Quantifying the impact of climate change on hydrologic features is essential for the scientific planning, management and sustainable use of water resources in Northwest China. Based on hydrometeorological data and glacier inventory data, the Spatial Processes in Hydrology (SPHY) model was used to simulate the changes of hydrologic processes in the Upper Shule River (USR) from 1971 to 2020, and variations of runoff and runoff components were quantitatively analyzed using the simulations and observations. The results showed that the glacier area has decreased by 21.8% with a reduction rate of 2.06 km(2)/a. Significant increasing trends in rainfall runoff, glacier runoff (GR) and baseflow indicate there has been a consistent increase in total runoff due to increasing rainfall and glacier melting. The baseflow has made the largest contribution to total runoff, followed by GR, rainfall runoff and snow runoff, with mean annual contributions of 38%, 28%, 18% and 16%, respectively. The annual contribution of glacier and snow runoff to the total runoff shows a decreasing trend with decreasing glacier area and increasing temperature. Any increase of total runoff in the future will depend on an increase of rainfall, which will exacerbate the impact of drought and flood disasters.

In contrast to widespread glacier retreat evidenced globally, glaciers in the Karakoram region have exhibited positive mass balances and general glacier stability over the past decade. Snow and glacier meltwater from the Karakoram and the western Himalayas, which supplies the Indus River Basin, provide an essential source of water to more than 215 million people, either directly, as potable water, or indirectly, through hydroelectric generation and irrigation for crops. This study focuses on water resources in the Upper Indus Basin (UIB) which combines the ranges of the Hindukush, Karakoram and Himalaya (HKH). Specifically, we focus on the Gilgit River Basin (GRB) to inform more sustainable water use policy at the sub-basin scale. We employ two degree-day approaches, the Spatial Processes in Hydrology (SPHY) and Snowmelt Runoff Model (SRM), to simulate runoff in the GRB during 2001-2012. The performance of SRM was poor during July and August, the period when glacier melt contribution typically dominates runoff. Consequently, SPHY outperformed SRM, likely attributable to SPHY's ability to discriminate between glacier, snow, and rainfall contributions to runoff during the ablation period. The average simulated runoff revealed the prevalent snowmelt contribution as 62%, followed by the glacier melt 28% and rainfall 10% in GRB. We also assessed the potential impact of climate change on future water resources, based on two Representative Concentration Pathways (RCP) (RCP 4.5 and RCP 8.5). We estimate that summer flows are projected to increase by between 5.6% and 19.8% due to increased temperatures of between 0.7 and 2.6 degrees C over the period 2039-2070. If realized, increased summer flows in the region could prove beneficial for a range of sectors, but only over the short to medium term and if not associated with extreme events. Long-term projections indicate declining water resources in the region in terms of snow and glacier melt.

为深入研究高寒流域河川径流的水源解析，选取雅鲁藏布江帕隆藏布上游流域为研究区，采用月流量、遥感积雪面积数据、实测冰川径流数据等多目标率定方法，改进单一依靠流量数据率定模型的方法，基于SPHY(Spatial Processes in Hydrology)水文模型开展水文模拟及径流组分研究，提高了总体建模质量.结果表明：在率定期和验证期Nash-Sutcliffe效率系数分别为0.95和0.94，模型具有较好的适用性.降雨径流、融雪径流、冰川径流和基流作为径流来源，占总径流的比例分别为10%、25%、45%和20%，冰川径流和融雪径流是最重要的补给来源.月尺度上，冰川径流在7-8月占比最大，融雪径流在4-6月占比最大，降雨径流在各月占比最小.冰川径流占比最高，短期内可提供更多水资源保障社会经济发展，长期而言冰川径流将逐渐减少，造成水资源短缺.因此，当地需提高应对径流变化潜在风险的策略.

为深入研究高寒流域河川径流的水源解析，选取雅鲁藏布江帕隆藏布上游流域为研究区，采用月流量、遥感积雪面积数据、实测冰川径流数据等多目标率定方法，改进单一依靠流量数据率定模型的方法，基于SPHY(Spatial Processes in Hydrology)水文模型开展水文模拟及径流组分研究，提高了总体建模质量.结果表明：在率定期和验证期Nash-Sutcliffe效率系数分别为0.95和0.94，模型具有较好的适用性.降雨径流、融雪径流、冰川径流和基流作为径流来源，占总径流的比例分别为10%、25%、45%和20%，冰川径流和融雪径流是最重要的补给来源.月尺度上，冰川径流在7-8月占比最大，融雪径流在4-6月占比最大，降雨径流在各月占比最小.冰川径流占比最高，短期内可提供更多水资源保障社会经济发展，长期而言冰川径流将逐渐减少，造成水资源短缺.因此，当地需提高应对径流变化潜在风险的策略.

为深入研究高寒流域河川径流的水源解析，选取雅鲁藏布江帕隆藏布上游流域为研究区，采用月流量、遥感积雪面积数据、实测冰川径流数据等多目标率定方法，改进单一依靠流量数据率定模型的方法，基于SPHY(Spatial Processes in Hydrology)水文模型开展水文模拟及径流组分研究，提高了总体建模质量.结果表明：在率定期和验证期Nash-Sutcliffe效率系数分别为0.95和0.94，模型具有较好的适用性.降雨径流、融雪径流、冰川径流和基流作为径流来源，占总径流的比例分别为10%、25%、45%和20%，冰川径流和融雪径流是最重要的补给来源.月尺度上，冰川径流在7-8月占比最大，融雪径流在4-6月占比最大，降雨径流在各月占比最小.冰川径流占比最高，短期内可提供更多水资源保障社会经济发展，长期而言冰川径流将逐渐减少，造成水资源短缺.因此，当地需提高应对径流变化潜在风险的策略.