The number, duration and frequency of the heatwaves increased over time considering the EHF criterion, whereas no particular trend was detected in cases of TX90 and TN90. It was also evident that the first occurrence of all the HWs shifted towards the onset of the extended summer while considering the EHF criterion of HWs. The correlations between heatwave attributes and climate drivers depicted that heatwave over NSW was positively influenced by both the IOD and ENSO and negatively correlated with SAM. The findings of this study will be useful in formulating strategies for managing the impacts of extreme temperature events such as bushfires, floods, droughts to the most at-risk regions within NSW.
Keywords: Infolettre; Infolettre_Novembre_2024

Rainfall-triggered waste dump instability analysis based on surface 3D deformation in physical model test - Li, Hanlin; Jin, Xiaoguang; He, Jie; Xue, Yunchuan; Yang, Zhongping (Journal of Mountain Science, 2024)
Keywords: Infolettre; Infolettre_Ete_2024

Enhanced Bioaccumulation and Transfer of Monomethylmercury through Periphytic Biofilms in Benthic Food Webs of a River Affected by Run-of-River Dams - Leclerc, Maxime; Ponton, Dominic E.; Bilodeau, François; Planas, Dolors; Amyot, Marc (Environmental Science & Technology, 2023)
Keywords: Infolettre; Infolettre_Janvier_2024

Alternatives for sustained disaster risk reduction: A re-assessment - Le De, Loic; Baumann, Louise L.; Moatty, Annabelle; Le Masson, Virginie; Kikano, Faten; Fayazi, Mahmood; Fernandez, Manuela; Tomassi, Isabella; Cadag, Jake Rom D. (Jàmbá Journal of Disaster Risk Studies, 2023)
Keywords: Infolettre; Infolettre_Novembre_2023

Trends, Shifting, or Oscillations? Stochastic Modeling of Nonstationary Time Series for Future Water-Related Risk Management - Lee, Taesam; Ouarda, Taha B. M. J. (Earth's Future, 2023)
Hydrological time series often present nonstationarities such as trends, shifts, or oscillations due to anthropogenic effects and hydroclimatological variations, including global climate change. For water managers, it is crucial to recognize and define the nonstationarities in hydrological records. The nonstationarities must be appropriately modeled and stochastically simulated according to the characteristics of observed records to evaluate the adequacy of flood risk mitigation measures and future water resources management strategies. Therefore, in the current study, three approaches were suggested to address stochastically nonstationary behaviors, especially in the long-term variability of hydrological variables: as an overall trend, shifting mean, or as a long-term oscillation. To represent these options for hydrological variables, the autoregressive model with an overall trend, shifting mean level (SML), and empirical mode decomposition with nonstationary oscillation resampling (EMD-NSOR) were employed in the hydrological series of the net basin supply in the Lake Champlain-River Richelieu basin, where the International Joint Committee recently managed and significant flood damage from long consistent high flows occurred. The detailed results indicate that the EMD-NSOR model can be an appropriate option by reproducing long-term dependence statistics and generating manageable scenarios, while the SML model does not properly reproduce the observed long-term dependence, that are critical to simulate sustainable flood events. The trend model produces too many risks for floods in the future but no risk for droughts. The overall results conclude that the nonstationarities in hydrological series should be carefully handled in stochastic simulation models to appropriately manage future water-related risks.
Keywords: Infolettre; Infolettre_Octobre_2023; Infolettre_Septembre_2023

Synthesis of a novel flocculant with dimethylamino propylmethacrylamide and polyether and its flocculation performance - He, Jie; Duan, Ming; Zhou, Shouwei; Zhao, Liqiang; Luo, Zhifeng; Fang, Shenwen (Journal of Dispersion Science and Technology, 2024)
Keywords: Infolettre; Infolettre_Septembre_2024

Synthesis of a water‐soluble high hydroxymethyl content phenolic resin crosslinker and the associated polyacrylamide weak gel property investigation - He, Jie; Ye, Zi; Liao, Dong; Chen, Qing‐mei; Liu, Hang‐rui; Fan, Hai‐bo; Luo, Min; Zhong, Cheng (Journal of Polymer Science, 2024)
Abstract As an in‐depth profile control agent, water‐soluble phenolic resin crosslinking polyacrylamide weak gel has been widely used in the middle and high water cut stage of water flooding reservoir. In this study, the phenolic resin was synthesized by two‐step alkali catalysis. Factors influencing the synthesis of phenolic resin, including the molar ratio of phenol and formaldehyde, catalyst types, reaction time, were investigated with hydroxylmethyl and aldehyde content as the criterion. When the molar ratio of phenolic resin was 1:2 and NaOH was catalyst, at 80°C for 4 h, the phenolic resin had the highest hydroxymethyl content (49.37%) and the lowest free aldehyde content (2.95%). Weak gel was formed by the reaction of LT002‐polyacrylamide with phenolic resin. Taking the gelation time and strength as criteria, the factors influencing the crosslinking property, including hydroxymethyl content, crosslinker addition, and polyacrylamide concentration were investigated respectively. Under optimal formulation, the property investigation shows that the hydroxymethyl group in the phenolic resin can be crosslinked with the amide group in polyacrylamide, the gelation time is long (50–60 h), and the gelation strength is larger than 5 × 10 4 mPa s, which is conductive to the plugging of deep oil layers. When the permeability was 5061 × 10 −3 μm 2 , the plugging rate was 72.73%.
Keywords: Infolettre; Infolettre_Ete_2024

Discrete Element Method Analyses of Bond Degradation Evolutions for Cemented Soils - He, Jie; Li, Tao; Rui, Yi (Fractal and Fractional, 2024)
The degradation of soil bonding, which can be described by the evolution of bond degradation variables, is essential in the constitutive modeling of cemented soils. A degradation variable with a value of 0/1.0 indicates that the applied stress is completely sustained by bonded particles/unbounded grains. The discrete element method (DEM) was used for cemented soils to analyze the bond degradation evolution and to evaluate the degradation variables at the contact scale. Numerical cemented soil samples with different bonding strengths were first prepared using an advanced contact model (CM). Constant stress ratio compression, one-dimensional compression, conventional triaxial tests (CTTs), and true triaxial tests (TTTs) were then implemented for the numerical samples. After that, the numerical results were adopted to investigate the evolution of the bond degradation variables BN and B0. In the triaxial tests, B0 evolves to be near to or larger than BN due to shearing, which indicates that shearing increases the bearing rate of bond contacts. Finally, an approximate stress-path-independent bond degradation variable Bσ was developed. The evolution of Bσ with the equivalent plastic strain can be effectively described by an exponential function and a hyperbolic function.
Keywords: Infolettre; Infolettre_Mars_2024

