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The lower Athabasca River (Canada) has experienced notable declines in streamflow and increasing oil sands development since the 1970s. This study investigates the potential impacts of climate change on navigability using both observed historical and projected future flows derived via hydrological simulations driven by an ensemble of statistically downscaled general circulation model climate data. Our use of proposed indices that form the Aboriginal Navigation Index (ANI) and a new index based on percentage over threshold (POT) occurrences yielded novel insights into anticipated changes to the flow regime. Comparisons of near (2041–2070) and far (2071–2100) future periods with the historical baseline (1981–2010) yielded results that project significant reductions in the 500 m3 s−1 POT during the fall navigability period spanning weeks 34 to 43, as well as reductions in the integrated ANIFall. These results indicate that challenging navigational conditions may become more frequent in the second half of the 21st century, not only during this fall period but also earlier into the summer, due to a shift in the flow regime, with potentially severe impacts on the users of the river channels. Our assessment approach is transferable to other regional study areas and should be considered in water management and environmental flow frameworks. [ABSTRACT FROM AUTHOR]

Anthropogenic climate change--induced snowpack loss is affecting streamflow predictability, as it becomes less dependent on the initial snowpack conditions and more dependent on meteorological forecasts. We assess future changes to seasonal streamflow predictability over two large river basins, Liard and Athabasca in western Canada, by approximating streamflow response from the Variable Infiltration Capacity (VIC) hydrologic model with the Bayesian regularized neutral network (BRNN) machine learning emulator. We employ the BRNN emulator in a testbed ensemble streamflow prediction system by treating VIC-simulated snow water equivalent (SWE) as a known predictor and precipitation and temperature from GCMs as ensemble forecasts, thereby isolating the effect of SWE on streamflow predictability. We assess warm-season mean and maximum flow predictability over 2041--70 and 2071--2100 future periods against the1981--2010 historical period. The results indicate contrasting patterns of change, with the predictive skills for mean flow generally declining for the two basins, and marginally increasing or decreasing for the headwater subbasins. The predictive skill for maximum flow declines for the relatively warmer Athabasca basin and improves for the colder Liard basin and headwater subbasins. While the decreasing skill for the Athabasca is attributable to substantial loss in SWE, the improvement for the Liard and headwaters can be attributed to an earlier maximum flow timing that reduces the forecast horizon and offsets the effect of SWE loss. Overall, while the future change in SWE does affect the streamflow prediction skill, the loss of SWE alone is not a sufficient condition for the reduction in streamflow predictability. [ABSTRACT FROM AUTHOR]

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The article reports that western cordillera supplies freshwater across much of western Canada mainly through meltwater from snow and ice. Topics include the study incorporates existing information to synthesize and future freshwater supplies and demands across major north-, west-, and eastflowing sub-basins of the Canadian western cordillera, and the greatest and most widespread impact is the seasonality of streamflow has characterized by earlier spring freshets, and decreased summerflow.

River ice, like open-water conditions, is an integral component of the cold-climate hydrological cycle. The annual succession of river ice formation, growth, decay and clearance can include low flows and ice jams, as well as midwinter and spring break-up events. Reports and associated data of river ice occurrence are often limited to single locations or regional assessments, are season-specific, and use readily available data. 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 recorded variables from a subset 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, ice thickness, date, time and data quality rating. Guidelines on the data extraction, rating procedure and challenges are provided. At each location, time series of up to 15 variables specific to the occurrence of freeze-up and winter-low events, midwinter 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 10.18164/c21e1852-ba8e-44af-bc13-48eeedfcf2f4 (de Rham et al., 2020). [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM AUTHOR]

