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Rain‐on‐snow (ROS) is a compound hydrometeorological extreme event that can lead to severe socioeconomic impacts and affect ecosystem function. In high‐latitude regions, the percolation of liquid precipitation through snowpack and the associated formation of ice layers can create greater potential for significant runoff and also cause hardship for wintertime ungulate foraging. In this study, we assess the characteristics of ROS events and the corresponding impacts over a large sub‐arctic river basin in northwestern Canada. We propose seven indices to assess the projected changes in both major and minor ROS events, defined as instances of 10 and 3 mm/day, respectively, of rainfall occurring on SWE greater than 5 mm, taking into account precipitation intensity and snowpack depth. We use simulations from the variable infiltration capacity hydrologic model driven by a suite of multivariate bias‐corrected global climate models from the fifth phase of the Coupled Model Intercomparison Project and assess the ROS changes under the 1.5, 2, 3 and 4°C global warming levels above the pre‐industrial period. Overall, ROS events occur more frequently in October–December and January–March (JFM) compared to other seasons. The effects of major and minor ROS events on runoff generation in JAS and OND are considerable at higher elevations, with mean runoff more than 50% greater on ROS days than non‐ROS days in many cases. Furthermore, the analyses project notable increases in the frequency of both Major and Minor ROS events in all summer and fall. However, a notable decrease in ROS frequency is present in spring, and in winter, ROS frequency has inconsistent changes. Our comprehensive assessment of ROS events, their projected changes, and associated impacts in a sub‐arctic river basin underscore these events' critical role in shaping hydrological patterns and affecting communities, infrastructure and ecosystem dynamics. [ABSTRACT FROM AUTHOR]

Obtaining reliable water balance estimates remains a major challenge in Canada for large regions with scarce in situ measurements. Various remote sensing products can be used to complement observation-based datasets and provide an estimate of the water balance at river basin or regional scales. This study provides an assessment of the water balance using combinations of various remote sensing– and data assimilation–based products and quantifies the nonclosure errors for river basins across Canada, ranging from 90 900 to 1 679 100 km2, for the period from 2002 to 2015. A water balance equation combines the following to estimate the monthly water balance closure: multiple sources of data for each water budget component, including two precipitation products—the global product WATCH Forcing Data ERA-Interim (WFDEI), and the Canadian Precipitation Analysis (CaPA); two evapotranspiration products—MODIS, and Global Land surface Evaporation: The Amsterdam Methodology (GLEAM); one source of water storage data—GRACE from three different centers; and observed discharge data from hydrometric stations (HYDAT). The nonclosure error is attributed to the different data products using a constrained Kalman filter. Results show that the combination of CaPA, GLEAM, and the JPL mascon GRACE product tended to outperform other combinations across Canadian river basins. Overall, the error attributions of precipitation, evapotranspiration, water storage change, and runoff were 36.7%, 33.2%, 17.8%, and 12.2%, which corresponded to 8.1, 7.9, 4.2, and 1.4 mm month−1, respectively. In particular, the nonclosure error from precipitation dominated in Western Canada, whereas that from evapotranspiration contributed most in the Mackenzie River basin. [ABSTRACT FROM AUTHOR]

We describe a state-of-the-art framework for projecting hydrologic impacts due to enhanced warming and amplified moisture fluxes in the subarctic environment under anthropogenic climate change. We projected future hydrologic changes based on phase 5 of the Coupled Model Intercomparison Project global climate model simulations using the Variable Infiltration Capacity hydrologic model and a multivariate bias correction/downscaling method for the Liard basin in subarctic northwestern Canada. Subsequently, the variable importance of key climatic controls on a set of hydrologic indicators was analyzed using the random forests statistical model. Results indicate that enhanced warming and wetness by the end of century would lead to pronounced declines in annual and monthly snow water equivalent (SWE) and earlier maximum SWE. Prominent changes in the streamflow regime include increased annual mean and minimum flows, earlier maximum flows, and either increased or decreased maximum flows depending on interactions between temperature, precipitation, and snow. Using the variable importance analysis, we find that precipitation exerts the primary control on maximum SWE and annual mean and maximum flows, and temperature has the main influence on timings of maximum SWE and flow, and minimum flow. Given these climatic controls, the changes in the hydrologic indicators become progressively larger under the scenarios of 1.5°, 2.0°, and 3.0°C global mean temperature increases above the preindustrial period. Hence, the framework presented in this study provides a detailed diagnosis of the hydrologic changes as well as controls and interactions of the climatic variables, which could be generalized for understanding regional scale changes in subarctic/nival basins. [ABSTRACT FROM AUTHOR]

