Spatially Distributed Snow and Glacier-melt Runoff Model (SDSGRM) was developed to evaluate the glacier-melt (GM), snowmelt (SM) and rainfall induced runoff contribution to the total stream runoff. It includes temperature index, radiation-temperature index, advection driven index and energy balance methods and generates gridded outputs. The model was successfully calibrated (NSE and R more than 0.7 and CRM between −0.06 and 0.1) for 2010–2013 and validated (NSE and R greater than 0.6 and CRM between 0.08 and 0.3) for 2014–2015 and 2017–2018 in glaciated Mago river basin of Arunachal Pradesh, Eastern Himalaya. The average runoff contribution was found out to be about 82% from rainfall, 11% from SM and 7% from GM. Considering the model's acceptable performance, any glaciated basin with a lack of data can benefit greatly from using SDSGRM to quantify runoff contributions as well as to determine the impact of climate change on hydrological system.

中文翻译：

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针对数据稀缺的高海拔河流流域开发空间分布的雪和冰川融化径流模型（SDSGRM）

空间分布的雪和冰川融化径流模型 (SDSGRM) 旨在评估冰川融化 (GM)、融雪 (SM) 和降雨引起的径流对总河流径流的贡献。它包括温度指数、辐射温度指数、平流驱动指数和能量平衡方法，并生成网格输出。该模型已在2010-2013年成功校准（NSE和R大于0.7，CRM在-0.06和0.1之间），并在2014-2015年和2017-2018年在冰川中进行了验证（NSE和R大于0.6，CRM在0.08和0.3之间）。喜马拉雅山东部阿鲁纳恰尔邦的马戈河流域。结果发现，平均径流贡献约为 82% 来自降雨，11% 来自 SM，7% 来自 GM。考虑到模型的可接受性能，任何缺乏数据的冰川盆地都可以从使用 SDSGRM 量化径流贡献以及确定气候变化对水文系统的影响中受益匪浅。