Fine Particle Migration in a Gas Hydrate Sand: Single- and Two-Phase Fluid Using a Device for Observation at the Pore Scale - He, Jie; Huang, Xiang; Cao, Pei (Journal of Marine Science and Engineering, 2024)
The production of natural gas hydrates will change the cementation strength, porosity, and effective stress in the stratum, which may lead to engineering and geological disasters. Sand production is a phenomenon where sand particles are carried out of the reservoir along with fluids during gas extraction, posing challenges to safe and sustainable production. This study explored the mechanism of fine particle migration in multiphase flow by a microscopic visualization test device. The device can inject a gas–liquid–solid phase at the same time and allow real-time observation. Experimental tests on fine particle migration of single- and two-phase fluid flow were carried out considering different conditions, i.e., fine particle concentration, fine particle size, fluid flow rate, and gas–liquid ratio. The results show that in single-phase fluid flow, the original gas will gradually dissolve in the liquid phase, and finally stay in the test device as bubbles, which can change the pore structures, resulting in the accumulation of fine particles at the gas–liquid interface. In two-phase fluid flow with mixed gas–water fluids, there are two flow modes of gas–liquid flow: mixed flow and separated flow. The interfacial tension at the gas–liquid interface can effectively migrate fine particles when the gas–liquid flows alternately and the sand production rate further increases as the gas–liquid ratio increases. In addition, changes in the concentration of fine particles, particle size, fluid flow rate, and the gas–liquid ratio will affect the migration of fine particles, leading to differences in the final sand production.
Keywords: Infolettre; Infolettre_Fevrier_2024

Determination of duration, threshold and spatiotemporal distribution of extreme continuous precipitation in nine major river basins in China - Jin, Haoyu; Chen, Xiaohong; Adamowski, Jan; Hatami, Shadi (Atmospheric Research, 2024)
Keywords: Infolettre; Infolettre_Mars_2024

Use of Mixed Methods in the Science of Hydrological Extremes: What Are Their Contributions? - Kabo, Raymond; Bourgault, Marc-André; Barrette, Nathalie; Tanguay, Louis (Hydrology, 2023)
Research in hydrological sciences is constantly evolving to provide adequate answers to address various water-related issues. Methodological approaches inspired by mathematical and physical sciences have shaped hydrological sciences from its inceptions to the present day. Nowadays, as a better understanding of the social consequences of extreme meteorological events and of the population’s ability to adapt to these becomes increasingly necessary, hydrological sciences have begun to integrate knowledge from social sciences. Such knowledge allows for the study of complex social-ecological realities surrounding hydrological phenomena, such as citizens’ perception of water resources, as well as individual and collective behaviors related to water management. Using a mixed methods approach to combine quantitative and qualitative approaches has thus become necessary to understand the complexity of hydrological phenomena and propose adequate solutions for their management. In this paper, we detail how mixed methods can be used to research flood hydrology and low-flow conditions, as well as in the management of these hydrological extremes, through the analysis of case studies. We frame our analysis within the three paradigms (positivism, post-positivism, and constructivism) and four research designs (triangulation, complementary, explanatory, and exploratory) that guide research in hydrology. We show that mixed methods can notably contribute to the densification of data on extreme flood events to help reduce forecasting uncertainties, to the production of knowledge on low-flow hydrological states that are insufficiently documented, and to improving participatory decision making in water management and in handling extreme hydrological events.
Keywords: Infolettre; Infolettre_Ete_2023

Interpolation of Precipitation Extremes on a Large Domain Toward IDF Curve Construction at Unmonitored Locations - Jalbert, Jonathan; Genest, Christian; Perreault, Luc (Journal of Agricultural, Biological and Environmental Statistics, 2022)
Abstract An intensity–duration–frequency (IDF) curve describes the relationship between rainfall intensity and duration for a given return period and location. Such curves are obtained through frequency analysis of rainfall data and commonly used in infrastructure design, flood protection, water management, and urban drainage systems. However, they are typically available only in sparse locations. Data for other sites must be interpolated as the need arises. This paper describes how extreme precipitation of several durations can be interpolated to compute IDF curves on a large, sparse domain. In the absence of local data, a reconstruction of the historical meteorology is used as a covariate for interpolating extreme precipitation characteristics. This covariate is included in a hierarchical Bayesian spatial model for extreme precipitations. This model is especially well suited for a covariate gridded structure, thereby enabling fast and precise computations. As an illustration, the methodology is used to construct IDF curves over Eastern Canada. An extensive cross-validation study shows that at locations where data are available, the proposed method generally improves on the current practice of Environment and Climate Change Canada which relies on a moment-based fit of the Gumbel extreme-value distribution.
Keywords: Infolettre; Infolettre_Avril_2022; Site_internet_RIISQ

Besoins et préférences des citoyens pour l’outil prévisionnel en temps réel des crues : Une recherche mixte - Jean, V.; Frini, A.; Boucher, M-A.; Mbaye, K. (Université du Québec à Rimouski, 2022)
Keywords: Infolettre; Infolettre_Septembre_2022; Site_internet_RIISQ

