Abstract. This study evaluated the effects of climate perturbations on snowmelt, soil moisture and streamflow generation in small Canadian Prairie basins using a modeling approach based on classification of basin biophysical and hydraulic parameters. Seven basin classes that encompass the entirety of the Prairie ecozone in Canada were determined by cluster analysis of biophysical characteristics. Individual semi-distributed virtual basin (VB) models representing these classes were parameterized in the Cold Regions Hydrological Model (CRHM) platform which includes modules for snowmelt and sublimation, soil freezing and thawing, actual evapotranspiration (ET), soil moisture dynamics, groundwater recharge and depressional storage dynamics including fill and spill runoff generation and variable connected areas. Precipitation (P) and temperature (T) perturbation scenarios covering the range of climate model predictions for the 21st century were used to evaluate climate sensitivity of hydrological processes in individual land cover and basin types across the Prairie ecozone. Results indicated that snow accumulation in wetlands had a greater sensitivity to P and T than that in croplands and grasslands in all the basin types. Wetland soil moisture was also more sensitive to T than the cropland and grassland soil moisture. Jointly influenced by land cover distribution and local climate, basin-average snow accumulation was more sensitive to T in the drier and grassland-characterized basins than in the wetter basins dominated by cropland, whilst basin-average soil moisture was most sensitive to T and P perturbations in basins typified by pothole depressions and broad river valleys. Annual streamflow had the greatest sensitivities to T and P in the dry and poorly connected Interior Grassland basins but the smallest in the wet and well-connected Southern Manitoba basins. The ability of P to compensate for warming induced reductions in snow accumulation and streamflow was much higher in the wetter and cropland-dominated basins than in the drier and grassland-characterized basins, whilst decreases in cropland soil moisture induced by the maximum expected warming of 6 °C could be fully offset by P increase of 11 % in all the basins. These results can be used to 1) identify locations which had the largest hydrological sensitivities to changing climate; and 2) diagnose underlying processes responsible for hydrological responses to expected climate change. Variations of hydrological sensitivity in land cover and basin types suggest that different water management and adaptation methods are needed to address enhanced water stress due to expected climate change in different regions of the Prairie ecozone.

Abstract. Significant challenges from changes in climate and land use face sustainable water use in the Canadian Prairies ecozone. The region has experienced significant warming since the mid-20th century, and continued warming of an additional 2 ∘C by 2050 is expected. This paper aims to enhance understanding of climate controls on Prairie basin hydrology through numerical model experiments. It approaches this by developing a basin-classification-based virtual modelling framework for a portion of the Prairie region and applying the modelling framework to investigate the hydrological sensitivity of one Prairie basin class (High Elevation Grasslands) to changes in climate. High Elevation Grasslands dominate much of central and southern Alberta and parts of south-western Saskatchewan, with outliers in eastern Saskatchewan and western Manitoba. The experiments revealed that High Elevation Grassland snowpacks are highly sensitive to changes in climate but that this varies geographically. Spring maximum snow water equivalent in grasslands decreases 8 % ∘C−1 of warming. Climate scenario simulations indicated that a 2 ∘C increase in temperature requires at least an increase of 20 % in mean annual precipitation for there to be enough additional snowfall to compensate for enhanced melt losses. The sensitivity in runoff is less linear and varies substantially across the study domain: simulations using 6 ∘C of warming, and a 30 % increase in mean annual precipitation yields simulated decreases in annual runoff of 40 % in climates of the western Prairie but 55 % increases in climates of eastern portions. These results can be used to identify those areas of the region that are most sensitive to climate change and highlight focus areas for monitoring and adaptation. The results also demonstrate how a basin classification-based virtual modelling framework can be applied to evaluate regional-scale impacts of climate change with relatively high spatial resolution in a robust, effective and efficient manner.

