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This study evaluated the effects of climate perturbations on snowmelt, soil moisture, and streamflow generation in small Canadian Prairies basins using a modelling approach based on classification of basin biophysical characteristics. Seven basin classes that encompass the entirety of the Prairies Ecozone in Canada were determined by cluster analysis of these 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 Prairies Ecozone. Results indicated that snow accumulation in wetlands had a greater sensitivity to P and T than that in croplands and grasslands in all 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 Grasslands (See Fig. 1) 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 a P increase of 11 % in all 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 Prairies Ecozone. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Issues related to large uncertainty and parameter equifinality have posed big challenges for hydrological modeling in cold regions where runoff generation processes are particularly complicated. Tracer-aided hydrological models that integrate the transportation and fractionation processes of water stable isotope are increasingly used to constrain parameter uncertainty and refine the parameterizations of specific hydrological processes in cold regions. However, the common unavailability of site sampling of spatially distributed precipitation isotopes hampers the practical applications of tracer-aided models in large-scale catchments. This study, taking the precipitation isotope data (isotopes-incorporated global spectral model – isoGSM) derived from the isotopic general circulation models (iGCMs) as an example, explored its utility in driving a tracer-aided hydrological model in the Yarlung Tsangpo River basin (YTR; around 2×105 km 2 , with a mean elevation of 4875 m) on the Tibetan Plateau (TP). The isoGSM product was firstly corrected based on the biases between gridded precipitation isotope estimates and the limited site sampling measurements. Model simulations driven by the corrected isoGSM data were then compared with those forced by spatially interpolated precipitation isotopes from site sampling measurements. Our results indicated that (1) spatial precipitation isotopes derived from the isoGSM data helped to reduce modeling uncertainty and improve parameter identifiability in a large mountainous catchment on the TP, compared to a calibration method using discharge and snow cover area fraction without any information on water isotopes; (2) model parameters estimated by the corrected isoGSM data presented higher transferability to nested subbasins and produced higher model performance in the validation period than that estimated by the interpolated precipitation isotope data from site sampling measurements; (3) model calibration forced by the corrected isoGSM data successfully rejected parameter sets that overestimated glacier melt contribution and gave more reliable contributions of runoff components, indicating the corrected isoGSM data served as a better choice to provide informative spatial precipitation isotope than the interpolated data from site sampling measurements at the macro scale. This work suggested plausible utility of combining isoGSM data with measurements, even from a sparse sampling network, in improving hydrological modeling in large high mountain basins. [ABSTRACT FROM AUTHOR]

Tibetan Plateau (TP) is well known as Asia's water tower from where many large rivers originate. However, due to complex spatial variability in climate and topography, there is still a lack of a high-quality rainfall dataset for hydrological modeling and flood prediction. This study therefore aims to establish a high-accuracy daily rainfall product through merging rainfall estimates from three satellites, i.e., GPM-IMERG, GSMaP and CMORPH, based on a high-density rainfall gauge network. The new merged daily rainfall dataset with a spatial resolution of 0.1 ∘ focuses on warm seasons (10 June–31 October) from 2014 to 2019. Statistical evaluation indicated that the new dataset outperforms the raw satellite estimates, especially in terms of rainfall accumulation and the detection of ground-based rainfall events. Hydrological evaluation in the Yarlung Zangbo River basin demonstrated high performance of the merged rainfall dataset in providing accurate and robust forcings for streamflow simulations. The new rainfall dataset additionally shows superiority to several other products of similar types, including MSWEP and CHIRPS. This new rainfall dataset is publicly accessible at 10.11888/Hydro.tpdc.271303 (Li and Tian, 2021). [ABSTRACT FROM AUTHOR]

Tibetan Plateau (TP) is well known as the Asia’s water tower from where many large rivers originate. However, due to complex spatial variability of climate and topography, there is still a lack of high-quality rainfall dataset for hydrological modelling and flood prediction. This study, therefore, aims to establish a high-accuracy daily rainfall product through merging rainfall estimates from three satellites, i.e., GPM-IMERG, GSMaP, and CMORPH, based on the likelihood measurements of a high-density rainfall gauge network. The new merged daily rainfall dataset with a spatial resolution of 0.1°, focuses on warm seasons (June 10th-October 31st) from 2014 to 2019. Statistical evaluation indicated that the new dataset outperforms the raw satellite estimates, especially in terms of rainfall accumulation and the detection of ground-based rainfall events. Hydrological evaluation in the Yarlung Zangbo River Basin demonstrated high performance of the merged rainfall dataset in providing accurate and robust forcings for streamflow simulations. The new rainfall dataset additionally shows superiority to several other products of similar types, including MSWEP and CHIRPS. This new rainfall dataset is publicly accessible at https://doi.org/10.11888/Hydro.tpdc.271303 (Li et al.,2021). [ABSTRACT FROM AUTHOR]