Land use/land cover change (LUCC) combined with gold mining activity (GMA) have reportedly affected the water quality of Amazonian rivers by intensifying surface soil erosion and increasing rivers' sediment concentration (SC). However, the role of LUCC on river siltation in comparison to that caused by GMA has not been assessed, and predictions of SC in the rivers accounting for future LUCC are scarce. This study applied a sediment modeling approach on Crepori Basin, located at eastern Amazon Basin, to simulate the impacts of past and future LUCC on SC in the river, comparing their impacts to those caused by GMA. Between 1973 and 2012, the expansion of deforested areas in the region had increased sheet erosion-driven SC in the river, especially during the high-water season, by up to 73.3%. LUCC projections for 2050 suggest future increases in sheet erosion-driven SC during the high-water season by more than three times of that caused by the land cover scenario of 1998–2012. Comparison between SC driven by sheet erosion to that caused by GMA has also shown that during the high-water and the low-water seasons, respectively, only about 14% and 6% of the total SC in the Crepori River resulted from laminar soil erosion, with the remaining proportion resulting from GMA. [ABSTRACT FROM AUTHOR]

ABSTRACT Precipitation, temperature, and evaporative demand are the most dominant factors affecting water availability in a region. This study examines projected changes in these hydro-climatic variables over western Canada under two greenhouse gas emissions scenarios using statistically downscaled, high resolution climate data generated by six Global Climate Models ( GCMs) from the latest Coupled Model Intercomparison Project ( CMIP5). Potential changes in the spatial and seasonal distributions of water availability over nine major western Canadian river basins are examined by computing the 3- and 12-month standardized precipitation and evapotranspiration indices ( SPEI-3 and SPEI-12). While individual GCM projections vary on the rate and seasonality of changes, they all indicate similar spatial and temporal patterns. The highest projected increases in precipitation and temperature are primarily in the northern basins, with some decreases in summer precipitation in the southern basins. The evolution of the SPEI-12 values for the southern basins such as Columbia, Saskatchewan, Fraser and Athabasca indicate a gradual increase in the magnitude and duration of water deficit, while the reverse was found for most of the northern basins such as Peel/Lower Mackenzie, Liard, and Northern Pacific that show a gradual increase in water surplus on an annual basis. The SPEI-3, however, shows that almost all river basins in western Canada, with the exception of Peel/Lower Mackenzie that are located in the extreme north of the study region, are projected to experience decreasing water availability in summer. In general, the study highlights the potential changes in the spatial and seasonal distribution of western Canadian water resources and sets the stage for a more detailed and process based hydro-climate modelling study to be conducted in the region. [ABSTRACT FROM AUTHOR]

Purpose: The transport of fine sediments and associated chemical constituents originating from potential anthropogenic and natural sources is becoming an issue of increasing importance in the Lower Athabasca River (LAR) ecosystem in northern Alberta, Canada. This study aims to (1) establish an integrated numerical modelling framework to investigate the transport of fine cohesive sediments and associated chemical constituents during both ice-covered and open-water periods and (2) apply the modelling framework to investigate the state and temporal/spatial variation in sediment and selected chemical constituents within the LAR. Materials and methods: One-dimensional hydrodynamic and transport models, combined with a river ice model, are used to predict the flow characteristics, transport of sediments and a selection of three metals and three polycyclic aromatic hydrocarbons (PAHs) within a ∼200 km reach of the LAR, both in open-water and ice-covered conditions. The models are validated using available field measurements and are applied to investigate the state and variation of sediment and chemicals for a baseline period as well as to assess the effect of various hypothetical pollution scenarios. Results and discussion: The model simulations successfully reproduce the hydrodynamics and sediment transport patterns as well as the state and variation of selected metal and PAH constituents. The results generally show that the concentration of chemical constituents in the bed sediment is the major factor in determining the state and variation of their concentration in the water column, and the high-flow season is the critical period for the transport of sediment and chemicals in the system. The scenario simulation results indicate that increases in the concentrations of chemical constituents in tributary streams have to be orders of magnitude higher to have a noticeable effect on their corresponding water column concentration in the LAR. Those effects are also found to be higher only within the immediate vicinity of the tributary confluences and gradually diminish with distance downstream of the confluences. Conclusions: The numerical modelling framework developed in this study provides a tool for investigation and understanding of the state and temporal/spatial variation of sediment and associated chemical constituents within cold region rivers such as the LAR. By conducting additional scenario-based studies (such as future climate and chemicals loading), the models can be used to identify possible future states of sediment and water quality constituents in the LAR ecosystem. [ABSTRACT FROM AUTHOR]