• Snow, glaciers, wetlands, frozen ground and permafrost needed in hydrological models. • Water quality export by coupling biochemical transformations to cold regions processes. • Hydrological sensitivity to land use depends on cold regions processes. • Strong cold regions hydrological sensitivity to climate warming. Cold regions involve hydrological processes that are not often addressed appropriately in hydrological models. The Cold Regions Hydrological Modelling platform (CRHM) was initially developed in 1998 to assemble and explore the hydrological understanding developed from a series of research basins spanning Canada and international cold regions. Hydrological processes and basin response in cold regions are simulated in a flexible, modular, object-oriented, multiphysics platform. The CRHM platform allows for multiple representations of forcing data interpolation and extrapolation, hydrological model spatial and physical process structures, and parameter values. It is well suited for model falsification, algorithm intercomparison and benchmarking, and has been deployed for basin hydrology diagnosis, prediction, land use change and water quality analysis, climate impact analysis and flood forecasting around the world. This paper describes CRHM’s capabilities, and the insights derived by applying the model in concert with process hydrology research and using the combined information and understanding from research basins to predict hydrological variables, diagnose hydrological change and determine the appropriateness of model structure and parameterisations.

Abstract. Wetland drainage has been pervasive in the North American Prairie Pothole Region. There is strong evidence that this drainage increases the hydrological connectivity of previously isolated wetlands and, in turn, runoff response to snowmelt and rainfall. It can be hard to disentangle the role of climate from the influence of wetland drainage in observed records. In this study, a basin-classification-based virtual modelling approach is described that can isolate these effects on runoff regimes. The basin class which was examined, entitled Pothole Till, extends throughout much of Canada's portion of the Prairie Pothole Region. Three knowledge gaps were addressed. First, it was determined that the spatial pattern in which wetlands are drained has little influence on how much the runoff regime was altered. Second, no threshold could be identified below which wetland drainage has no effect on the runoff regime, with drainage thresholds as low as 10 % in the area being evaluated. Third, wetter regions were less sensitive to drainage as they tend to be better hydrologically connected, even in the absence of drainage. Low flows were the least affected by drainage. Conversely, during extremely wet years, runoff depths could double as the result of complete wetland removal. Simulated median annual runoff depths were the most responsive, potentially tripling under typical conditions with high degrees of wetland drainage. As storage capacity is removed from the landscape through wetland drainage, the size of the storage deficit of median years begins to decrease and to converge on those of the extreme wet years. Model simulations of flood frequency suggest that, because of these changes in antecedent conditions, precipitation that once could generate a median event with wetland drainage can generate what would have been a maximum event without wetland drainage. The advantage of the basin-classification-based virtual modelling approach employed here is that it simulated a long period that included a wide variety of precipitation and antecedent storage conditions across a diversity of wetland complexes. This has allowed seemingly disparate results of past research to be put into context and finds that conflicting results are often only because of differences in spatial scale and temporal scope of investigation. A conceptual framework is provided that shows, in general, how annual runoff in different climatic and drainage situations will likely respond to wetland drainage in the Prairie Pothole Region.

Extensive wetland drainage has occurred across the Canadian Prairies, and drainage activities are ongoing in many areas (Dahl 1990; Watmough and Schmoll 2007; Bartzen et al. 2010; Dahl 2014; Prairi...

The goal of this commentary is to critically evaluate the use of popular performance metrics in hydrologic modeling. We focus on the Nash-Sutcliffe Efficiency (NSE) and the Kling-Gupta Efficiency (KGE) metrics, which are both widely used in hydrologic research and practice around the world. Our specific objectives are: (a) to provide tools that quantify the sampling uncertainty in popular performance metrics; (b) to quantify sampling uncertainty in popular performance metrics across a large sample of catchments; and (c) to prescribe the further research that is, needed to improve the estimation, interpretation, and use of popular performance metrics in hydrologic modeling. Our large-sample analysis demonstrates that there is substantial sampling uncertainty in the NSE and KGE estimators. This occurs because the probability distribution of squared errors between model simulations and observations has heavy tails, meaning that performance metrics can be heavily influenced by just a few data points. Our results highlight obvious (yet ignored) abuses of performance metrics that contaminate the conclusions of many hydrologic modeling studies: It is essential to quantify the sampling uncertainty in performance metrics when justifying the use of a model for a specific purpose and when comparing the performance of competing models.

