Streamflow forecasts due precipitation water in a tropical large watershed at Brazil for flood early warning, based on SWAT model

• Autor(a) principal: Deus, Simonny C. S
• Data de Publicação: 2018
• Outros Autores: Neves, Ramiro J. J, Jauche, Eduardo, Almeida, Carina, Faial, Kleber Raimundo Freitas, Medeiro, Adaelson Campelo, Mendes, Rosivaldo A, Faial, Kelson do Carmo Freitas, Leite, Jandecy Cabral, Deus, Ricardo J. A
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Digital do Instituto Evandro Chagas (Patuá)
• DOI: 10.5935/2447-0228.20180027.
• Texto Completo: https://patua.iec.gov.br/handle/iec/3497
• topic: Água de Chuva / prevenção & controle; Bacias Hidrográficas / análise; Precipitação Atmosférica; Escoamento de Água de Chuva / métodos; Coeficiente de Escoamento; Modelo SWAT; Previsão de Inundações; Previsões / métodos; Inundações; Bacia do Tocantins-Araguaia (PA); Usina Hidrelétrica de Tucuruí (PA)

The Tocantins-Araguaia Watershed, which is distributed equivalent to 11% of Brazilian territory, conveys waters to the northern portion of Brazil with average discharge of 11000 m3 s -1 , with contribution from the Tocantins River (40%), the Araguaia River (45%), and the Itacaiúnas River (5%), making possible an intangible flood in the Marabá city and Tucuruí Hydroelectric Plant (Downstream) during periods of high rainfall within the tropical watershed without provide timely warnings. For flash flood forecasting in a tropical large watershed, streamflow forecasts due precipitation water is required for flood early warning and in this sense, numerical prediction models are fundamental to extend streamflow forecast of a watershed due to precipitation. The paper focuses on the use Soil and Water Assessment Tool (SWAT), January 2007 to December 2010 period, to comparison of streamflows obtained from the post-processed precipitation forecasts, in providing skilful flood forecasts. In this sense, the basin was divided into 109 sub-basins and 1969 HRUs, and the model was calibrated and validated based on flow rate data in three monitoring points located next of Marabá city and Tucuruí hydroelectric. Posteriorly, simulated discharges scenario due to climatic variability extreme were generated under three strategies: 10%, 50% and 100% increase in ambient temperature (24℃) due natural and/or anthropogenic events within the watershed. The model results show that stream flows obtained adds value to the flood early warning system when compared to precipitation forecasts. Considering that climate is a direct function of temperature it is obvious that all relevant phenomena undergo changes. The scenarios results show that 50% increase in ambient temperature this leads to greater and faster evaporation. Thus, the gradual increase of precipitation in tropical watershed large alters flow rates over time and increase flood potentials in areas downstream of the basins. However, the need for more detailed evaluation of the model results in the study area is highlighted, due adequately represent the convective precipitation within the large tropical watershed.