Flows and transport of sediment and associated chemical constituents within the lower reaches of the Athabasca River between Fort McMurray and Embarrass Airport are investigated using a two-dimensional (2D) numerical model called Environmental Fluid Dynamics Code (EFDC). The river reach is characterized by complex geometry, including vegetated islands, alternating sand bars and an unpredictable thalweg. The models were setup and validated using available observed data in the region before using them to estimate the levels of cohesive sediment and a select set of chemical constituents, consisting of polycyclic aromatic hydrocarbons (PAHs) and metals, within the river system. Different flow scenarios were considered, and the results show that a large proportion of the cohesive sediment that gets deposited within the study domain originates from the main stem upstream inflow boundary, although Ells River may also contribute substantially during peak flow events. The floodplain, back channels and islands in the river system are found to be the major areas of concern for deposition of sediment and associated chemical constituents. Adsorbed chemical constituents also tend to be greater in the main channel water column, which has higher levels of total suspended sediments, compared to in the flood plain. Moreover, the levels of chemical constituents leaving the river system are found to depend very much on the corresponding river bed concentration levels, resulting in higher outflows with increases in their concentration in the bed sediment. [ABSTRACT FROM AUTHOR]

Several different gridded climate data sets have recently been made available with the purpose of providing a consistent set of climatic data for many hydro-climatic studies. Recent advances in land-surface schemes and their implementation in fully distributed processes-based hydrologic models have demanded even higher-resolution gridded data. It remains, however, a challenge to identify the most reliable gridded climate data for hydrologic modelling, especially in mountainous headwater regions where there is significant spatial variability but few observing stations. Moreover, the accuracy of such climate forcing data applied to alpine headwaters directly affects the modelled hydrologic responses of the lower, downstream portions of river basins. This study evaluates the spatial and temporal differences in precipitation and temperature fields among three high-resolution climate data sets available in Canada, namely, the North American Regional Reanalysis, the Canadian Precipitation Analysis and the thin-plate smoothing splines (ANUSPLIN). Inter-comparison of the quality of these data sets was undertaken for the Athabasca River basin in western Canada. The hydrologic responses of this watershed with respect to each of the three gridded climate data sets were also evaluated using the Variable Infiltration Capacity model. Results indicate that the data sets have systematic differences, which vary with regional characteristics - the largest differences being for mountainous regions. The hydrologic model simulations corresponding to those three forcing data sets also show significant differences and more with North American Regional Reanalysis than those between Canadian Precipitation Analysis and ANUSPLIN. © 2014 Her Majesty the Queen in Right of Canada. Hydrological Processes © 2014 John Wiley & Sons Ltd. [ABSTRACT FROM AUTHOR]