Entre héritage réglementaire et imaginaire du risque: gestion des zones inondables et pratiques d'adaptation au Québec et à Lachute - Gaudette, Marilyne; Germain, Daniel (Zenodo, 2025)
Floods, intensified by climate change, pose major challenges for flood zone management in Quebec. This report addresses these issues through two complementary aspects: a historical analysis of the evolution of flood zone management in Quebec and the projected impact of the cartographic and regulatory overhaul, as well as an exploration of the imaginary surrounding the flood-prone territory of the city of Lachute, which has faced recurrent floods for decades and yet continues to be inhabited. The historical analysis reveals that the major floods of 1974, 1976, 2017, and 2019 marked significant turning points in Quebec’s risk management, particularly by highlighting gaps in the regulatory framework and flood zone mapping. The adoption of the Act Respecting Land Use Planning and Development (LAU) in 1979 and the Policy for the Protection of Shorelines, Littorals, and Floodplains (PPRLPI) in 1987 represented a shift toward a preventive approach. However, inconsistencies, insufficient updates to maps, and uneven enforcement of standards have hindered their effectiveness. The catastrophic floods of 2017 and 2019 triggered a regulatory overhaul, a modernization of mapping, and measures to strengthen community resilience. In 2022, a transitional regime came into effect to tighten the regulation of activities in flood zones, pending the adoption of a risk-based management framework. However, to this day, the regulatory perimeters proposed in the modernization project fail to account for the adaptive capacities deployed by communities to live with water, thus providing a biased interpretation of flood risk. The second part explores the social and cultural representations associated with Lachute’s flood-prone territory. It highlights the complex relationships that have developed between residents and the Rivière du Nord through successive flooding episodes and the adaptation strategies implemented to cope, particularly by those who have repeatedly experienced flooding. These residents have come to live with overflow events and to (co)exist with water, challenging the persistent notion that flood-prone areas are inherently dangerous. While local strategies are sometimes innovative, they remain constrained by a regulatory framework that disregards the human experience of the territory and the specific ways in which people inhabit exposed areas to learn to manage flood risks. In summary, this report underscores the urgency of a territorialized, risk-based approach to modernizing flood zone management. It also highlights the need to look beyond cartographic boundaries and better integrate human and cultural dimensions into planning policies, as illustrated in the case of Lachute, to more accurately reflect the true level of risk. These reflections aim to promote more coherent, sustainable, and acceptable management, planning, and development of exposed territories in response to the growing challenges posed by climate change.
Keywords: Infolettre; Infolettre_Mai_2025

Projected Changes in Extreme Precipitation Patterns across Algerian Sub-Regions - Hamitouche, Yasmine; Zeroual, Ayoub; Meddi, Mohamed; Assani, Ali A.; Alkama, Ramdane; Şen, Zekâi; Zhang, Xinhua (Water, 2024)
Extreme precipitation events play a crucial role in shaping the vulnerability of regions like Algeria to the impacts of climate change. To delve deeper into this critical aspect, this study investigates the changing patterns of extreme precipitation across five sub-regions of Algeria using data from 33 model simulations provided by the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP-CMIP6). Our analysis reveals a projected decline in annual precipitation for four of these regions, contrasting with an expected increase in desert areas where annual precipitation levels remain low, typically not exceeding 120 mm. Furthermore, key precipitation indices such as maximum 1-day precipitation (Rx1day) and extremely wet-day precipitation (R99p) consistently show upward trends across all zones, under both SSP245 and SSP585 scenarios. However, the number of heavy precipitation days (R20mm) demonstrates varied trends among zones, exhibiting stable fluctuations. These findings provide valuable foresight into future precipitation patterns, offering essential insights for policymakers and stakeholders. By anticipating these changes, adaptive strategies can be devised to mitigate potential climate change impacts on crucial sectors such as agriculture, flooding, water resources, and drought.
Keywords: Infolettre; Infolettre_Ete_2024; Site_internet_RIISQ

Regional seismic loss estimation and critical earthquake scenarios for the Western Quebec seismic zone - Goda, Katsuichiro; Rimando, Jeremy; Peace, Alexander L.; Sirous, Navid; Rosset, Philippe; Chouinard, Luc (Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, 2023)
Earthquakes pose potentially substantial risks to residents in the Western Quebec seismic zone of eastern Canada, where Ottawa and Montreal are located. In eastern Canada, the majority of houses are not constructed to modern seismic standards and most homeowners do not purchase earthquake insurance for their homes. If a devastating earthquake strikes, homeowners would be left unprotected financially. To quantify financial risks to homeowners in the Western Quebec seismic zone, regional earthquake catastrophe models are developed by incorporating up-to-date public information on hazard, exposure and vulnerability. The developed catastrophe models can quantify the expected and upper-tail financial seismic risks by considering a comprehensive list of possible seismic events as well as critical earthquake scenarios based on the latest geological data in the region. The results indicate that regional seismic losses could reach several tens of billions of dollars if a moderate-to-large earthquake occurs near urban centres in the region, such as Montreal and Ottawa. The regional seismic loss estimates produced in this study are useful for informing earthquake risk management strategies, including earthquake insurance and disaster relief policies.
Keywords: Infolettre; Infolettre_Mai_2023

Geomechanical Properties of Deep-Sea Pore-Filled Methane Hydrate-Bearing Soils at Critical State Using DEM Analysis - He, Jie; Li, Tao; Rui, Yi (Fractal and Fractional, 2023)
The recognition of the geomechanical properties of methane hydrate-bearing soil (MHBS) is crucial to exploring energy resources. The paper presents the mechanical properties of a pore-filled MHBS at a critical state using the distinct element method (DEM). The pore-filled MHBS was simulated as cemented MH agglomerates to fill the soil pores at varying levels of methane hydration (MH) saturation. A group of triaxial compression (TC) tests were conducted, subjecting MHBS samples to varying effective confining pressures (ECPs). The mechanical behaviors of a pore-filled MHBS were analyzed, as it experienced significant strains leading to a critical state. The findings reveal that the proposed DEM successfully captures the qualitative geomechanical properties of MHBS. As MH saturation increases, the shear strength of MHBS generally rises. Moreover, higher ECPs result in increased shear strength and volumetric contraction. The peak shear strength of MHBS increases with rising MH saturation, while the residual deviator stress remains mainly unchanged at a critical state. There is a good correlation between fabric changes of the MHBS with variations in principal stresses and principal strains. With increasing axial strain, the coordination number (CN) and mechanical coordination number (MCN) increase to peak values as the values of MH saturation and ECPs increase, and reach a stable value at a larger axial strain.
Keywords: Infolettre; Infolettre_Octobre_2023

