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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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.