Freshwater ice plays an important role in physical, biological, and chemical processes affecting cold-region lakes. To examine the potential magnitude of climate-change-related impacts in ice-cover characteristics, particularly its formation, duration, breakup, thickness, and structural composition over North America, this study employs a one-dimensional, process-based, lake simulation model, 'MyLake' (Multi-year simulation model for Lake thermo- and phytoplankton dynamics). The model is first calibrated and validated for Baker Lake, Nunavut, Canada, and then used to simulate patterns of ice conditions using a set of hypothetical lakes of varying depth (5, 20, and 40 m) located at a 2° latitude/longitude grid pattern for the major cold-region portion of North America between 40 and 75° latitude. The model is driven by gridded atmospheric forcing data from the North American Regional Reanalysis (NARR) and the Canadian Regional Climate Model (CRCM) with projections of future climate corresponding to the SRES A2 emissions scenario. The NARR-based simulation results for the period 1979-2006 are consistent with observations of lake-ice thickness and phenology obtained from the Canadian Ice Database. The CRCM-based lake-ice simulation results for the baseline (1961-1990) and future (2041-2070) time periods indicate that projected air-temperature warming will advance break-up by 10-20 days and delay freeze-up by 5-15 days, thereby reducing lake-ice duration by about 15-35 days. Lake depth is also found to have significant influence on lake-ice freeze-up dates and maximum thicknesses but not on the break-up dates. Such changes are accompanied by a reduction in ice thickness of 10-30 cm. Cover composition is also altered as a result of changes in ice thickness and snow loading resulting in somewhat greater thicknesses of white-ice (1-5 cm) over most areas except towards the east and west coasts, as well as more southerly latitudes where it slightly decreased. Implications of such cover changes are also discussed. Copyright © 2011 Royal Meteorological Society and Crown in the right of Canada. [ABSTRACT FROM AUTHOR]

Shrestha, Rajesh R., Yonas B. Dibike, and Terry D. Prowse, 2011. Modeling Climate Change Impacts on Hydrology and Nutrient Loading in the Upper Assiniboine Catchment. Journal of the American Water Resources Association (JAWRA) 48(1): 74-89. DOI: 10.1111/j.1752-1688.2011.00592.x Abstract: This paper presents a modeling study on climate-induced changes in hydrologic and nutrient fluxes in the Upper Assiniboine catchment, located in the Lake Winnipeg watershed. The hydrologic and agricultural chemical yield model, Soil and Water Assessment Tool (SWAT) was employed to model a 21-year baseline (1980-2000) and future (2042-2062) periods with model forcings for future climates derived from three regional climate models (RCMs) and their ensemble means. The modeled future scenarios reveal that potential future changes in the climatic regime are likely to modify considerably hydrologic and nutrient fluxes. The effects of future changes in climatic variables, especially precipitation and temperature, are clearly evident in the resulting snowmelt and runoff regimes. The future hydrologic scenarios consistently show earlier onsets of spring snowmelt and discharge peaks, and higher total runoff volumes. The simulated nutrient loads closely match the dynamics of the future runoff for both nitrogen and phosphorus, in terms of earlier timing of peak loads and higher total loads. However, nutrient concentrations could decrease due to the higher rate of runoff increase. Overall, the effects of these changes on the nutrient transport regime need to be considered together with possible future changes in land use, crop type, fertilizer application, and transformation processes in the receiving water bodies. [ABSTRACT FROM AUTHOR]

