Abstract Advancements in science and technology lead to the development of different sensors that measure precipitation, an intrinsic component of the hydrological cycle. As conventional rainfall measurement is tedious, satellite precipitation products are being developed. In the current study, the newly released ECMWF (European Centre for Medium-Range Weather Forecasts) ReAnalysis (ERA-5) along with the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) dataset was statistically evaluated against Indian Meteorological Department (IMD) gridded data and was employed for streamflow simulations using the Soil and Water Assessment Tool (SWAT) model in five contrasting climatic regions of India. Distinct calibration scenarios were developed to test the performance of these reanalysis datasets for simulating streamflow. From categorical and continuous statistical results, ERA-5 exhibited better performance in detecting low (0–5 mm/h) and medium intensity (6–25 mm/h) rainfall, whereas CHIRPS manifested better performance in detecting high intensity rainfall events (>25 mm/h). CHIRPS proved to be effective in simulating streamflows in three out of five basins, whereas IMD exhibited better performance in the other two basins leaving ERA-5 with poor performance for streamflow simulations in all the basins. It was also observed that Satellite Precipitation Products (SPP's) are accurate in humid and tropical regions when compared to arid and semi-arid regions. The worst performance was exhibited in the Ponnaiyar river basin by SPP's and hence bias correction and integration techniques were applied to improve the performance of streamflow simulations further. The novel integration of SPP employing nudging scheme yielded better streamflow simulations when forced into SWAT hydrological model compared to the streamflow simulations obtained when loaded with bias-corrected and raw datasets. The implemented nudging scheme improved the performance of streamflow simulations and hence can be implemented in any basin that is ungauged or resulting in poor hydrological modeling performance when employed with one SPP. The adopted nudging scheme will be highly useful to generate long-term consistent precipitation records in an ungauged or poorly gauged river basin.

中文翻译：

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印度不同气候条件下再分析降雨产品的评价与整合

摘要 科学技术的进步导致了测量降水的不同传感器的发展，降水是水文循环的一个内在组成部分。由于常规降雨测量繁琐，因此正在开发卫星降水产品。在当前的研究中，新发布的 ECMWF（欧洲中期天气预报中心）再分析 (ERA-5) 以及气候危害组红外降水站 (CHIRPS) 数据集针对印度气象部门 (IMD) 网格进行了统计评估数据并被用于在印度五个对比鲜明的气候区域使用土壤和水评估工具 (SWAT) 模型进行水流模拟。开发了不同的校准场景来测试这些再分析数据集的性能，以模拟水流。从分类和连续统计结果来看，ERA-5在检测低强度（0-5 mm/h）和中等强度（6-25 mm/h）降雨方面表现出更好的性能，而CHIRPS在检测高强度降雨事件方面表现出更好的性能（> 25 毫米/小时）。CHIRPS 被证明在模拟五个流域中的三个流域中是有效的，而 IMD 在其他两个流域中表现出更好的性能，而 ERA-5 在所有流域中的流域模拟性能都很差。还观察到，与干旱和半干旱地区相比，潮湿和热带地区的卫星降水产品 (SPP) 是准确的。SPP 在 Ponnaiyar 河流域表现出最差的性能，因此应用了偏差校正和积分技术以进一步提高流量模拟的性能。与加载偏差校正和原始数据集时获得的水流模拟相比，采用轻推方案的 SPP 的新颖集成在强制进入 SWAT 水文模型时产生了更好的水流模拟。实施的微调方案提高了水流模拟的性能，因此可以在任何未测量或在与一个 SPP 一起使用时导致较差水文建模性能的流域中实施。所采用的微调方案对于在未测量或测量差的流域中生成长期一致的降水记录非常有用。实施的微调方案提高了水流模拟的性能，因此可以在任何未测量或在与一个 SPP 一起使用时导致较差水文建模性能的流域中实施。所采用的微调方案对于在未测量或测量差的流域中生成长期一致的降水记录非常有用。实施的微调方案提高了水流模拟的性能，因此可以在任何未测量或在与一个 SPP 一起使用时导致较差水文建模性能的流域中实施。所采用的微调方案对于在未测量或测量差的流域中生成长期一致的降水记录非常有用。