Tracer data have been successfully used for hydrograph separation in glacierized basins. However, in these basins uncertainties of the hydrograph separation are large and are caused by the spatiotemporal variability in the tracer signatures of water sources, the uncertainty of water sampling, and the mixing model uncertainty. In this study, we used electrical conductivity (EC) measurements and two isotope signatures (δ 18O and δ 2H) to label the runoff components, including groundwater, snow and glacier meltwater, and rainfall, in a Central Asian glacierized basin. The contributions of runoff components (CRCs) to the total runoff and the corresponding uncertainty were quantified by two mixing approaches, namely a traditional end-member mixing approach (abbreviated as EMMA) and a Bayesian end-member mixing approach. The performance of the two mixing approaches was compared in three seasons that are distinguished as the cold season, snowmelt season, and glacier melt season. The results show the following points. (1) The Bayesian approach generally estimated smaller uncertainty ranges for the CRC when compared to the EMMA. (2) The Bayesian approach tended to be less sensitive to the sampling uncertainties of meltwater than the EMMA. (3) Ignoring the model uncertainty caused by the isotope fractionation likely led to an overestimated rainfall contribution and an underestimated meltwater share in the melt seasons. Our study provides the first comparison of the two end-member mixing approaches for hydrograph separation in glacierized basins and gives insight into the application of tracer-based mixing approaches in similar basins. [ABSTRACT FROM AUTHOR]

• Hydrological sensitivity to future climate change over the entire Canadian Southern Boreal Forest (SBF) was assessed by a virtual basin modelling approach. • The virtual basin hydrological models were forced by 4-km gridded convection-permitting Weather Research and Forecasting (WRF) outputs. • With future climate, the SBF would switch to a higher water yield region dominated by less predictable rainfall-triggered streamflow. • Spatially varied sensitivities in governing hydrological processes suggest that regional adaptation strategies corresponding to local climate change would be needed. This study develops a physically based hydrological process model using the Cold Region Hydrological Modelling (CRHM) platform to simulate the water budget storages and fluxes over the Canadian southern boreal forest (SBF). Evaluation of the CRHM-based model in a well-gauged SBF basin, White Gull Creek (WGC), Saskatchewan, Canada, indicated quite good performance in reproducing historical observations of streamflow, snow water equivalent (SWE), evapotranspiration (ET) and soil moisture without parameter calibration from streamflow. The entire SBF was then evenly divided into 2243 virtual basins, each of which was structured and parameterized with the same land cover, soil and hydrological parameters as the WGC basin, but with local latitude and topography in order to examine the sensitivity of governing hydrological processes to future climate variability and perturbation. Hydrological sensitivity in the virtual basins was assessed by examining the differences between hydrological simulations driven by 4-km gridded convection-permitting Weather Research and Forecasting (WRF) outputs in the current period (ctrl, 2001–2013) and a Pseudo Global Warming period (pgw, 2087–2099). The WRF simulation in the pgw period was forced by a perturbation of the same boundary conditions from ERA reanalysis data as for the ctrl period, and the perturbation was based on the ensemble-mean of projected changes from the CMIP5 RCP 8.5 emission scenario. Results showed that temperature would increase by 4.5℃ to 7℃ over the SBF but increases in annual precipitation of 15–24% would more than compensate for the effects of warming on runoff generation and result in greater streamflow volumes. Annual streamflow volumes would increase by 64 mm (35%) and 95 mm (16%) in the west and east, and by 48 mm (17%) in the central SBF. Annual snowfall and maximum SWE would decrease by 89–109 mm (∼29%) in the east, 3–8 mm (∼6%) in the west, and 31–50 mm (∼20%) in the central SBF. Annual mean soil moisture storage would decrease by 54–56 mm (27%) in the west and central, and by only 37 mm (14%) in the east SBF. Decreases in soil moisture would be caused by reduced soil freezing and enhanced thawing under future warming which would increase soil water loss from ET, subsurface runoff and percolation into groundwater storage. The larger sensitivity of streamflow and snow processes in the east SBF is partly due to the wetter climate and the larger increase in annual precipitation, the later also buffered the sensitivity of soil moisture to warming. These results show that the SBF would switch to a higher water yield region, dominated by rainfall-runoff fed streamflow over a longer snow-free season, and provide first-order guidance for sustainable water management of the SBF in the future. [ABSTRACT FROM AUTHOR]