The formation and break-up of ice-cover are important seasonal events in mid- to high-latitude cold-region lakes. There is increasing concern regarding how climate change will affect lake-water thermal structure and lake-ice characteristics, particularly ice formation, duration, break-up, thickness, and composition. This study employs a one-dimensional process-based multi-year lake ice model, MyLake, to simulate the evolution of the Northern Hemisphere lake-ice and thermal structure patterns under a changing climate. After testing the model on Baker Lake located in Nunavut Canada, large-scale simulations were conducted over the major land masses of the Northern Hemisphere subarctic regions between 40° and 75°N using hypothetical lakes positioned at 2·5° latitude and longitude resolution. For the baseline period of 1960-1999, the lake-ice model was driven by gridded atmospheric forcings from the ERA-40 global reanalysis data set while atmospheric model forcings corresponding to future (2040-2079) climate were obtained by modifying the ERA-40 data according to the Canadian Global Climate Model projection based on the SRES A2 emissions scenario. Analysis of the modelling results indicates that lake-ice freeze-up timing will be delayed by 5-20 days and break-up will be advanced by approximately 10-30 days, thereby resulting in an overall decrease in lake-ice duration by about 15-50 days. Maximum lake-ice thickness will also be reduced by 10-50 cm. The change in maximum snow depth on the lake-ice ranges between − 15 to + 5 cm, while the change in white-ice thickness ranges between − 20 to + 10 cm depending on the geographic location and other climate parameters. The future warming will also result in an overall increase in lake-water temperature, with summer stratification starting earlier and extending later into the year. Copyright © 2011 Crown in the right of Canada. Published by John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Climate change impact studies have generally downscaled large-scale global climate model (GCM) output data; however, few studies have considered downscaling regional climate model (RCM) data. It is unclear whether further downscaling raw RCM data could be beneficial or not in a hydrologic impact study. This study provides some experimental results to address that question. Raw Canadian regional climate model (CRCM4.2) data are downscaled by using a common statistical downscaling method (SDSM) and a data-driven technique called a time-lagged feedforward network (TLFN). Regardless of the downscaling methods and the predictands (e.g., precipitation, temperature), the downscaled CRCM4.2 data are found to be much closer to the observed data than the raw CRCM4.2 data. When the downscaled CRCM4.2 data are used in a hydrologic model (HBV), the model's ability to accurately simulate streamflow and reservoir inflow is significantly improved as compared to the use of the raw CRCM4.2 data. Simulations of future river flow and reservoir inflow reveal that the general patterns of changes in future flow are quite similar whether downscaled or raw CRCM4.2 data are used. However, the use of downscaled CRCM4.2 data seems to provide more consistent predictions of the magnitude and timing of changes. It appears that the RCM may still suffer from the bias problem inherent to the parent GCM. Further downscaling raw RCM data permits bias correction, improves hydrologic modeling, and provides more consistent changes (magnitude and timing) of future flows. [ABSTRACT FROM AUTHOR]

The article discusses the difficulties associated with downscaling meteorological data in order to model climate changes. Simulations involving the WatFlood and HBV-96 models are discussed and the outcomes of simulations of the the Saguenay watershed, located in Quebec, Canada, are described. Data that was downscaled using the Statistical Down-Scaling Model (SDSM), a regression-based method, produced variations in the predictive power of the two models. The significance of such variations for attempts to accurately estimate the hydrological effects of climate change are discussed.

Three downscaling models, namely the Statistical Down-Scaling Model (SDSM), the Long Ashton Research Station Weather Generator (LARS-WG) model and an artificial neural network (ANN) model, have been compared in terms of various uncertainty attributes exhibited in their downscaled results of daily precipitation, daily maximum and minimum temperature. The uncertainty attributes are described by the model errors and the 95% confidence intervals in the estimates of means and variances of downscaled data. The significance of those errors has been examined by suitable statistical tests at the 95% confidence level. The 95% confidence intervals in the estimates of means and variances of downscaled data have been estimated using the bootstrapping method and compared with the observed data. The study has been carried Out using 40 years of observed and downscaled daily precipitation data and daily maximum and minimum temperature data, starting from 1961 to 2000. In all the downscaling experiments, the simulated predictors of the Canadian Global Climate Model (CGCM1) have been used. The uncertainty assessment results indicate that, in daily precipitation downscaling, the LARS-WG model errors are significant at the 95% confidence level only in a very few months, the SDSM errors are significant in some months, and the ANN model errors are significant in almost all months of the year. In downscaling daily maximum and minimum temperature, the performance of all three models is similar in terms of model errors evaluation at the 95% confidence level. But, according to the evaluation of variability and uncertainty in the estimates of means and variances of downscaled precipitation and temperature, the performances of the LARS-WG model and the SDSM are almost similar, whereas the ANN model performance is found to be poor in that consideration. Further assessment of those models, in terms of skewness and average dry-spell length comparison between observed and downscaled daily precipitation, indicates that the downscaled daily precipitation skewness and average dry-spell lengths of the LARS-WG model and the SDSM are closer to the observed data, whereas the ANN model downscaled precipitation underestimated those statistics in all months. [ABSTRACT FROM AUTHOR]

