WRF-Hydro for Streamflow Simulation in the MATOPIBA Region within the Tocantins/Araguaia River Basin—Brazil: Implications for Water Resource Management

Abstract

The effective management of water resources in regions with a high potential for water resources, such as the Tocantins/Araguaia Basin in Brazil, is crucial in the face of current climate change and urban and agricultural expansion. In this context, this study evaluates the WRF-Hydro hydrological model to simulate the flow of the Manuel Alves Pequeno, Vermelho, and Manuel Alves Grande rivers in the MATOPIBA region (encompassing areas from the states of Maranhão, Tocantins, Piauí, and Bahia), an agricultural frontier and the most key area in terms of grain production in Brazil. The aim is to analyze the hydrological parameters of soil infiltration, surface retention depth, land surface roughness, and Manning’s channel roughness. The simulations are conducted at a spatial resolution of 3 km with a channel network of 100 m, covering a period of heavy rainfall from 13 March to 1 June 2018. For model validation, observational data from three river gauge stations of the National Water and Sanitation Agency are used, with assessments based on the Nash-Sutcliffe efficiency index, standard deviation of observations, root mean square error, percentage bias, and correlation coefficient, resulting in values of 0.69, 0.56, 4.99, and 0.83, respectively. In particular, the adjustment of the infiltration factor and surface roughness parameter has a greater contribution to improving the statistical results than the adjustment of the other two hydrological parameters. Additionally, the quality of discharge simulation at each river gauge station is correlated with the temporal distribution of simulated precipitation compared to observed data in the drainage network. Highlighting WRF-Hydro’s potential as a fine-scale model easily coupled with numerical weather prediction, this study significantly advances regional river dynamics evaluation, crucial for strategic water resource management.