Alpine areas play a substantial role in supplying the world's water resources. The hydrological cycle in these areas has been experiencing notable alterations owing to climate change. However, the present comprehension of how water yield capacity (WYC) responds to climate change at varying elevations within alpine basins is impeded due to the complex terrain and simplified representation of coupled water-energy processes in traditional hydrological models. Through integrating the Weather Research and Forecasting hydrological modeling system (WRF-Hydro) and Budyko framework, this study quantitatively assessed the influence of climate change on WYC across different elevations in a Tibetan Plateau alpine basin, named Xiying River Basin (XRB). The results indicated the WRF-Hydro adeptly reproduced the streamflow and evapotranspiration (ET) within the XRB. The combination of the WRF-Hydro model allows the Budyko framework, traditionally limited to the watershed scale, to be applicable at the grid scale. We found that the XRB underwent substantial climate change from 1980 to 2015, and there existed an abrupt change in 1997. Climate change caused the WYC reduced by -17.06% during the post-1997 period (1998-2015), compared to the pre-1997 period (1980-1997). Additionally, all elevation bands displayed the WYC reductions, ranging from -3.69% to -24.31%, with diminishing magnitude at higher elevations. This WYC reduction is primarily attributed to an increase of 11.38% in ET. Although ET and precipitation increased with elevation, the former consistently exceeded the latter, resulting in decreasing water deficits and an altitudinal gradient of the WYC reduction. Besides the increasing vapor pressure deficit and decreasing albedo, our findings emphasized the significance of precipitation event timing in influencing WYC. The longer time intervals between precipitation events in the XRB led to more soil moisture loss through ET. These findings shed valuable implications for policymakers, offering guidance for the formulation of sustainable policies for water resource management and ecological conservation.

Water yield is a key ecosystem function index, directly impacting the sustainable development of the basin economy and ecosystem. Climate and land use/land cover (LULC) changes are the main driving factors affecting water yield. In the context of global climate change, assessing the impacts of climate and LULC changes on water yield in the alpine regions of the Qinghai-Tibet Plateau (QTP) is essential for formulating rational management and development strategies for water resources. On the basis of the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, we simulated and analyzed the spatiotemporal variations and the impacts of LULC and climate changes on water yield from 2001 to 2019 in the upstream regions of the Shule River Basin (USRB) on the northeastern margin of the QTP. Three scenarios were designed in the InVEST model to clearly analyze the contributions of climate and LULC changes on the variation of water yield. The first scenario integrated climate and LULC change into the model according to the actual conditions. The second scenario was simulation without LULC change, and the third scenario was without climate change. The results showed that (1) the InVEST model had a good performance in estimating water yield (coefficient of determination (R-2) = 0.986; root mean square error (RMSE) = 3.012, p < 0.05); (2) the water yield significantly increased in the temporal scale from 2001 to 2019, especially in the high altitude of the marginal regions (accounting for 32.01%), while the northwest regions significantly decreased and accounted for only 8.39% (p < 0.05); (3) the spatial distribution of water yield increased from the middle low-altitude regions to the marginal high-altitude regions; and (4) through the analysis of the three scenarios, the impact of climate change on water yield was 90.56%, while that of LULC change was only 9.44%. This study reveals that climate warming has a positive impact on water yield, which will provide valuable references for the integrated assessment and management of water resources in the Shule River Basin.

With climate warming, many regions are experiencing changes in snow accumulation and persistence. These changes are known to affect streamflow volume, but the magnitude of the effect varies between regions. This research evaluates whether variables derived from remotely sensed snow cover can be used to estimate annual streamflow at the small watershed scale across the western U.S., a region with a wide range of climate types. We compared snow cover variables derived from MODIS, snow persistence (SP), and snow season (SS), to more commonly utilized metrics, snow fraction (fraction of precipitation falling as snow, SF), and peak snow water equivalent (SWE). Each variable represents different information about snow, and this comparison assesses similarities and differences between the snow metrics. Next, we evaluated how two snow variables, SP and SWE, related to annual streamflow (Q) for 119 USGS reference watersheds and examined whether these relationships varied for wet/warm (precipitation surplus) and dry/cold (precipitation deficit) watersheds. Results showed high correlations between all snow variables, but the slopes of these relationships differed between climates, with wet/warm watersheds displaying lower SF and higher SWE for the same SP. In dry/cold watersheds, both SP and SNODAS SWE correlated with Q spatially across all watersheds and over time within individual watersheds. We conclude that SP can be used to map spatial patterns of annual streamflow generation in dry/cold parts of the region. Applying this approach to the Upper Colorado River Basin demonstrates that 50% of streamflow comes from areas >3,000 masl. If the relationship between SP and Q is similar in other dry/cold regions, this approach could be used to estimate annual streamflow in ungauged basins.