The Soil and Water Assessment Tool (SWAT) model was configured to simulate streamflow under data scarcity scenario for a snow-dominated, forested, mountainous Mago River basin located in the Eastern Himalayan region of India. To account for the role played by snowmelt dynamics on streamflow and its influence on water balance components of the basin, two separate projects were set up: a Reference project in which only hydrological parameters related to streamflow were considered without regard to snow-related parameters, elevation bands, and associated lapse rates and another project referred to as Elevation Band project in which 10 elevation bands were set up for six snow-dominated headwater sub-basins. Sensitivity analysis and calibration was performed using SWAT Calibration Uncertainty Programs/Sequential Uncertainty Fitting 2 for both the projects. The result of the sensitivity analysis showed that curve number (CN 2) was found to be most sensitive. The comparison between the two calibrated projects revealed that inclusion of snow-related parameters, elevation bands, and the associated lapse rates in the snow-dominated headwater catchments improved the hydrological simulation performance and this improvement propagated downstream towards the outlet of the basin. This enhancement highlighted the ability of SWAT to capture the snowmelt dynamics prevailing in the Eastern Himalayan region. Analysis of the water balance components showed that water yield and percolation increased, while evapotranspiration decreased under the effect of snow cover. The contribution of snowmelt runoff to the annual streamflow of the basin was about 8%, and the maximum contribution was made during the pre-monsoon period. This study also highlighted the importance of the presence of snow cover to sustain the ecosystem of the region.

The SWAT model was applied successfully in an Eastern Himalayan river basin. The role of snow dynamics in the hydrology of the watershed was investigated and it was found that the contribution of snowmelt water to the total water yield of the basin was very significant particularly during lean season for the sustenance of the regional ecosystem

土壤和水评估工具（SWAT）模型被配置为在位于印度东部喜马拉雅地区的雪域为主，森林茂密的山区Mago河盆地中，在数据稀缺情况下模拟水流。为了说明融雪动力学对河流流量及其对流域水平衡成分的影响，建立了两个独立的项目：一个参考项目，其中仅考虑与河流流量有关的水文参数，而不考虑与雪有关的参数，高程带和相关的流失率，以及另一个称为高程带项目，其中为六个以雪为主的上游流域建立了10个高程带。对于两个项目，都使用SWAT校准不确定度程序/顺序不确定度拟合2进行了灵敏度分析和校准。灵敏度分析的结果表明，曲线编号（CN 2）最敏感。两个校准项目之间的比较表明，在以雪为主的源头集水区中包含与雪有关的参数，海拔带和相关的流失率，改善了水文模拟性能，并且这种改善向下游流向盆地出口。这种增强突出了特警队捕捉东部喜马拉雅山地区普遍存在的融雪动态的能力。对水平衡成分的分析表明，在积雪的影响下，水的产量和渗透增加，而蒸散量减少。融雪径流对流域年流量的贡献约为8％，最大贡献发生在季风前期。这项研究还强调了积雪对维持该地区生态系统的重要性。

SWAT模型已在喜马拉雅东部流域成功应用。研究了雪动力学在流域水文学中的作用，发现融雪水对流域总水量的贡献非常显着，特别是在淡季期间，对于区域生态系统的维持