Study on the long-term performance of shield tunnel passing through the gas-bearing strata - He, Jie; Wei, Xiangyang; Yin, Mei (Underground Space, 2023)
When the shield tunnel passes through the gas-bearing strata, gas and water leakage may occur depending on the sealing performance of the segment joints. This process involves the complex multiphase seepage flow phenomenon in unsaturated soil. In this study, a fully coupled solid-liquid-gas model of the GIL Utility Tunnel was established to investigate the influence of the high-pressure gas on the mechanical properties of the tunnel segments and joints. The constitutive model of the Extended Barcelona Basic Model was implemented to simulate the effect of the seepage process on soil deformation. The results show that significant upward displacement occurred in the gas reservoir and its overlying strata, and the maximum displacement reached 30 mm. In addition, during the leakage of the gas and the water, an increase in the average soil effective stress was observed. It would induce a reduction in the suction and expansion of the yield surface. The tunnel tended to be stable from 20 years onwards, thus the soil deformation due to the water leakage only occurred at the early stage. In addition, the joint opening under the most unfavorable internal force combination was 0.69 mm, and the corresponding bolt stress was 119.5 MPa, which is below the yield limit. The results of this study help to understand the influence of high-pressure gas on tunnel safety and the sealing performance of the joints.
Keywords: Infolettre; Infolettre_Juin_2023

Benefit of assimilating satellite all-sky infrared radiances on the cloud and precipitation prediction of a long-lasting mesoscale convective system over the Tibetan plateau - He, Jie; Ma, Xulin; Chen, Xingchao (Quarterly Journal of the Royal Meteorological Society, 2023)
Heavy rainfall events in the warm season (May–September) over the Tibetan Plateau (TP) region and its downstream areas are often closely related to eastward-propagating Tibetan Plateau Vortices (TPVs). Hence, improving the prediction of TPVs and their associated convective activity is of paramount importance, given the significant potential impacts they can have on densely populated downstream regions, including but not limited to flooding and damages. In this study, a typical long-lived TPV that occurred in July 2008 was used for the first time to explore the benefit of assimilating satellite all-sky infrared radiances on the cloud and precipitation prediction of the TPV-induced eastward-propagating mesoscale convective system (MCS). The all-sky infrared radiances from the water vapor (WV) channel of the geostationary Meteosat-7 and other conventional observations were assimilated into a 4-km grid spacing regional model using the ensemble Kalman filter. The results revealed that the all-sky infrared data assimilation improved the cloud, precipitation, dynamical, and thermodynamical analyses as well as 0–12-hr deterministic and ensemble forecasts. Compared with the experiment in which the all-sky infrared radiances were not assimilated (non-radiance experiment), the experiment with assimilated all-sky infrared radiances yielded clearly improved initial wind and cloud fields, 1–12-hr cloud forecasts, and 1–6-hr precipitation forecasts. This study indicates that assimilation of all-sky satellite radiances has the potential for improving the operational cloud and precipitation forecasts over the TP and its downstream areas.
Keywords: Infolettre; Infolettre_Septembre_2023

Do civil engineering fronts emerge from interdisciplinary research? - He, Jie; Yao, Junlan; Chen, Xin; Liu, Fang; Zhu, Hehua (Frontiers of Structural and Civil Engineering, 2023)
Abstract Interdisciplinary research is considered a source of innovativeness and creativity, serving as a key mechanism for creating recombination necessary for the evolution of science systems. The aim of this study is to quantitatively establish the connection between interdisciplinary research and the research fronts that have recently emerged in civil engineering. The degree of interdisciplinarity of the research fronts was measured by developing metrics from bibliographic analyses. As indicated by the consistent increase in the metrics of interdisciplinarity over time, research fronts tend to emerge in studies with increasing diversity in the disciplines involved. The active disciplines involved in the fronts vary over time. The most active disciplines are no longer fundamental but those associated with energy, environment, and sustainable development, focusing on solutions to climate change and integrating intelligence technologies.
Keywords: Infolettre; Infolettre_Fevrier_2023

Numerical and experimental analyses of methane leakage in shield tunnel - He, Jie; Zhu, Hehua; Wei, Xiangyang; Jin, Rui; Jiao, Yaji; Yin, Mei (Frontiers of Structural and Civil Engineering, 2023)
Abstract Tunnels constructed in gas-bearing strata are affected by the potential leakage of harmful gases, such as methane gas. Based on the basic principles of computational fluid dynamics, a numerical analysis was performed to simulate the ventilation and diffusion of harmful gases in a shield tunnel, and the effect of ventilation airflow speed on the diffusion of harmful gases was evaluated. As the airflow speed increased from 1.8 to 5.4 m/s, the methane emission was diluted, and the methane accumulation was only observed in the area near the methane leakage channels. The influence of increased ventilation airflow velocity was dominant for the ventilation modes with two and four fans. In addition, laboratory tests on methane leakage through segment joints were performed. The results show that the leakage process can be divided into “rapid leakage” and “slight leakage”, depending on the leakage pressure and the state of joint deformation. Based on the numerical and experimental analysis results, a relationship between the safety level and the joint deformation is established, which can be used as guidelines for maintaining utility tunnels.
Keywords: Infolettre; Infolettre_Octobre_2023

Smooth Spatial Modeling of Extreme Mediterranean Precipitation - Hammami, Hela; Carreau, Julie; Neppel, Luc; Elasmi, Sadok; Feki, Haifa (Water, 2022)
Extreme precipitation events can lead to disastrous floods, which are the most significant natural hazards in the Mediterranean regions. Therefore, a proper characterization of these events is crucial. Extreme events defined as annual maxima can be modeled with the generalized extreme value (GEV) distribution. Owing to spatial heterogeneity, the distribution of extremes is non-stationary in space. To take non-stationarity into account, the parameters of the GEV distribution can be viewed as functions of covariates that convey spatial information. Such functions may be implemented as a generalized linear model (GLM) or with a more flexible non-parametric non-linear model such as an artificial neural network (ANN). In this work, we evaluate several statistical models that combine the GEV distribution with a GLM or with an ANN for a spatial interpolation of the GEV parameters. Key issues are the proper selection of the complexity level of the ANN (i.e., the number of hidden units) and the proper selection of spatial covariates. Three sites are included in our study: a region in the French Mediterranean, the Cap Bon area in northeast Tunisia, and the Merguellil catchment in central Tunisia. The comparative analysis aim at assessing the genericity of state-of-the-art approaches to interpolate the distribution of extreme precipitation events.
Keywords: Infolettre; Infolettre_Fevrier_2023

