TOPMODEL Hydrometeorological Modeling with Rain Gauge Data Integrated by High-Resolution Satellite Estimates. A Case Study in MuriaéRiver Basin, Brazil  

作　　者：Marcos Figueiredo Salviano Augusto José Pereira Filho Felipe Vemado Marcos Figueiredo Salviano;Augusto José Pereira Filho;Felipe Vemado(Geological Survey of Brazil, São Paulo, Brazil;Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, São Paulo, Brazil)

机构地区：[1]Geological Survey of Brazil, Sã o Paulo, Brazil [2]Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de Sã o Paulo, Sã o Paulo, Brazil

出　　处：《Atmospheric and Climate Sciences》2021年第3期486-507,共22页大气和气候科学（英文）

摘　　要：This study consists of hydrological simulations of the Muriaé river watershed with the topography-based hydrological model (TOPMODEL) and available stream gauge and rain measurements between 2009 and 2013 for two subbasins, namely </span><i><span style="font-family:Verdana;">Carangola</span></i><span style="font-family:Verdana;"> and </span><i><span style="font-family:Verdana;">Patrocínio do Muriaé</span></i><span style="font-family:Verdana;">. The simulations were carried out with the Climate Prediction Center morphing method (CMORPH) precipitation estimates and rain gauge measurements integrated into CM- ORPH by the Statistical Objective Analysis Scheme (SOAS). TOPMODEL calibration was performed with the shuffled complex evolution (SCE-UA) method with Nash-Sutcliffe efficiency (NSE). The best overall results were obtained with CMORPH (NSE ~ 0.6) for both subbasins. The simulations with SOAS resulted in an NSE ~ 0.2. However, in an analysis of days with high- level stages, SOAS simulations resulted in a better hit rate (23%) compared to CMORPH (10%). CMORPH simulations underestimated the flows at the flood periods, which indicates the importance to use multi-sensor precipitation data. The results with TOPMODEL allow an estimate of future discharges, which allows for better planning of a flood warning system and discharge measurement schedule.This study consists of hydrological simulations of the Muriaé river watershed with the topography-based hydrological model (TOPMODEL) and available stream gauge and rain measurements between 2009 and 2013 for two subbasins, namely </span><i><span style="font-family:Verdana;">Carangola</span></i><span style="font-family:Verdana;"> and </span><i><span style="font-family:Verdana;">Patrocínio do Muriaé</span></i><span style="font-family:Verdana;">. The simulations were carried out with the Climate Prediction Center morphing method (CMORPH) precipitation estimates and rain gauge measurements integrated into CM- ORPH by the Statistical Objective Analysis Scheme (SOAS). TOPMODEL calibration was performed with the shuffled complex evolution (SCE-UA) method with Nash-Sutcliffe efficiency (NSE). The best overall results were obtained with CMORPH (NSE ~ 0.6) for both subbasins. The simulations with SOAS resulted in an NSE ~ 0.2. However, in an analysis of days with high- level stages, SOAS simulations resulted in a better hit rate (23%) compared to CMORPH (10%). CMORPH simulations underestimated the flows at the flood periods, which indicates the importance to use multi-sensor precipitation data. The results with TOPMODEL allow an estimate of future discharges, which allows for better planning of a flood warning system and discharge measurement schedule.

关 键 词：Hydrologic Model CMORPH Statistical Objective Analysis Scheme (SOAS) TOPMODEL Muriaé River 

分 类 号：P33[天文地球—水文科学]