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Assessing Suitability of Satellite Rainfall Data for Estimation of Daily Streamflows of a Small Tropical Catchment in India

机译:评估卫星降雨数据的适用性,以估算印度小型热带集水区的日常流出

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Reliable estimation of streamflow is crucial for developing effective water resources management strategies. However, there are several watersheds in India which are ungauged or contain inconsistent data archives for rainfall and discharge products, particularly for small watersheds at daily scale. This paper investigates the efficacy of the remote sensing rainfall products, precisely Tropical Rainfall Measuring Mission (TRMM) on daily scale over upper Tungabhadra sub-basin, a small tropical catchment in India. This precipitation dataset was corrected with in-situ rainfall data and used as a input to the physically based Variable Infiltration Capacity (VIC) hydrological model for estimation of streamflows. Streamflows generated with original TRMM rainfall data has resulted in larger difference in both the high and low streamflows when compared with observed discharge values, and resulted in high positive bias and low Nash-Sutcliffe efficiency (NSE) at the daily timescale. The corrected TRMM rainfall data enhanced this daily hydrological simulation with significant improvement in different performance indicators (i.e., NSE, bias and `goodness of fit'). Thus this study finds that the TRMM data products with appropriate correction can be used for estimation of daily streamflows over small watersheds.
机译:对流出的可靠估计对于开发有效的水资源管理策略至关重要。然而,印度有几个流域被吞噬或含有不一致的降雨和排放产品的数据档案,特别是对于日常规模的小流域。本文调查了遥感降雨产品,精确的热带降雨测量使命(TRMM)在上层桐树盆地的日本尺度上,是印度的一个小型热带集水区的疗效。该降水数据集用原位降雨数据校正,并用作物理基于可变渗透能力(VIC)水文模型的输入,用于估计流流。用原始TRMM降雨数据产生的流式流出导致高流出的差异较大,与观察到的放电值相比,并导致每日时间尺度的高正面偏差和低纳什·索菲利(NSE)。纠正的TRMM降雨数据增强了这种日常水文模拟,不同的性能指标的显着改善(即,NSE,偏见和适合的良好性')。因此,该研究发现,具有适当校正的TRMM数据产品可用于估计小流域的日常流式流。

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