Evaluation of Concrete Constitutive Models for Finite Element Simulation of Dam Shear Keys - Freitas, Mario; Ben Ftima, Mahdi; Léger, Pierre; Bouaanani, Najib (Proceedings of the Canadian Society of Civil Engineering Annual Conference 2022, 2023)
Keywords: Infolettre; Infolettre_Septembre_2024

Concepts and evolution of urban hydrology - Fletcher, Tim D.; Burns, Matthew J.; Russell, Kathryn L.; Hamel, Perrine; Duchesne, Sophie; Cherqui, Frédéric; Roy, Allison H. (Nature Reviews Earth & Environment, 2024)
Keywords: Infolettre; Infolettre_Novembre_2024

Combining large-scale and regional hydrological forecasts using simple methods - Fontaine, Nicolas; Boucher, Marie-Amélie; Anctil, François; Odry, Jean; Lachance-Cloutier, Simon; Fortin, Vincent; Turcotte, Richard (Canadian Water Resources Journal / Revue canadienne des ressources hydriques, 2024)
Keywords: Infolettre; Infolettre_Novembre_2023

Anthropogenic exacerbations of summer-autumn compound dry-hot severity in the middle and lower reaches of the Yangtze River - Feng, Shuyun; Gu, Xihui; Guan, Yansong; Wang, Quan J.; Wang, Lunche; Du, Lingtong; He, Jie; Zhang, Xiang; Kong, Dongdong (Journal of Hydrology, 2025)
Keywords: Infolettre; Infolettre_Decembre_2024

Deciphering the sedimentary imprint of tsunamis and storms in the Lesser Antilles (Saint Martin): A 3500-year record in a coastal lagoon - Fabbri, Stefano C.; Sabatier, Pierre; Paris, Raphaël; Falvard, Simon; Feuillet, Nathalie; Lothoz, Amélie; St-Onge, Guillaume; Gailler, Audrey; Cordrie, Louise; Arnaud, Fabien; Biguenet, Maude; Coulombier, Thibault; et al. (Marine Geology, 2024)
Keywords: Infolettre; Infolettre_Septembre_2024

Aerial photogrammetry to characterise and numerically model an ice jam in Southern Quebec - Duguay, Jason; Lindenschmidt, Karl-Erich; Trudel, Mélanie; Pruneau, Antoine (Hydrology Research, 2023)
Abstract Collecting data on the dynamic breakup of a river's ice cover is a notoriously difficult task. However, such data are necessary to reconstruct the events leading to the formation of ice jams and calibrate numerical ice jam models. Photogrammetry using images from remotely piloted aircraft (RPA) is a cost-effective and rapid technique to produce large-scale orthomosaics and digital elevation maps (DEMs) of an ice jam. Herein, we apply RPA photogrammetry to document an ice jam that formed on a river in southern Quebec in the winter of 2022. Composite orthomosaics of the 2-km ice jam provided evidence of overbanking flow, hinge cracks near the banks and lengthy longitudinal stress cracks in the ice jam caused by sagging as the flow abated. DEMs helped identify zones where the ice rubble was grounded to the bed, thus allowing ice jam thickness estimates to be made in these locations. The datasets were then used to calibrate a one-dimensional numerical model of the ice jam. The model will be used in subsequent work to assess the risk of ice interacting with the superstructure of a low-level bridge in the reach and assess the likelihood of ice jam flooding of nearby residences.
Keywords: Infolettre; Infolettre_Novembre_2023

The role of internal climate variability on future streamflow projections - Faghih, Mina; Brissette, François (Journal of Hydrology, 2023)
Keywords: Infolettre; Infolettre_Octobre_2023

Effects of the Water-Cement Ratio and the Molding Temperature on the Hydration Heat of Cement - Dai, Jinpeng; He, Jie; Wang, Qicai; Lou, Xuyu (Journal of Wuhan University of Technology-Mater. Sci. Ed., 2024)
Keywords: Infolettre; Infolettre_Septembre_2024

Machine learning prediction of electric flux in concrete and mix proportion optimization design - Dai, Jinpeng; Yang, Xiaoyuan; He, Jie; Wang, Qicai; Zhang, Zhijie (Materials Today Communications, 2024)
Keywords: Infolettre; Infolettre_Fevrier_2024

Updating the intensity-duration-frequency curves in major Canadian cities under changing climate using CMIP5 and CMIP6 model projections - Crévolin, Vincent; Hassanzadeh, Elmira; Bourdeau-Goulet, Sarah-Claude (Sustainable Cities and Society, 2023)
Keywords: Bourdeau-Brien_Michael; Infolettre; Infolettre_Avril_2023

Using depth specific electrical conductivity estimates to improve hydrological simulations in a heterogeneous tile-drained field - Boico, Vinicius F.; Therrien, René; Højberg, Anker L.; Iversen, Bo V.; Koganti, Triven; Varvaris, Ioannis (Journal of Hydrology, 2022)
In agricultural fields, tile drains represent potential pathways for the migration of solutes, such as nitrates, in groundwater and surface water bodies. Tile drain flow is controlled by the temporal and spatial dynamics of the shallow groundwater table, which results from complex interactions between climate, topography and soil heterogeneity. Studies on the effect of topsoil heterogeneity on shallow water and drainage dynamics by fully 3D surface water and groundwater flow modeling are limited. The objective of our study is to demonstrate the use of depth specific electrical conductivity (EC) estimates to improve hydrological simulations in a tile-drained field. The model was applied to a field site in Denmark where times series of drainage discharge and water table elevations are available. Clay-rich soil zones were identified in a tile-drained field using depth specific electrical conductivity estimates generated by the inversion of apparent electrical conductivity data measured using an electromagnetic induction instrument. One model that included the low-permeability clayey zones in the soil layers down to a depth of 1.2 m was compared to a simpler model that assumed homogeneous soil layers. Both models simulate drainage discharge that compares well to the observations. However, including the clayey zones improves the simulation of hydraulic heads, and water table fluctuations, and generates flooded areas that are more representative of those observed during the wet seasons. Our results suggest that the simulation of water table fluctuations can be improved when the soil heterogeneity determined from depth specific EC estimates is included in integrated hydrological models. A better representation of the subsurface flow dynamics will also improve subsequent simulations of the transport and fate of agrochemical substances leaching from fields such as nitrate, which may deteriorate the quality of groundwater and surface water bodies.
Keywords: Infolettre; Infolettre_Avril_2022