The issues of downscaling the outputs of a global climate model (GCM) to a scale that is appropriate to hydrological impact studies are investigated using a temporal neural network approach. The time-lagged feed-forward neural network (TLFN) is proposed for downscaling daily total precipitation and daily maximum and minimum temperature series for the Serpent River watershed in northern Quebec (Canada). The downscaling models are developed and validated using large-scale predictor variables derived from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis dataset. Atmospheric predictors such as specific humidity, wind velocity, and geopotential height are identified as the most relevant inputs to the downscaling models. The performance of the TLFN downscaling model is also compared to a statistical downscaling model (SDSM). The downscaling results suggest that the TLFN is an efficient method for downscaling both daily precipitation and temperature series. The best downscaling models were then applied to the outputs of the Canadian Global Climate Model (CGCM1), forced with the Intergovernmental Panel on Climate Change (IPCC) IS92a scenario. Changes in average precipitation between the current and the future scenarios predicted by the TLFN are generally found to be smaller than those predicted by the SDSM model. Furthermore, application of the downscaled data for hydrologic impact analysis in the Serpent River resulted in an overall increasing trend in mean annual flow as well as earlier spring peak flow. The results also demonstrate the emphasis that should be given in identifying the appropriate downscaling tools for impact studies by showing how a future climate scenario downscaled with different downscaling methods could result in significantly different hydrologic impact simulation results for the same watershed. [ABSTRACT FROM AUTHOR]

Recent developments in the field of computational intelligence (CI) techniques are helping to solve various problems of water resources modeling and management. These techniques have also shown their potential as an alternative approach to conventional controllers. In this paper, artificial neural networks (ANN) and fuzzy systems (FS) are shown to be efficient alternatives to using optimal control algorithms in real-time control of the polder water system of Overwaard in The Netherlands. The relation between the optimal decision or action and the influencing parameters are learned by ANN and FS and then used to derive the decisions and control actions in real-time. It was possible to reproduce the centralized behavior (in terms of water levels and corresponding discharges) of optimal control action by using easily measurable local information. Moreover, it is demonstrated that model simulation with external intelligent controllers is ten times faster than that with the optimal control. [ABSTRACT FROM AUTHOR]

Presents a study which investigated the possibility of using a machine learning paradigm based on the theory of statistical learning, namely that of the support vector machine (SVM). Basic ideas underlying statistical learning theory and SVM; Potential of the SVM for feature classification and multiple regression problems; Analysis of the performance of the SVM.

The important aspect of changing hydro-climatic extremes is addressed in studies examining projected changes to flood-generating mechanisms associated with snowmelt across Canada, and historical and projected changes to severe Canadian Prairie droughts. The earth has vast amounts of surface and sub-surface freshwater in the form of lakes, reservoirs, rivers, wetlands, soil water, groundwater, as well as water stored in snowpacks, glaciers, and permafrost. Hydro-climatic extremes such as floods and droughts have significant impacts on freshwater availability and are projected to increase in frequency as the result of climate change. Summary of This Special Issue This special issue includes two invited critical reviews related to hydro-climatic processes associated with freshwater availability. [Extracted from the article]

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]