• Basins in the Canadian Prairies have varying contributing fractions of their areas. • Caused by the variable storage of water in depressions. • The effects of the spatial and frequency distributions of depressions are quantified. • Will lead to the development of improved hydrological models for the region. Runoff in many locations within the Canadian Prairies is dominated by intermittent fill-and-spill between depressions. As a result, many basins have varying fractions of their areas connected to their outlets, due to changing depressional storage. The objective of this research is to determine the causes of the relationships between water storage and the connected fraction of depression-dominated Prairie basins. It is hypothesized that the shapes of the relationship curves are influenced by both the spatial and frequency distributions of depressional storage. Three sets of numerical experiments are presented to test the hypothesis. The first set of experiments demonstrates that where the number of depressions is small, their size and spatial distributions are important in controlling the relationship between the volume of depressional storage and the connected fraction of a basin. As the number of depressions is increased, the areal fractions of the largest depressions decrease, which reduces the importance of the spatial distribution of depressions. The second set of experiments demonstrates that the curve enveloping the connected fraction of a basin can be derived from the frequency distribution of depression areas, and scaling relationships between the area, volume and catchment area of the depressions, when the area of the largest depression is no greater than approximately 5% of the total. The third set of experiments demonstrates that the presence of a single large depression can strongly influence the relationship between the depressional storage and the connected fraction of a basin, depending on the relative size of the large depression, and its location within the basin. A single depression containing 30% of the total depressional area located near the outlet was shown to cause a basin to be nearly endorheic. A similar depression near the top of a basin was demonstrated not to fill and was therefore unable to contribute flows. The implications of the findings for developing hydrological models of large Prairie drainage basins are discussed.

The hydrography of the Canadian Prairies and adjacent northern US Great Plains is unusual in that the landscape is flat and recently formed due to the effects of pleistocene glaciation and a semi-arid climate since holocene deglaciation. Therefore, there has not been sufficient energy, time, or runoff water to carve typical dendritic surface water drainage networks in many locations. In these regions, runoff is often detented and sometimes stored by the millions of depressions (known locally as “potholes” or “sloughs”) that cover the landscape.

Abstract. East of the Continental Divide in the cold interior of Western Canada, the Mackenzie and Nelson River basins have some of the world's most extreme and variable climates, and the warming climate is changing the landscape, vegetation, cryosphere, and hydrology. Available data consist of streamflow records from a large number (395) of natural (unmanaged) gauged basins, where flow may be perennial or temporary, collected either year-round or during only the warm season, for a different series of years between 1910 and 2012. An annual warm-season time window where observations were available across all stations was used to classify (1) streamflow regime and (2) seasonal trend patterns. Streamflow trends were compared to changes in satellite Normalized Difference Indices. Clustering using dynamic time warping, which overcomes differences in streamflow timing due to latitude or elevation, identified 12 regime types. Streamflow regime types exhibit a strong connection to location; there is a strong distinction between mountains and plains and associated with ecozones. Clustering of seasonal trends resulted in six trend patterns that also follow a distinct spatial organization. The trend patterns include one with decreasing streamflow, four with different patterns of increasing streamflow, and one without structure. The spatial patterns of trends in mean, minimum, and maximum of Normalized Difference Indices of water and snow (NDWI and NDSI) were similar to each other but different from Normalized Difference Index of vegetation (NDVI) trends. Regime types, trend patterns, and satellite indices trends each showed spatially coherent patterns separating the Canadian Rockies and other mountain ranges in the west from the poorly defined drainage basins in the east and north. Three specific areas of change were identified: (i) in the mountains and cold taiga-covered subarctic, streamflow and greenness were increasing while wetness and snowcover were decreasing, (ii) in the forested Boreal Plains, particularly in the mountainous west, streamflows and greenness were decreasing but wetness and snowcover were not changing, and (iii) in the semi-arid to sub-humid agricultural Prairies, three patterns of increasing streamflow and an increase in the wetness index were observed. The largest changes in streamflow occurred in the eastern Canadian Prairies.

