Evaluation of Satellite-Based and Reanalysis Precipitation Datasets with Gauge-Observed Data over Haraz-Gharehsoo Basin, Iran

Evaluating satellite-based products is vital for precipitation estimation sustainable water resources management. The current study evaluates the accuracy of predicting using four remotely sensed rainfall datasets—Tropical Rainfall Measuring Mission (TRMM-3B42V7), Precipitation Estimation from Remotely Sensed Information Artificial Neural Networks Climate Data Records (PERSIANN-CDR), Cloud Classification System-Climate Record (PERSIANN-CCS-CDR), and National Centers Environmental Prediction (NCEP)-Climate Forecast System Reanalysis (CFSR)—over Haraz-Gharehsoo basin during 2008–2016. benchmark values assessment are gauge-observed data gathered without missing at nine ground-based measuring stations over basin. results indicate that TRMM CCS-CDR satellites provide more robust estimations in 75% high-altitude daily, monthly, annual time scales. Furthermore, comparative analysis reveals some underestimations each satellite. underestimation obtained by CDR, CCS-CDR, CFSR 8.93 mm, 20.34 9.77 17.23 mm annually, respectively. compared to previous studies conducted other basins. It concluded considering satellite product estimating valuable essential hydrological modelling.