Spatiotemporal variability of runoff events in response to rainfall, snowmelt, and rain-on-snow in the Lake Erie Basin - Ali, Geneviève; Siebert, Krystal; Mizero, Steven Mugisha (Journal of Hydrology: Regional Studies, 2024)
Keywords: Infolettre

Impact of Assimilating Radar Solid Precipitation Data in the Canadian Precipitation Analysis System - Beaudry, Florence L.; Bélair, Stéphane; Thériault, Julie M.; Khedhaouiria, Dikra; Lespinas, Franck; Michelson, Daniel; Feng, Pei-Ning; Aubry, Catherine (Journal of Hydrometeorology, 2024)
Abstract The Canadian Precipitation Analysis (CaPA) system provides near-real-time precipitation analyses over Canada by combining observations with short-term numerical weather prediction forecasts. CaPA’s snowfall estimates suffer from the lack of accurate solid precipitation measurements to correct the first-guess estimate. Weather radars have the potential to add precipitation measurements to CaPA in all seasons but are not assimilated in winter due to radar snowfall estimate imprecision and lack of precipitation gauges for calibration. The main objective of this study is to assess the impact of assimilating Canadian dual-polarized radar-based snowfall data in CaPA to improve precipitation estimates. Two sets of experiments were conducted to evaluate the impact of including radar snowfall retrievals, one set using the high-resolution CaPA (HRDPA) with the currently operational quality control configuration and another increasing the number of assimilated surface observations by relaxing quality control. Experiments spanned two winter seasons (2021 and 2022) in central Canada, covering part of the entire CaPA domain. The results showed that the assimilation of radar-based snowfall data improved CaPA’s precipitation estimates 81.75% of the time for 0.5-mm precipitation thresholds. An increase in the probability of detection together with a decrease in the false alarm ratio suggested an improvement of the precipitation spatial distribution and estimation accuracy. Additionally, the results showed improvements for both precipitation mass and frequency biases for low precipitation amounts. For larger thresholds, the frequency bias was degraded. The results also indicated that the assimilation of dual-polarization radar data is beneficial for the two CaPA configurations tested in this study.
Keywords: Infolettre; Infolettre_Septembre_2024

Uncertainty propagation within a water level ensemble prediction system - Bessar, Mohammed Amine; Anctil, François; Matte, Pascal (Journal of Hydrology, 2021)
Keywords: Infolettre; Infolettre_Janvier_2022; Site_internet_RIISQ

Operations research approaches for improving coordination, cooperation, and collaboration in humanitarian relief chains: A framework and literature review - Adsanver, Birce; Balcik, Burcu; Bélanger, Valérie; Rancourt, Marie-Ève (European Journal of Operational Research, 2024)
Keywords: Infolettre; Infolettre_Septembre_2024

Normative Influences on Farmers’ Intentions to Practice Conservation Without Compensation - Vaske, Jerry J.; Landon, Adam C.; Miller, Craig A. (Environmental Management, 2020)
Keywords: Ouvrage_Collectif_Numéro1

Batellerie Gallo-Romaine. Pratiques régionales et influences maritimes méditerranéennes - Boetto, Giulia; Pomey, Patrice; Tchernia, André (Errance-Centre Camille Jullian, 2011)
Les récentes découvertes d’épaves de barges fluviales gallo-romaines à Lyon au Parc Saint-Georges, en 2003, et à Arles à partir de 2002, ont non seulement attiré l’attention sur la batellerie fluviale gallo-romaine mais aussi porté au premier plan des recherches le bassin rhodanien et le midi de la Gaule jusque-là peu présent ou même totalement absent du débat. Ce volume est issu d'une rencontre sur le thème de la batellerie gallo-romaine à la lumière de ces découvertes récentes organisée à Aix-en-Provence dans le cadre des Séminaires de recherche en archéologie maritime méditerranéenne du Centre Camille Jullian.
Keywords: Ouvrage_Collectif_Numéro1

I. Le BAPE, 40 ans de démocratie écologique: - Gauthier, Mario; Simard, Louis (La démocratie écologique, 2022)
Keywords: Ouvrage_Collectif_Numéro1

Strategies for integrating water management and spatial planning: Organising for spatial quality in the Dutch “Room for the River” program - Busscher, T.; Van Den Brink, M.; Verweij, S. (Journal of Flood Risk Management, 2019)
In response to extreme flood events and an increasing awareness that traditional flood control measures alone are inadequate to deal with growing flood risks, spatial flood risk management strategies have been introduced. These strategies do not only aim to reduce the probability and consequences of floods, they also aim to improve local and regional spatial qualities. To date, however, research has been largely ignorant as to how spatial quality, as part of spatial flood risk management strategies, can be successfully achieved in practice. Therefore, this research aims to illuminate how spatial quality is achieved in planning practice. This is done by evaluating the configurations of policy instruments that have been applied in the Dutch Room for the River policy program to successfully achieve spatial quality. This policy program is well known for its dual objective of accommodating higher flood levels as well as improving the spatial quality of the riverine areas. Based on a qualitative comparative analysis, we identified three successful configurations of policy instruments. These constitute three distinct management strategies: the “program‐as‐guardian”, the “project‐as‐driver,” and “going all‐in” strategies. These strategies provide important leads in furthering the development and implementation of spatial flood risk management, both in the Netherlands and abroad.
Keywords: Ouvrage_Collectif_Numéro1

