%0 Journal Article
%T TOPMODEL Hydrometeorological Modeling with Rain Gauge Data Integrated by High-Resolution Satellite Estimates. A Case Study in Muriaé River Basin, Brazil
%A Marcos Figueiredo Salviano
%A Augusto Jos¨¦ Pereira Filho
%A Felipe Vemado
%J Atmospheric and Climate Sciences
%P 486-507
%@ 2160-0422
%D 2021
%I Scientific Research Publishing
%R 10.4236/acs.2021.113029
%X This
study consists of hydrological simulations of the Muria¨¦ 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;\">Patroc¨ªnio do Muria¨¦</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.
%K Hydrologic Model
%K CMORPH
%K Statistical Objective Analysis Scheme (SOAS)
%K TOPMODEL
%K Muria&#233
%K River
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=109858