Abstract. The interior of western Canada, like many similar cold mid- to high-latitude regions worldwide, is undergoing extensive and rapid climate and environmental change, which may accelerate in the coming decades. Understanding and predicting changes in coupled climate–land–hydrological systems are crucial to society yet limited by lack of understanding of changes in cold-region process responses and interactions, along with their representation in most current-generation land-surface and hydrological models. It is essential to consider the underlying processes and base predictive models on the proper physics, especially under conditions of non-stationarity where the past is no longer a reliable guide to the future and system trajectories can be unexpected. These challenges were forefront in the recently completed Changing Cold Regions Network (CCRN), which assembled and focused a wide range of multi-disciplinary expertise to improve the understanding, diagnosis, and prediction of change over the cold interior of western Canada. CCRN advanced knowledge of fundamental cold-region ecological and hydrological processes through observation and experimentation across a network of highly instrumented research basins and other sites. Significant efforts were made to improve the functionality and process representation, based on this improved understanding, within the fine-scale Cold Regions Hydrological Modelling (CRHM) platform and the large-scale Modélisation Environmentale Communautaire (MEC) – Surface and Hydrology (MESH) model. These models were, and continue to be, applied under past and projected future climates and under current and expected future land and vegetation cover configurations to diagnose historical change and predict possible future hydrological responses. This second of two articles synthesizes the nature and understanding of cold-region processes and Earth system responses to future climate, as advanced by CCRN. These include changing precipitation and moisture feedbacks to the atmosphere; altered snow regimes, changing balance of snowfall and rainfall, and glacier loss; vegetation responses to climate and the loss of ecosystem resilience to wildfire and disturbance; thawing permafrost and its influence on landscapes and hydrology; groundwater storage and cycling and its connections to surface water; and stream and river discharge as influenced by the various drivers of hydrological change. Collective insights, expert elicitation, and model application are used to provide a synthesis of this change over the CCRN region for the late 21st century.

In cold agricultural regions, seasonal snowmelt over frozen soils provides the primary source of runoff and transports large nutrient loads downstream. The postglacial landscape of the Canadian Prairies and Northern Plains of the United States creates challenges for hydrological and water quality modeling. Here, the application of conventional hydrological models is problematic because of cold regions hydrological and chemical processes, the lack of fluvially eroded drainage systems, large noncontributing areas to streamflow and level topography. A new hydrodynamic model was developed to diagnose overland flow from snowmelt in this situation. The model was used to calculate the effect of variable contributing areas on (1) hydrological connectivity and the development of (2) tipping points in streamflow generation and (3) predominant chemical transport pathways. The agricultural Steppler Basin in Manitoba, Canada, was used to evaluate the model and diagnose snowmelt runoff. Relationships were established between contributing area and (1) snowmelt runoff intensity, (2) seasonal snowmelt volumes and duration, and (3) inundated, active and connected areas. Variations in the contributing area depended on terrain and snowmelt characteristics including wind redistribution of snow. Predictors of hydrological response and the size of the contributing area were developed which can be used in larger scale hydrological models of similar regions

