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.
Highlights
Floods are a natural phenomenon, but when occurring in inhabited areas they become natural disasters
The simulations were carried out with the Climate Prediction Center morphing method (CMORPH) precipitation estimates and rain gauge measurements integrated into CMORPH by the Statistical Objective Analysis Scheme (SOAS)
TOPMODEL calibration was performed with the shuffled complex evolution (SCE-UA) method with Nash-Sutcliffe efficiency (NSE)
Summary
Floods are a natural phenomenon, but when occurring in inhabited areas they become natural disasters. Urban expansion associated with socioeconomic problems acts in the increase and intensification of natural disasters related to floods. This is due to changes in the original hydrological cycle, such as increased soil waterproofing, deforestation, erosion, and structural interventions in rivers [2] [3]. The population (mainly low income) increase in hazardous areas enhances the magnitude of natural disaster’s impact [4]. The economic damage caused by natural disasters is significant, as it is estimated that in 2008 alone it was approximately US$ 1 billion [6]
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