Evaluation of Three Satellite-Based Precipitation Products Over the Lower Mekong River Basin Using Rain Gauge Observations and Hydrological Modeling

Satellite-based precipitation products (SPPs) have great potential in water-related applications, especially in ungauged/poor-gauged basins. Three SPPs, namely integrated multisatellite retrieval for the global precipitation measurement (GPM) mission, tropical rainfall measuring mission multisatellite precipitation analysis version 7, and precipitation estimation from remotely sensed information using artificial neural networks—climate data record, were evaluated over the lower Mekong river basin (LMB) from January 4, 2014 to February 28, 2017 at daily and monthly scales. Daily rainfall data collected from 119 rain gauges in the LMB were used to conduct a pixel-point comparison. Daily discharge observations at six stream gauges, together with a well-calibrated distributed hydrological model, were used to evaluate the hydrological utilities of the three SPP s. The results convey that: integrated multisatellite retrieval for the GPM mission shows more stable and precise estimation of precipitation in pixel-point comparisons (for both all rainfall events and only heavy rain events) than the other two SPP s; precipitation estimation from remotely sensed information using artificial neural networks—climate data record overestimates the rainfall amounts in LMB seriously by 17%; and integrated multisatellite retrieval for the GPM mission performs better than other two SPP s when forcing hydrological model to simulate discharges with more stable and accurate discharge results (daily Nash–Sutcliffe efficiency coefficient larger than 0.73 and monthly Nash–Sutcliffe efficiency coefficient larger than 0.84).