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Water Resources Early Warning Study of MODIS cloud-precipitation relationship over the Wuxi Rive basin

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  2018 ASABE Annual International Meeting  1800455.(doi:10.13031/aim.201800455)
Authors:   Dingwang Zhou, Jie Chen, Weijun Bao, Zonglou Guo
Keywords:   MODIS, cloud-precipitation, BP neural network, Wuxi Rive basin

Abstract. It is great significant to surface water management systems to provide early warning of abrupt, large variations in water quantity, which likely indicates the occurrence of drought or flood. In this study, according to Moderate Resolution Imaging Spectroradiometer (MODIS) data and weather station data during the period of March 2000 to December 2004 in Wuxi Rive basin, we built a cloud-precipitation relationship of water quantity warning provision by the back propagation(BP) neural network model. Results showed that the precision of forecast rainfall after 10 days is over 60% by using cloud-precipitation relationship. By combining satellite remote date, presented approach can avoid timely natural disasters and improve the efficiency for watershed management.

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