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

机译:评估卫星降雨数据对估算印度一个小型热带流域每日流量的适用性

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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:可靠的流量估算对于制定有效的水资源管理策略至关重要。但是,印度有几个流域没有被测量或包含不一致的降雨和排放产品数据存档,尤其是对于日规模的小流域。本文研究了印度小型热带流域Tungabhadra子流域日常尺度上的遥感降雨产品(确切地说是热带降雨测量任务,TRMM)的功效。该降水数据集已用原位降雨数据进行了校正,并用作基于物理的可变渗透能力(VIC)水文模型的输入,用于估算水流。与观察到的流量值相比,使用原始TRMM降雨量数据生成的流量导致高流量和低流量的差异更大,并且在每日时间尺度上导致高正偏差和低Nash-Sutcliffe效率(NSE)。校正后的TRMM降雨量数据通过不同性能指标(即NSE,偏差和``拟合优度'')的显着改善增强了日常水文模拟。因此,本研究发现,经过适当校正的TRMM数据产品可用于估算小流域的日流量。

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