This study integrated a water isotope module into the hydrological model THREW (Tsinghua Representative Elementary Watershed) which has been successfully used in high and cold regions. Signatures of oxygen stable isotope (¹⁸O) of different water inputs and stores were simulated coupling with the simulations of runoff generation. Isotope measurements of precipitation water samples and assumed constant isotope signature of ice meltwater were used to force the isotope module. Isotope signatures of water stores such as snowpack and subsurface water were updated by an assumed completely mixing procedure. Fractionation effects of snowmelt and evapotranspiration were modeled in a Rayleigh fractionation approach. The isotope-aided model was subsequently applied for the quantification of runoff components and estimations of mean water travel time (MTT) and mean residence time (MRT) in the glacierized watershed of Karuxung river on the Tibetan Plateau. Model parameters were calibrated by three variants with different combinations of streamflow, snow cover area and isotopic composition of stream water. Modeled MTT and MRT were validated by estimates of a tracer-based sine-wave method. Results indicate that (1) the proposed model performs well on simultaneously reproducing the observations of streamflow, snow cover area and isotopic composition of stream water, despite the fact that only precipitation water samples were available for tracer input; (2) isotope data facilitate more robust estimations on contributions of runoff components (CRCs) to streamflow in the melting season, as well as on MTT and MRT; (3) involving isotope data for the model calibration obviously reduces uncertainties in the quantification of CRCs and estimations of MTT and MRT, through better constraining the competitions among different runoff processes induced by meltwater and rainfall. Our results inform scientists on the high value of water isotope data for improving process understanding in a glacierized basin on the Tibetan Plateau.

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 km², 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.

Precipitation is one of the most important input to hydrological models, although obtaining sufficient precipitation observations and accurate precipitation estimates in High Mountain Asia (HMA) is challenging. ERA5 precipitation is the latest generation of reanalysis dataset that is attracting huge attention from various fields but it has not been evaluated in hydrological simulations in HMA. To remedy this gap, we first statistically evaluated ERA5 precipitation with observations from 584 gauges in HMA, and then investigated its potential in hydrological simulation in 11 HMA basins using the Variable Infiltration Capacity (VIC) hydrological model. The ERA5 precipitation generally captures the seasonal variations of gauge observations, and the broad spatial distributions of precipitation in both magnitude and trends in HMA. The ERA5 exhibits a reasonable flow simulation (RB of 5%–10%) at the Besham hydrological station of the upper Indus (UI) basin when the contribution from glacier runoff is added to the simulated total runoff. But it overestimates the observations in other HMA basins by 33%–106% without considering glacier runoff, mostly due to the overestimates in the ERA5 precipitation inputs. Therefore, a bias correction is definitely needed before ERA5 precipitation is used for hydrological simulations in HMA basins.

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.

Tracer-aided hydrological models integrating water isotope modules into the simulation of runoff generation are useful tools to reduce uncertainty of hydrological modeling in cold basins that are featured by complex runoff processes and multiple runoff components. However, there is little guidance on the strategy of field water sampling for isotope analysis to run tracer-aided hydrological models, which is especially important for large mountainous basins on the Tibetan Plateau (TP) where field water sampling work is highly costly. This study conducted a set of numerical experiments based on the THREW-T (Tsinghua Representative Elementary Watershed - Tracer-aided version) model to evaluate the reliance of the tracer-aided modeling performance on the availability of site measurements of water isotope in the Yarlung Tsangpo river (YTR) basin on the TP. Data conditions considered in the numerical experiments included the availability of glacier meltwater isotope measurement, quantity of site measurements of precipitation isotope, and the variable collecting strategies for stream water samples. Our results suggested that (1) in high-mountain basins where glacier meltwater samples for isotope analysis are not available, estimating glacier meltwater isotope by an offset parameter from the precipitation isotope is a feasible way to force the tracer-aided hydrological model. Using a set of glacier meltwater δ¹⁸O that were 2 ‰–9 ‰ lower than the mean precipitation δ¹⁸O resulted in only small changes in the model performance and the quantifications of contributions of runoff components (CRCs, smaller than 5 %) to streamflow in the YTR basin. (2) The strategy of field sampling for site precipitation to correct the global gridded isotope product of isoGSM (isotope-incorporated global spectral model) for model forcing should be carefully designed. Collecting precipitation samples at sites falling in the same altitude tends to be worse at representing the ground pattern of precipitation δ¹⁸O over the basin than collecting precipitation samples from sites in a range of altitudes. (3) Collecting weekly stream water samples at multiple sites in the wet and warm seasons is the optimal strategy for calibrating and evaluating a tracer-aided hydrological model in the YTR basin. It is highly recommended to increase the number of stream water sampling sites rather than spending resources on extensive sampling of stream water at a sole site for multiple years. These results provide important implications for collecting site measurements of water isotopes for running tracer-aided hydrological models to improve quantifications of CRCs in high-mountain basins.