The rising global temperature is shifting the runoff patterns of snowmelt-dominated alpine watersheds, resulting in increased cold season flows, earlier spring peak flows, and reduced summer runoff. Projections of future runoff are beneficial in preparing for the anticipated changes in streamflow regimes. This study applied the degree–day Snowmelt Runoff Model (SRM) in combination with the MODIS to remotely sense snow cover observations for modeling the snowmelt runoff response of the Upper Athabasca River Basin in western Canada. After assessing its ability to simulate the observed historical flows, the SRM was applied for projecting future runoff in the basin. The inclusion of a spatial and temporal variation in the degree–day factor (DDF) and separation of the DDF for glaciated and non-glaciated areas were found to be important for improved simulation of varying snow conditions over multiple years. The SRM simulations, driven by an ensemble of six statistically downscaled GCM runs under the RCP8.5 scenario for the future period (2070–2080), show a consistent pattern in projected runoff change, with substantial increases in May runoff, smaller increases over the winter months, and decreased runoff in the summer months (June–August). Despite the SRM's relative simplicity and requirement of only a few input variables, the model performed well in simulating historical flows, and provides runoff projections consistent with historical trends and previous modeling studies. [ABSTRACT FROM AUTHOR]

Climatic change is affecting streamflow regimes of the permafrost region, altering mean and extreme streamflow conditions. In this study, we analyzed historical trends in annual mean flow (Qmean), minimum flow (Qmin), maximum flow (Qmax) and Qmax timing across 84 hydrometric stations in the permafrost region of Canada. Furthermore, we related streamflow trends with temperature and precipitation trends, and used a multiple linear regression (MLR) framework to evaluate climatic controls on streamflow components. The results revealed spatially varied trends across the region, with significantly increasing (at 10% level) Qmin for 43% of stations as the most prominent trend, and a relatively smaller number of stations with significant Qmean, Qmax and Qmax timing trends. Temperatures over both the cold and warm seasons showed significant warming for >70% of basin areas upstream of the hydrometric stations, while precipitation exhibited increases for >15% of the basins. Comparisons of the 1976 to 2005 basin-averaged climatological means of streamflow variables with precipitation and temperature revealed a positive correlation between Qmean and seasonal precipitation, and a negative correlation between Qmean and seasonal temperature. The basin-averaged streamflow, precipitation and temperature trends showed weak correlations that included a positive correlation between Qmin and October to March precipitation trends, and negative correlations of Qmax timing with October to March and April to September temperature trends. The MLR-based variable importance analysis revealed the dominant controls of precipitation on Qmean and Qmax, and temperature on Qmin. Overall, this study contributes towards an enhanced understanding of ongoing changes in streamflow regimes and their climatic controls across the Canadian permafrost region, which could be generalized for the broader pan-Arctic regions. [ABSTRACT FROM AUTHOR]

Spring freshet is the dominant annual discharge event in all major Arctic draining rivers with large contributions to freshwater inflow to the Arctic Ocean. Research has shown that the total freshwater influx to the Arctic Ocean has been increasing, while at the same time, the rate of change in the Arctic climate is significantly higher than in other parts of the globe. This study assesses the large-scale atmospheric and surface climatic conditions affecting the magnitude, timing and regional variability of the spring freshets by analyzing historic daily discharges from sub-basins within the four largest Arctic-draining watersheds (Mackenzie, Ob, Lena and Yenisei). Results reveal that climatic variations closely match the observed regional trends of increasing cold-season flows and earlier freshets. Flow regulation appears to suppress the effects of climatic drivers on freshet volume but does not have a significant impact on peak freshet magnitude or timing measures. Spring freshet characteristics are also influenced by El Niño-Southern Oscillation, the Pacific Decadal Oscillation, the Arctic Oscillation and the North Atlantic Oscillation, particularly in their positive phases. The majority of significant relationships are found in unregulated stations. This study provides a key insight into the climatic drivers of observed trends in freshet characteristics, whilst clarifying the effects of regulation versus climate at the sub-basin scale. [ABSTRACT FROM AUTHOR]

