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A new method for sensitivity analysis of water depths is presented based on a two-dimensional hydraulic model as a convenient and cost-effective alternative to Monte Carlo simulations. The method involves perturbation of the probability distribution of input variables. A relative sensitivity index is calculated for each variable, using the Gauss quadrature sampling, thus limiting the number of runs of the hydraulic model. The variable-related highest variation of the expected water depths is considered to be the most influential. The proposed method proved particularly efficient, requiring less information to describe model inputs and fewer model executions to calculate the sensitivity index. It was tested over a 45 km long reach of the Richelieu River, Canada. A 2D hydraulic model was used to solve the shallow water equations (SWE). Three input variables were considered: Flow rate, Manning’s coefficient, and topography of a shoal within the considered reach. Four flow scenarios were simulated with discharge rates of 759, 824, 936, and 1113 m 3 / s . The results show that the predicted water depths were most sensitive to the topography of the shoal, whereas the sensitivity indices of Manning’s coefficient and the flow rate were comparatively lower. These results are important for making better hydraulic models, taking into account the sensitivity analysis.

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.

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.

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.

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.

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).

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...

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.

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.

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.

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.

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.

Abstract Accelerating mountain glacier recession in a warming climate threatens the sustainability of mountain water resources. The extent to which groundwater will provide resilience to these water resources is unknown, in part due to a lack of data and poorly understood interactions between groundwater and surface water. Here we address this knowledge gap by linking climate, glaciers, surface water, and groundwater into an integrated model of the Shullcas Watershed, Peru, in the tropical Andes, the region experiencing the most rapid mountain‐glacier retreat on Earth. For a range of climate scenarios, our model projects that glaciers will disappear by 2100. The loss of glacial meltwater will be buffered by relatively consistent groundwater discharge, which only receives minor recharge (~2%) from glacier melt. However, increasing temperature and associated evapotranspiration, alongside potential decreases in precipitation, will decrease groundwater recharge and streamflow, particularly for the RCP 8.5 emission scenario. , Plain Language Summary Mountain regions play an important role in water supply, because meltwater from snow and ice feeds rivers during dry periods. Groundwater (water stored in the pore spaces of soils and rock), which flows into rivers, is also an important store of water in mountain areas and may help to protect water resources against the negative impacts of shrinking mountain glaciers. We used extensive field measurements and computer modeling of the Shullcas Watershed in the Peruvian Andes to determine the current and future role of groundwater in the face of climate change. Our model projects that glaciers in our study area will disappear by 2100. The loss of glacier meltwater is buffered in the short term (~30 years) by consistent groundwater flow to rivers. However, in the long term (>60 years), precipitation is expected to decrease and rising temperatures lead to increased evaporation and water use by plants. These factors reduce groundwater recharge and storage, causing dry season streamflow to drop. , Key Points Groundwater accounts for a large fraction of streamflow and only receives minor (~2%) recharge from glaciers in the study catchment in Peru As meltwater decreases, groundwater provides consistent discharge in the near term (~30 years), becoming a larger fraction of streamflow In the long term (>60 years), groundwater storage and discharge decrease in response to higher evapotranspiration and lower precipitation

Abstract. Climate models predict amplified warming at high elevations in low latitudes, making tropical glacierized regions some of the most vulnerable hydrological systems in the world. Observations reveal decreasing streamflow due to retreating glaciers in the Andes, which hold 99 % of all tropical glaciers. However, the timescales over which meltwater contributes to streamflow and the pathways it takes – surface and subsurface – remain uncertain, hindering our ability to predict how shrinking glaciers will impact water resources. Two major contributors to this uncertainty are the sparsity of hydrologic measurements in tropical glacierized watersheds and the complication of hydrograph separation where there is year-round glacier melt. We address these challenges using a multi-method approach that employs repeat hydrochemical mixing model analysis, hydroclimatic time series analysis, and integrated watershed modeling. Each of these approaches interrogates distinct timescale relationships among meltwater, groundwater, and stream discharge. Our results challenge the commonly held conceptual model that glaciers buffer discharge variability. Instead, in a subhumid watershed on Volcán Chimborazo, Ecuador, glacier melt drives nearly all the variability in discharge (Pearson correlation coefficient of 0.89 in simulations), with glaciers contributing a broad range of 20 %–60 % or wider of discharge, mostly (86 %) through surface runoff on hourly timescales, but also through infiltration that increases annual groundwater contributions by nearly 20 %. We further found that rainfall may enhance glacier melt contributions to discharge at timescales that complement glacier melt production, possibly explaining why minimum discharge occurred at the study site during warm but dry El Niño conditions, which typically heighten melt in the Andes. Our findings caution against extrapolations from isolated measurements: stream discharge and glacier melt contributions in tropical glacierized systems can change substantially at hourly to interannual timescales, due to climatic variability and surface to subsurface flow processes.

