Using Reanalysis and Remotely Sensed Temperature and Precipitation Data for Hydrological Modeling in Monsoon Climate: Mekong River Case Study

Abstract

Abstract Many large basins in the “Monsoon Asia” region have sparse surface observation networks of the hydrometeorological parameters needed for hydrological modeling. These models are often used in water resources–related planning, impact assessments, and flood forecasting, which sets strict requirements for model accuracy and reliability. The aim of this study was to assess the performance of several publicly available reanalyses and remotely sensed datasets when used in modeling of discharges in the Mekong River basin. Tested precipitations were extracted from Tropical Rainfall Measuring Mission (TRMM) 3B42, versions 6 and 7; Asian Precipitation–Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE); Climate Forecast System Reanalysis (CFSR); and Interim ECMWF Re-Analysis (ERA-Interim) datasets. Temperature data were extracted from CFSR and ERA-Interim datasets. The model results obtained using these datasets were compared to measured discharges and modeled values based on daily surface observations. It was found that using TRMM, version 7, and APHRODITE precipitation datasets together with CFSR temperature data resulted in similar accuracy of computed discharges in the Mekong main stem as using surface observation data. This indicates that these gridded datasets might support well the modeling efforts in monsoon-driven large river basins in Monsoon Asia.