Runoff from Arctic rivers constitutes a major freshwater influx to the Arctic Ocean. In these nival-dominated river systems, the majority of annual discharge is released during the spring snowmelt period. The circulation regime of the salinity-stratified Arctic Ocean is connected to global earth–ocean dynamics through thermohaline circulation; hence, variability in freshwater input from the Arctic flowing rivers has important implications for the global climate system. Daily discharge data from each of the four largest Arctic-draining river watersheds (Mackenzie, Ob, Lena and Yenisei; herein referred to as MOLY) are analyzed to identify historic changes in the magnitude and timing of freshwater input to the Arctic Ocean with emphasis on the spring freshet. Results show that the total freshwater influx to the Arctic Ocean increased by 89 km3/decade, amounting to a 14% increase during the 30-year period from 1980 to 2009. A distinct shift towards earlier melt timing is also indicated by proportional increases in fall, winter and spring discharges (by 2.5%, 1.3% and 2.5% respectively) followed by a decrease (by 5.8%) in summer discharge as a percentage of the mean annual flow. This seasonal increase in discharge and earlier pulse onset dates indicates a general shift towards a flatter, broad-based hydrograph with earlier peak discharges. The study also reveals that the increasing trend in freshwater discharge to the Arctic Ocean is not solely due to increased spring freshet discharge, but is a combination of increases in all seasons except that of the summer. [ABSTRACT FROM AUTHOR]

The article which was recently published contained error. The second given names "Andrade" and "de Lucia" were captured as particles. Given in this article is the correct naming of authors. [ABSTRACT FROM AUTHOR]

Flows originating from alpine dominated cold region watersheds typically experience extended winter low flows followed by spring snowmelt and summer rainfall driven high flows. In a warmer climate, there will be a temperature-induced shift in precipitation from snowfall towards rain along with changes in precipitation intensity and snowmelt timing, resulting in alterations in the frequency and magnitude of peak flow events. This study examines the potential future changes in the frequency and severity of peak flow events in the Athabasca River watershed in Alberta, Canada. The analysis is based on simulated flow data by the variable infiltration capacity (VIC) hydrologic model driven by statistically downscaled climate change scenarios from the latest coupled model inter-comparison project (CMIP5). The hydrological model projections show an overall increase in mean annual streamflow in the watershed and a corresponding shift in the freshet timing to an earlier period. The river flow is projected to experience increases during the winter and spring seasons and decreases during the summer and early fall seasons, with an overall projected increase in peak flow, especially for low frequency events. Both stationary and non-stationary methods of peak flow analysis, performed at multiple points along the Athabasca River, show that projected changes in the 100-year peak flow event for the high emissions scenario by the 2080s range between 4% and 33% depending on the driving climate models and the statistical method of analysis. A closer examination of the results also reveals that the sensitivity of projected changes in peak flows to the statistical method of frequency analysis is relatively small compared to that resulting from inter-climate model variability. [ABSTRACT FROM AUTHOR]

Land cover changes (LCC) affect the water balance (WB), changing surface runoff (SurfQ), evapotranspiration (ET), groundwater (GW) regimes, and streamflow (Q). The Tapajós Basin (southeastern Amazon) has experienced LCC over the last 40 years, with increasing LCC rates projected for the near future. Several studies have addressed the effects of climate changes on the region’s hydrology, but few have explored the effects of LCC on its hydrological regime. In this study, the Soil and Water Assessment Tool (SWAT) was applied to model the LCC effects on the hydrology of the Upper Crepori River Basin (medium Tapajós Basin), using historical and projected LCC based on conservation policies (GOV_2050) and on the “Business as Usual” trend (BAU_2050). LCC that occurred from 1973 to 2012, increased Q by 2.5%, without noticeably altering the average annual WB. The future GOV_2050 and BAU_2050 scenarios increased SurfQ by 238.87% and 300.90%, and Q by 2.53% and 2.97%, respectively, and reduced GW by 4.00% and 5.21%, and ET by 2.07% and 2.43%, respectively. Results suggest that the increase in deforestation will intensify floods and low-flow events, and that the conservation policies considered in the GOV_2050 scenario may still compromise the region’s hydrology at a comparable level to that of the BAU_2050. [ABSTRACT FROM AUTHOR]