Abstract The management of sugar maple (Acer saccharum) at the northern edge of its range is mainly oriented toward timber production, from trees of higher grades. However, both the quality of mature trees in natural stands and how the quality may vary depending on the silvicultural treatment are unknown, especially under northern conditions. The objective of this study was to describe the variation in stem quality of mature maple trees (diameter >33 cm) according to climatic, geographic or soil variables, and to evaluate the effects of a first selection cutting cycle on this quality. Annual temperature (1.7–4.1° C) was the most important variable explaining differences in the proportion of higher-grade trees, with a 16 percent gain associated with every additional increase in degrees Celsius. The practice of a first selection cutting was associated with an 11 percent gain in this proportion. Although the actual proportion of high-quality trees was below 35 percent on the coolest sites, a proper tree selection through silviculture could likely improve this proportion in future decades, whereas the potential effects of climate change are unclear.

TanDEM-X digital elevation model (DEM) is a global DEM released by the German Aerospace Center (DLR) at outstanding resolution of 12 m. However, the procedure for its creation involves the combination of several DEMs from acquisitions spread between 2011 and 2014, which casts doubt on its value for precise glaciological change detection studies. In this work we present TanDEM-X DEM as a high-quality product ready for use in glaciological studies. We compare it to Aerial Laser Scanning (ALS)-based dataset from April 2013 (1 m), used as the ground-truth reference, and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) V003 DEM and SRTM v3 DEM (both 30 m), serving as representations of past glacier states. We use a method of sub-pixel coregistration of DEMs by Nuth and Kääb (2011) to determine the geometric accuracy of the products. In addition, we propose a slope-aspect heatmap-based workflow to remove the errors resulting from radar shadowing over steep terrain. Elevation difference maps obtained by subtraction of DEMs are analyzed to obtain accuracy assessments and glacier mass balance reconstructions. The vertical accuracy (± standard deviation) of TanDEM-X DEM over non-glacierized area is very good at 0.02 ± 3.48 m. Nevertheless, steep areas introduce large errors and their filtering is required for reliable results. The 30 m version of TanDEM-X DEM performs worse than the finer product, but its accuracy, −0.08 ± 7.57 m, is better than that of SRTM and ASTER. The ASTER DEM contains errors, possibly resulting from imperfect DEM creation from stereopairs over uniform ice surface. Universidad Glacier has been losing mass at a rate of −0.44 ± 0.08 m of water equivalent per year between 2000 and 2013. This value is in general agreement with previously reported mass balance estimated with the glaciological method for 2012–2014.

Local scour is the removal of soil around bridge foundations under the erosive action of flowing water. This hydraulic risk has raised awareness of the need for developing continuous monitoring techniques to estimate scour depth around bridge piers and abutments. One of the emerging techniques is based on monitoring the vibration frequency of either bridge piers or a driven sensor in the riverbed. The sensor proposed in this study falls into the second category. Some unresolved issues are investigated: the effect of the geometry and material of the sensor, the effect of the embedded length and the effect of soil type. To this end, extensive laboratory tests are performed using rods of different materials, with various geometries and lengths. These tests are conducted in both dry sand and a soft clayey soil. Since the sensor will be placed in the riverbed, it is crucial to evaluate the effect of immersed conditions on its response. A numerical 3D finite-element model was developed and compared against experimental data. This model was then used to compute the ‘wet’ frequencies of the sensor. Finally, based on both the experimental and numerical results, an equivalent cantilever model is proposed to correlate the variation of the frequency of the sensor to the scour depth.