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https://doi.org/10.1002/(SICI)1099-1085(199707)11:9%3C1169::AID-HYP551%3E3.0.CO;2-W

has been cited by the following article:

• TITLE: TOPMODEL Hydrometeorological Modeling with Rain Gauge Data Integrated by High-Resolution Satellite Estimates. A Case Study in Muriaé River Basin, Brazil

  AUTHORS: Marcos Figueiredo Salviano, Augusto José Pereira Filho, Felipe Vemado

  KEYWORDS: Hydrologic Model, CMORPH, Statistical Objective Analysis Scheme (SOAS), TOPMODEL, Muriaé River

  JOURNAL NAME: Atmospheric and Climate Sciences, Vol.11 No.3, June 16, 2021

  ABSTRACT: 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 Carangola and Patrocínio do Muriaé. 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.