It is a common practice to employ hydrologic models for assessing present and future states of watersheds and assess the degree of alterations for a range of hydrologic indicators. Previous studies indicate that the hydrologic model may not be able to replicate some of the indicators of interest, which raises questions on the reliability of model simulated changes. Hence, we initiated a study to evaluate the replicability of the streamflow changes by employing the widely used variable infiltration capacity hydrologic model for sub-basins and mainstem of the Fraser River Basin, Canada. Given that the hydrologic regime of the region is known to be influenced by teleconnections to the Pacific Decadal Oscillation (PDO) and El Niño-Southern Oscillation (ENSO), we used hydrologic responses to the PDO and ENSO states as analogues for evaluating the model's ability to simulate climate-induced changes. The results revealed that the qualitative patterns of response, such as lower flows for the warm PDO state compared to the cool state, and progressively higher flows for the warm, neutral and cool ENSO states, were generally well reproduced for most hydrologic indicators. Additionally, while the directions of change between the different PDO and ENSO states were mostly well replicated, the magnitude of change for some of the indicators showed considerable differences. Hence, replicability of both magnitude and direction of change need to be carefully examined before using the simulated indicators for assessing future hydrologic changes, and a reliable replication increases the confidence of projected changes. Copyright © 2016 Her Majesty the Queen in Right of Canada. Hydrological Processes. © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This study uses a high-frequency discharge and nitrate concentration dataset from the Weida catchment in Germany for the catchment scale hydrologic response analysis. Nitrate transport in the catchment is mostly conservative as indicated by the nitrate stable isotope (δ15N and δ18O) analysis. Discharge-nitrate concentration data from the catchment show distinctive patterns, suggesting flushing and dilution response. A self-organizing feature map-based methodology was employed to identify such patterns or cluster in the datasets. Based on knowledge of the catchment conditions and prevailing understanding of discharge-nitrate concentration relationship, the clusters were characterized into five qualitative flow responses: (1) baseflow; (2) subsurface flow increase; (3) surface runoff increase; (4) surface runoff recession; and (5) subsurface flow decrease. Such qualitative flowpaths were used as soft data for a multi-objective calibration of a hydrological model (WaSiM-ETH). The calibration led to a reasonable simulation of overall discharge (Nash-Sutcliffe coefficient: 0.84) and qualitative flowpaths (76% agreement). A prerequisite for using such methodology is limited biogeochemical transformation of nitrate (such as denitrification). [ABSTRACT FROM AUTHOR]

Flows originating from cold and mountainous watersheds are highly dependent on temperature and precipitation patterns, and the resulting snow accumulation and melt conditions, affecting the magnitude and timing of annual peak flows. This study applied a multiple linear regression (MLR) modelling framework to investigate spatial variations and relative importance of hydroclimatic drivers of annual maximum flows (AMF) and mean spring flows (MAMJflow) in 25 river basins across western Canada. The results show that basin average maximum snow water equivalent (SWEmax), April 1st SWE and spring precipitation (MAMJprc) are the most important predictors of both AMF and MAMJflow, with the proportion of explained variance averaging 51.7%, 44.0% and 33.5%, respectively. The MLR models' abilities to project future changes in AMF and MAMJflow in response to changes to the hydroclimatic controls are also examined using the Canadian Regional Climate Model (CanRCM4) output for RCP 4.5 and RCP8.5 scenarios. The results show considerable spatial variations depending on individual watershed characteristics with projected changes in AMF ranging from −69% to +126% and those of MAMJflow ranging from −48% to +81% by the end of this century. In general, the study demonstrates that the MLR framework is a useful approach for assessing the spatial variation in hydroclimatic controls of annual maximum and mean spring flows in the western Canadian river basins. However, there is a need to exercise caution in applying MLR models for projecting changes in future flows, especially for regulated basins. [ABSTRACT FROM AUTHOR]