Evaluation of Satellite Meteorolo gical Datasets for their Application to the Distributed Rainfall-runoff Model in Scarce-data Southeast Asian Watersheds

DOI IR (HANDLE) Open Access
  • FUNABASHI Atsushi
    Laboratory of Water Environment Engineering, Course of Bioproduction Environmental Sciences, Department of Agro-environmental Sciences, Graduate School of Bioresource and Bioenvironmental Sciences, Kyushu University
  • HIRAMATSU Kazuaki
    Laboratory of Water Environment Engineering, Division of Bioproduction Environmental Sciences, Department of Agro—environmental Sciences, Faculty of Agriculture, Kyushu University
  • Trieu Anh Ngoc
    Division of Science, Technology and International Affairs, Thuyloi University, HCMC Campus, Vietnam
  • HARAD Masayoshi
    Laboratory of Water Environment Engineering, Division of Bioproduction Environmental Sciences, Department of Agro—environmental Sciences, Faculty of Agriculture, Kyushu University
  • TABATA Toshinori
    Laboratory of Water Environment Engineering, Division of Bioproduction Environmental Sciences, Department of Agro—environmental Sciences, Faculty of Agriculture, Kyushu University

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Other Title
  • データ寡少な東南アジア流域における衛星気象データセットの評価および分布型降雨流出モデルヘの適用

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In this study, the accuracy of satellite meteorological data was firstly evaluated, and a bias correction method was developed to apply these satellite meteorological data to the rainfall-runoff analysis in scarce-data watersheds of southeast Asia. The Sai Gon-Dong Nai river basin located in the southern part of Vietnam and the lower Chao Phraya river basin in Thailand were the target watersheds for the evaluation of satellite data, and the Thac Mo basin, which is a sub-basin of the Sai Gon-Dong Nai river basin, was the target of rainfall runoff analyses. The error indices of mean absolute error, root mean square error, percent bias and correlation coefficient were calculated for 5 types of rainfall satellite data and 2 types of evapotranspiration satellite data. As a result, the IMERG was selected for rainfall and the AgMERRA was selected for evapotranspiration as the data with high estimation accuracy. Next, based on the results of evaluation using the spatial distribution index SPE and the spatial mapping, the AgMERRA and the MSWEP were selected for rainfall and the AgMERRA was selected for evapotranspiration as highly compatible data for the spatial distribution pattern The bias correction using the percent bias was performed on these satellite data, and as a result of using them as input values for the distributed rainfall-runoff model incorporating the tank models for several land utilizations, good simulation accuracy could be obtained. It was concluded that the satellite data with high estimation accuracy to ground-based observation data could be sufficiently applied to rainfall-runoff analysis, and that the satellite data that had high compatibility with the spatial distribution pattern of ground-based observation data could be also applied to rainfall-runoff analysis by introducing the bias correction.

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