Pluralité des instruments et des logiques politiques pour l’adaptation aux changements globaux en zone côtière - Dhénain, Sandrine; Barreteau, Olivier (Natures Sciences Sociétés, 2018)
L’adaptation au changement climatique est un nouvel enjeu pour la gestion des territoires. Au niveau local, elle apparaît souvent comme une injonction, alors même que, pour l’instant, elle est un concept flou. Elle est présentée comme l’application de bonnes pratiques, mais les questions « qui s’adapte à quoi ? » et « pourquoi ? » demeurent implicites. En explicitant ces éléments, nous proposons de montrer que l’adaptation est une question plurielle et politique. À partir de l’analyse des documents de planification et des plans d’action faisant référence aux changements globaux sur un territoire littoral, nous montrons l’existence de quatre logiques d’adaptation distinctes, plus ou moins transformatrices du système socioécologique, que l’on peut appréhender à partir de la typologie suivante : « contrôler et maintenir », « faire faire », « réguler » et « reconfigurer », qui portent en germe différentes reconfigurations socioéconomiques et politiques. , Since the 2000s, “adaptation” is a new dictate for the management of local territories in France, but its implementation is fairly limited. Adaptation is mainly a semantically unclear and loosely defined concept. Decision-makers could “operationalize” adaptation by simply applying a specific methodology. However, adaptation is not a mere mechanism; it is also a process that implies economic, social and ecological trade-offs for the socio-ecological system. These political dimensions are often unformulated. In order to provide a vehicle to clarify this concept and its political dimensions, we propose a typology of adaptation measures. What does adaptation mean? Adjustment of what (territories, populations, communities, local economies, etc.), to what (climate change, global change) and with what effects? We reviewed local actions and strategic plans related to climate but also to urban planning, flooding and water management on the eastern coastal area of Languedoc Roussillon in Mediterranean France. We conducted and analyzed semi-structured interviews with institutional actors. We analyzed and classified public policy instruments, associated the underlying “logic” (raise limiting factors, create a new awareness, etc.), and their potential effects. Throughout our effort to develop a typology, we have highlighted the political dimensions of adaptation actions and shed a light on trade-offs linked to adaptation choices.
Keywords: Ouvrage_Collectif_Numéro1

ISO 31000 :. Management du risque – Principes et lignes directrices - International Standards Organisation (ISO) (Organisation internationale de normalisation, 2018)
Keywords: Ouvrage_Collectif_Numéro1

Let the river erode! Enabling lateral migration increases geomorphic unit diversity - Williams, R. D.; Bangen, S.; Gillies, E.; Kramer, N.; Moir, H.; Wheaton, J. (Science of The Total Environment, 2020)
River restoration practice frequently employs conservative designs that create and maintain prescribed, static morphology. Such approaches ignore an emerging understanding of resilient river systems that typically adjust their morphology in response to hydrologic, vegetative and sediment supply changes. As such, using increased dynamism as a restoration design objective will arguably yield more diverse and productive habitats, better managed expectations, and more self-sustaining outcomes. Here, we answer the following question: does restoring lateral migration in a channelised river that was once a wandering gravel-bed river, result in more diverse in-channel geomorphology? We acquired pre- and post-restoration topographic surveys on a segment of the Allt Lorgy, Scotland to quantify morphodynamics and systematically map geomorphic units, using Geomorphic Unit Tool (GUT) software. GUT implements topographic definitions to discriminate between a taxonomy of fluvial landforms that have been developed from an extension of the River Styles framework, using 3-tiered hierarchy: (1) differentiation based on stage or elevation relative to channel; (2) classification of form based on shape (mound, bowl, trough, saddle, plane, wall); and (3) mapping geomorphic units based on attributes (e.g., position and orientation). Results showed restoration increased geomorphic unit diversity, with the Shannon Diversity Index increasing from 1.40 pre-restoration (2012) to 2.04 (2014) and 2.05 (2016) after restoration. Channel widening, due to bank erosion, caused aerial coverage of in-channel geomorphic units to increase 23% after restoration and 6% further in the two-years following restoration. Once bank protection was removed, allowing bank erosion yieled a local supply of sediment to enable the formation and maintenance of lateral and point bars, riffles and diagonal bar complexes, and instream wood created structurally-forced pools and riffles. The methodology used systematically quantifies how geomorphic unit diversity increases when a river is given back its freedom space. The framework allows for testing restoration design hypotheses in post-project appraisal.
Keywords: Ouvrage_Collectif_Numéro1

Stream habitat provided by large wood at risk under drainage law - Shirey, Patrick D.; Kenny, Jillian B.; Brueseke, Michael A.; Lamberti, Gary A. (Earth Surface Processes and Landforms, 2020)
Watershed management efforts in agriculturally dominated landscapes of North America face nearly two centuries of laws and policies that encouraged habitat destruction. Although streams and wetlands in these landscapes are actively being restored using designs that incorporate science and engineering, watershed drainage laws can constrain action or impact passively restored or naturalized habitat. In general, drainage laws require removal of any riparian vegetation or wood deemed to obstruct flow in streams regulated as drains. We use a case study from Indiana (USA) to introduce the shortcomings of drainage laws for allowing large wood, which is an important habitat feature, to remain in stream ecosystems. Removals of large wood from monitored stream reaches in a regulated drain were associated with subsequent declines in fish biomass. Such legal activities represent an important environmental management problem that exists under drainage laws which apply to streams over a widespread geographic region of North America. Recent litigation in Wisconsin (USA) suggests that if state legislatures fail to update these antiquated laws, the courts may act in favour of science-based management of drains. The statutes and regulations that govern agricultural drainage warrant careful consideration if streams within drainage districts are to be managed to improve ecological function. © 2020 John Wiley & Sons, Ltd.
Keywords: Ouvrage_Collectif_Numéro1

Response of juvenile salmonids to large wood placement in Columbia River tributaries - Clark, Christopher; Roni, Philip; Burgess, Shelby (Hydrobiologia, 2019)
Placement of large wood is a common stream restoration technique in western North America and increasingly in other parts of the world. Considerable information exists on response of anadromous salmonids in small (< 15 m bankfull width) coastal streams of western North America, but limited information exists on anadromous fish response to wood placement in larger streams or in the more arid interior Columbia River Basin. An extensive post-treatment design was used to sample 29 large wood placement projects to determine their physical and biological effectiveness. We sampled paired treatment and control reaches that were approximately 20 times longer than bankfull width and quantified fish abundance and habitat attributes during summer. Proportion of pool area, number of pools, large wood (LW), and pool forming large wood were significantly higher in paired treatment than control reaches. Juvenile Chinook salmon (Oncorhynchus tshawytscha), steelhead (O. mykiss) coho salmon (O. kisutch), and cutthroat trout (O. clarkii) abundances were significantly higher in treatment than control reaches, but no significant responses were detected for mountain whitefish (Prosopium williamsoni) or dace (Rhinichthys spp.). Chinook and coho responses were positively correlated with LW and pool area suggesting wood placement produced reach-scale increases of juvenile salmonid abundance.
Keywords: Ouvrage_Collectif_Numéro1

