Snow and glacier melt are significant contributors to streamflow in Himalayan catchments, and their increasing contributions serve as key indicators of climate change. Consequently, the quantification of these streamflow components holds significant importance for effective water resource management. In this study, we utilized the spatio-temporal variability of isotopic signatures in stream water, rainfall, winter fresh snow, snowpack, glaciers, springs, and wells, in conjunction with hydrometeorological observations and Snow Cover Area (SCA) data, to identify water sources and develop a conceptual understanding of streamflow dynamics in three catchments (Lidder, Sindh, and Vishow) within the western Himalayas. The following results were obtained: (a) endmember contributions to the streamflow exhibit significant spatial and seasonal variability across the three catchments during 2018–2020; (b) snowmelt dominates streamflow, with average contributions across the entire catchment varying: 59% ± 9%, 55% ± 4%, 56% ± 6%, and 55% ± 9% in Lidder, 43% ± 6%, 38% ± 6%, 32% ± 4%, and 33% ± 5% in Sindh and 45% ± 8%, 40% ± 6%, 39% ± 6%, and 32% ± 5% in Vishow during spring, summer, autumn, and winter seasons, respectively; (c) glacier melt contributions can reach ~30% to streamflow near the source regions during peak summer; (d) The primary uncertainties in streamflow components are attributed to the spatiotemporal variability of tracer signatures of winter fresh snow/snowpack (±1.9% to ±20%); (e)regarding future streamflow components, if the glacier contribution were to disappear completely, the annual average streamflow in Lidder and Sindh could decrease up to ~20%. The depletion of the cryosphere in the region has led to a rapid increase in runoff (1980–1900), but it has also resulted in a significant streamflow reduction due to glacier mass loss and changes in peak streamflow over the past three decades (1990–2020). The findings highlight the significance of environmental isotope analysis, which provides insights into water resources and offers a critical indication of the streamflow response to glacier loss under a changing climate.

中文翻译：

---

通过基于多年示踪剂的水位线分离分析了解喜马拉雅山西部冰川流域的水文过程

积雪和冰川融化是喜马拉雅流域水流的重要贡献者，其日益增加的贡献成为气候变化的关键指标。因此，这些水流成分的量化对于有效的水资源管理具有重要意义。在这项研究中，我们利用溪流水、降雨、冬季新雪、积雪、冰川、泉水和水井中同位素特征的时空变化，结合水文气象观测和积雪面积 (SCA) 数据来识别水来源并发展了对喜马拉雅山西部三个流域（利德、信德和维秀）水流动力学的概念性理解。获得以下结果：(a) 2018-2020 年期间，三个流域的端元对径流的贡献表现出显着的空间和季节变化； (b) 融雪在水流中占主导地位，整个流域的平均贡献各不相同：59% ± 9%、55% ± 4%、56% ± 6%、Lidder 地区为 55% ± 9%、43% ± 6%、38春季、夏季期间，信德省为 % ± 6%、32% ± 4% 和 33% ± 5%，维秀省为 45% ± 8%、40% ± 6%、39% ± 6% 和 32% ± 5% ，分别为秋季和冬季； (c) 在夏季高峰期间，冰川融化对源区附近水流的贡献可达~30%； (d) 水流成分的主要不确定性归因于冬季新雪/积雪示踪剂特征的时空变化（±1.9%至±20%）； (e)关于未来的水流组成部分，如果冰川的贡献完全消失，利德省和信德省的年平均水流可能会减少约20%。该地区冰冻圈的消耗导致径流迅速增加（1980-1900年），但由于冰川质量损失和过去三十年（1990-1990年）峰值水流的变化，也导致水流显着减少。 2020）。这些发现凸显了环境同位素分析的重要性，它提供了对水资源的深入了解，并提供了气候变化下水流对冰川损失的响应的关键指示。