Utilization of satellite precipitation products (SPPs) for reliable flood modeling has become a necessity due to the scarcity of conventional gauging systems. Three high-resolution SPPs, i.e., Integrated Multi-satellite Retrieval for GPM (IMERG), Global Satellite Mapping of Precipitation (GSMaP), and Climate Hazards Group InfraRed Precipitation with Station (CHIRPS), data were assessed statistically and hydrologically in the sparsely gauged Chenab River basin of Pakistan. The consistency of rain gauge data was assessed by the double mass curve (DMC). The statistical metrics applied were probability of detection (POD), critical success index (CSI), false alarm ratio (FAR), correlation coefficient (CC), root mean square error (RMSE), and bias (B). The hydrologic evaluation was conducted with calibration and validation scenarios for the monsoon flooding season using the Integrated Flood Analysis System (IFAS) and flow duration curve (FDC). Sensitivity analysis was conducted using ±20% calibrating parameters. The rain gauge data have been found to be consistent with the higher coefficient of determination (R²). The mean skill scores of GSMaP were superior to those of CHIRPS and IMERG. More bias was observed during the monsoon than during western disturbances. The most sensitive parameter was the base flow coefficient (AGD), with a high mean absolute sensitivity index value. During model calibration, good values of performance indicators, i.e., R², Nash−Sutcliffe efficiency (NSE), and percentage bias (PBIAS), were found for the used SPPs. For validation, GSMaP performed better with comparatively higher values of R² and NSE and a lower value of PBIAS. The FDC exhibited SPPs’ excellent performance during 20% to 40% exceedance time.

中文翻译：

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数据稀缺环境中用于洪水估算的卫星降水产品评估

由于缺乏常规测量系统，利用卫星降水产品 (SPP) 进行可靠的洪水建模已成为必要。三个高分辨率 SPP，即 GPM 综合多卫星检索 (IMERG)、全球降水卫星测绘 (GSMaP) 和气候危害组红外降水台站 (CHIRPS)，数据在稀疏测量中进行了统计和水文评估巴基斯坦的杰纳布河流域。雨量计数据的一致性通过双质量曲线（DMC）进行评估。应用的统计指标是检测概率 (POD)、关键成功指数 (CSI)、误报率 (FAR)、相关系数 (CC)、均方根误差 (RMSE) 和偏差 (B)。水文评估是使用综合洪水分析系统 (IFAS) 和流量持续时间曲线 (FDC) 对季风洪水季的校准和验证情景进行的。使用 ±20% 校准参数进行灵敏度分析。已发现雨量计数据与较高的确定系数一致（2）^。GSMaP 的平均技能分数优于 CHIRPS 和 IMERG。在季风期间比在西部扰动期间观察到更多的偏差。最敏感的参数是基流系数 (AGD)，具有较高的平均绝对灵敏度指数值。在模型校准期间，为使用的 SPP 找到了良好的性能指标值，即R ^{2 、Nash-Sutcliffe 效率 (NSE) 和百分比偏差 (PBIAS)。}对于验证，GSMaP 表现更好， R ²和 NSE值相对较高，PBIAS 值较低。FDC 在 20% 到 40% 的超标时间内展示了 SPP 的出色性能。