A process-based approach to restoring depositional river valleys to Stage 0, an anastomosing channel network - Powers, Paul D.; Helstab, Matt; Niezgoda, Sue L. (River Research and Applications, 2019)
Stream restoration approaches most often quantify habitat degradation, and therefore recovery objectives, on aquatic habitat metrics based on a narrow range of species needs (e.g., salmon and trout), as well as channel evolution models and channel design tools biased toward single-threaded, and “sediment-balanced” channel patterns. Although this strategy enhances perceived habitat needs, it often fails to properly identify the underlying geomorphological and ecological processes limiting species recovery and ecosystem restoration. In this paper, a unique process-based approach to restoration that strives to restore degraded stream, river, or meadow systems to the premanipulated condition is presented. The proposed relatively simple Geomorphic Grade Line (GGL) design method is based on Geographic Information System (GIS) and field-based analyses and the development of design maps using relative elevation models that expose the relic predisturbance valley surface. Several case studies are presented to both describe the development of the GGL method and to illustrate how the GGL method of evaluating valley surfaces has been applied to Stage 0 restoration design. The paper also summarizes the wide applicability of the GGL method, the advantages and limitations of the method, and key considerations for future designers of Stage 0 systems anywhere in the world. By presenting this ongoing Stage 0 restoration work, the authors hope to inspire other practitioners to embrace the restoration of dynamism and diversity through restoring the processes that create multifaceted river systems that provide long-term resiliency, meta-stability, larger and more complex and diverse habitats, and optimal ecosystem benefits.
Keywords: Ouvrage_Collectif_Numéro1

Bank erosion processes measured with UAV-SfM along complex banklines of a straight mid-sized river reach - Duró, Gonzalo; Crosato, Alessandra; Kleinhans, Maarten G.; Uijttewaal, Wim S. J. (Earth Surface Dynamics, 2018)
We apply structure from motion (SfM) photogrammetry with imagery from an unmanned aerial vehicle (UAV) to measure bank erosion processes along a mid-sized river reach. This technique offers a unique set of characteristics compared to previously used methods to monitor banks, such as high resolution and relatively fast deployment in the field. We analyse the retreat of a 1.2 km restored bank of the Meuse River which has complex vertical scarps laying on a straight reach, features that present specific challenges to the UAV-SfM application. We surveyed eight times within a year with a simple approach, combining different photograph perspectives and overlaps to identify an effective UAV flight. The accuracy of the digital surface models (DSMs) was evaluated with real-time kinematic (RTK) GPS points and airborne laser scanning of the whole reach. An oblique perspective with eight photo overlaps and 20 m of cross-sectional ground-control point distribution was sufficient to achieve the relative precision to observation distance of ∼1 : 1400 and 3 cm root mean square error (RMSE), complying with the required accuracy. A complementary nadiral view increased coverage behind bank toe vegetation. Sequential DSMs captured signatures of the erosion cycle such as mass failures, slump-block deposition, and bank undermining. Although UAV-SfM requires low water levels and banks without dense vegetation as many other techniques, it is a fast-in-the-field alternative to survey reach-scale riverbanks in sufficient resolution and accuracy to quantify bank retreat and identify morphological features of the bank failure and erosion processes. Improvements to the adopted approach are recommended to achieve higher accuracies.
Keywords: Ouvrage_Collectif_Numéro1

Morphological adjustment of the Qingshuigou channel on the Yellow River Delta and factors controlling its avulsion - Zheng, Shan; Han, Shasha; Tan, Guangming; Xia, Junqiang; Wu, Baosheng; Wang, Kairong; Edmonds, Douglas A. (CATENA, 2018)
The avulsion time scale of channels on the Yellow River delta (YRD) is about a decade due to the large sediment load, and rapid channel aggradation and progradation. Nevertheless, the Qingshuigou channel has been maintained for about four decades since 1976. This channel provides an ideal opportunity to study channel evolution following avulsion and to examine different avulsion criteria. In this study, we analyzed the geomorphic adjustment of the lower Qingshuigou channel during 1976–2015, and calculated normalized gradient advantage and superelevation at the channel to estimate how close the channel was to avulsion. Results showed that channel evolution processes may be divided into four phases: I (1976–1980) rapid aggradation, II (1980–1985) channel widening and enlargement, III (1985–1996) main channel aggradation and shrinkage, and IV (1996–2015) main channel incision and deepening. Evolution phases I, II and III are similar to the avulsion cycle observed in natural and experimental fluvial systems. The calculated values of normalized gradient advantage and superelevation in early 1990s exceeded the critical values suggested by previous studies, implying that the channel was prone to avulsion. Nevertheless, avulsion was prevented mainly due to limited overbank flows, constriction from artificial dikes, and slowed channel extension as a result of reduced sediment load. The evolution of the Qingshuigou channel confirms previous arguments that superelevation and gradient advantage are not sufficient for avulsion, and multiple factors should be considered, including flood frequency, lateral mobility, sediment diameter, and human interruptions.
Keywords: Ouvrage_Collectif_Numéro1

A systematic review of school‐based interventions and their outcomes for youth exposed to traumatic events - Yohannan, Justina; Carlson, John S. (Psychology in the Schools, 2019)
Abstract Youth exposed to traumatic events are at higher risk for negative developmental outcomes, including low academic performance, poor social skills, and mental health concerns. To best address these risks, school‐based intervention services, and trauma‐informed practices can be provided. The goal of this study was to systematically review the intervention research conducted on school‐based trauma interventions, with specific attention to examine intervention effectiveness, feasibility, and acceptability across studies. It was found that feasibility and acceptability are not frequently examined, though the data available showed that Enhancing Resiliency Amongst Students Experiencing‐Stress (ERASE‐Stress) and school‐based cognitive behavioral therapy (CBT) had high rates of fidelity; and school‐based CBT had high levels of acceptability. The review also examined demographic variables and found that U. S.‐based research reported racially/ethnically diverse samples, and most samples were from low‐income populations. Most studies examined youth exposed to war‐ and terror‐related traumas or natural disaster‐related traumas. Additionally, this review provides future directions for research and reveals the need for further research on intervention feasibility and acceptability. A brief description of practice recommendations based on prior research has also been included. It also exposes the need for studies that examine various student demographic variables that are currently not examined and consistency in rating scale use in school‐based trauma intervention research.
Keywords: Ouvrage_Collectif_Numéro1