Estudo da vazão na bacia dos rios Tocantins/Araguaia: análise da influência de parâmetros hidrológicos do modelo WRF-Hydro

Abstract

Effective management of water resources in regions with great hydric potential, such as the Tocantins/Araguaia Basin in Brazil, is essential given the challenges imposed by energy generation, climate change, and the growth of urban and agricultural areas. In this context, this study evaluates the WRF-Hydro hydrometeorological model (Weather Research and Forecasting-Hydro) to simulate the flow of the Manuel Alves Pequeno, Vermelho, and Manuel Alves Grande rivers in the MATOPIBA region, which encompasses areas of the states of Maranhão, Tocantins, Piauí, and Bahia. This region is an important agricultural frontier in terms of grain production in Brazil. The simulations are conducted in two domains: an external one, with a spatial resolution of 9 km, and an internal one, with a resolution of 3 km and a hydrological network of 100 m. Initially, different sets of physical parameterizations based on previous studies with WRF (Weather Research and Forecasting) and WRF-Hydro in regions with climatic characteristics similar to those of the Tocantins/Araguaia River basin are tested. The selection of the best set of parameterizations for the region is carried out by comparing the precipitation results simulated by WRF-Hydro with observational data from March 1st to 28th, 2019. With the physical parameterizations defined, the analysis of hydrological parameters such as surface runoff, surface retention depth, surface flow roughness, and channel roughness is performed on the simulated flow results, covering a period of intense rainfall from March 13th to June 1st, 2018. For model validation, observational flow data from three fluviometric stations of the National Water and Basic Sanitation Agency (ANA) are used, with evaluations based on statistical indices, resulting in the best values of 0.69 for the Nash-Sutcliffe efficiency index, 0.83 for the correlation coefficient, 4.99 for the percentage bias, and 0.56 for the ratio between the mean square error and the standard deviation of the observations. In particular, the adjustment of the surface runoff parameters and roughness for this runoff contributes more to the improvement of the statistical results than the adjustment of the other two hydrological parameters. Additionally, the quality of the flow simulation at each river measurement station is related to the temporal distribution of simulated precipitation compared to the observed data in the drainage network. This study VI highlights the potential of WRF-Hydro as a fine-scale model, easily coupled with numerical weather forecasting, and significantly advances the assessment of regional river dynamics, crucial for the strategic management of water resources.