Adequacy of Satellite-derived Precipitation Estimate for Hydrological Modeling in Vietnam Basins

Abstract

This study evaluates eight Satellite-derived Precipitation Estimate (SPE) datasets, which include uncorrected SPE and gauge-corrected SPE products from Tropical Rainfall Measurement Mission Multi-satellite Precipitation Analysis (TMPA), Global Precipitation Measurement (GPM), Climate Hazards group Infrared Precipitation (CHIRP), and Precipitation Estimation form Remotely Sensed Information using Artificial Neural Networks (PERSIANN). These datasets are utilized with six representative river basins, corresponding to six sub-climate zones in Vietnam, during the period 2002–2017. The evaluations were carried out in two parts: 1) inter-comparison of the SPE products with rain gauges, for the six basins; 2) comparison of streamflow simulations, using the Soil and Water Assessment Tool (SWAT) forced by precipitation from rain gauge and SPE products. The results indicated that the gauge-corrected SPE datasets exhibited slightly better over the uncorrected datasets in comparison with rain gauges, but showed much higher performances as inputs in hydrological simulations. The GPM Integrated Multi-satellitE Retrievals for GPM (IMERG) Final run version 06B (GPM IMERGF-V6) exhibited the best overall performances among SPE products, in comparison with the rain gauges for the simulation of streamflow. This study is the first of its kind to validate GPM IMERG products in Vietnam, indicating the strong capability of the new IMERG retrieval algorithms. The CHIRP with stations (CHIRPS) dataset demonstrates a relatively low bias, could benefit long-term water resources planning for droughts. In monthly streamflow simulations, the SPE-driven simulations outperformed rain gauge-driven simulations in a larger basin (North West Region), which has low rain-gauge density. The results of this study could be a guide to determine the suitability of different SPE products for hydrological simulations.