Abstract Changes in Canadian Prairie streamflow, particularly trends over time, have not been well studied but are particularly relevant for food and water security in this vast agricultural region. Streamflow records for this region are often unsuitable for conventional trend analysis; streams are often intermittent and have only a few days per year with flow, and stations operate only during the warm season, because of a lack of flow during the very cold Prairie winter. This study takes an alternative approach; streamflow data for the period from March to October for individual years between 1910 and 2015 from 169 hydrometric stations from the Prairie and adjacent areas in Canada were converted to annual cumulative runoff series. These 5895 individual station-years were then clustered based upon their shape, using dynamic time warping. Three clusters of cumulative annual runoff were found; the first and most common type has infrequent days with flow and low total annual runoff [0–50 mm], the second has more days with flow and slightly greater runoff [48–175 mm], and the least common third type has the fewest days without flow, includes perennial streams, and has much greater annual runoff [>173 mm]. For each hydrometric station a time series of annual cluster memberships was created. Trends in the fractions of cluster types were determined using logistic regression, with spatial groupings of these time series over five-year periods. Trends in the fractions of types within an ecoregion indicate spatially consistent and organized changes in the pattern of runoff over the region. In the western Canadian Prairies, particularly in the Mixed Grassland and Cypress Upland ecoregions, drying is occurring, as indicated by the increased frequency of the dry type. In the northern and eastern Canadian Prairies, conditions are shifting to greater runoffs, particularly in the Aspen Parkland, where the wet types are increasing in frequency.

Abstract. Classification and clustering approaches provide a means to group watersheds according to similar attributes, functions, or behaviours, and can aid in managing natural resources within these regions. While widely used, approaches based on hydrological response parameters restrict analyses to regions where well-developed hydrological records exist, and overlook factors contributing to other management concerns, including biogeochemistry and ecology. In the Canadian Prairie, hydrometric gauging is sparse and often seasonal, large areas are endorheic and the landscape is highly modified by human activity, complicating classification based solely on hydrological parameters. We compiled climate, geological, topographical, and land cover data from the Prairie and conducted a classification of watersheds using a hierarchical clustering of principal components. Seven classes were identified based on the clustering of watersheds, including those distinguishing southern Manitoba, the pothole region, river valleys, and grasslands. Important defining variables were climate, elevation, surficial geology, wetland distribution, and land cover. In particular, three classes occur almost exclusively within regions that tend not to contribute to major river systems, and collectively encompass the majority of the study area. The gross difference in key characteristics across the classes suggests that future water management and climate change may carry with them heterogeneous sets of implications for water security across the Prairies. This emphasizes the importance of developing management strategies that target sub-regions expected to behave coherently as current human-induced changes to the landscape will affect how watersheds react to change. This study provides the first classification of watersheds within the Prairie based on climatic and biophysical attributes, and our findings provide a foundation for addressing questions related to hydrological, biogeochemical, and ecological behaviours at a regional level.

Abstract. Classification and clustering approaches provide a means to group watersheds according to similar attributes, functions, or behaviours, and can aid in managing natural resources. Although they are widely used, approaches based on hydrological response parameters restrict analyses to regions where well-developed hydrological records exist, and overlook factors contributing to other management concerns, including biogeochemistry and ecology. In the Canadian Prairie, hydrometric gauging is sparse and often seasonal. Moreover, large areas are endorheic and the landscape is highly modified by human activity, complicating classification based solely on hydrological parameters. We compiled climate, geological, topographical, and land-cover data from the Prairie and conducted a classification of watersheds using a hierarchical clustering of principal components. Seven classes were identified based on the clustering of watersheds, including those distinguishing southern Manitoba, the pothole region, river valleys, and grasslands. Important defining variables were climate, elevation, surficial geology, wetland distribution, and land cover. In particular, three classes occur almost exclusively within regions that tend not to contribute to major river systems, and collectively encompass the majority of the study area. The gross difference in key characteristics across the classes suggests that future water management and climate change may carry with them heterogeneous sets of implications for water security across the Prairie. This emphasizes the importance of developing management strategies that target sub-regions expected to behave coherently as current human-induced changes to the landscape will affect how watersheds react to change. The study provides the first classification of watersheds within the Prairie based on climatic and biophysical attributes, with the framework used being applicable to other regions where hydrometric data are sparse. Our findings provide a foundation for addressing questions related to hydrological, biogeochemical, and ecological behaviours at a regional level, enhancing the capacity to address issues of water security.

AbstractIn cold conditions, early winter precipitation occurs as snowfall and contributes to the accumulating seasonal snowpack. In a warming climate, precipitation may occur as rainfall in mountai...