Modelagem chuva-vazão a nível mensal das sub-bacias dos rios TAperoá e Piancó – PB

• Main Author: Sousa, Yesus Parvati Andrade
• Publication Date: 2021
• Format: Bachelor thesis
• Language: por
• Source: Biblioteca Digital de Teses e Dissertações da UFPB
• Download full: https://repositorio.ufpb.br/jspui/handle/123456789/25442
• topic: Modelos chuva-vazão; Redes Neurais Artificiais; Modelos chuva; Modelos chuva; CNPQ::ENGENHARIAS::ENGENHARIA CIVIL

Water is the most important asset in sustaining life and is present in practically everything around us, such as human supply, irrigation, electricity generation, among other activities. Therefore, among other needs, the monitoring of hydrological variables for the proper management of water resources must be carried out, whether at a local or regional level. In this sense, by measuring these variables, hydrological models can be developed, which seek to represent in a simplified way the physical phenomena that occur in nature. Within the mathematical hydrological models, we have the rainfall-runoff models, which aim to perform the flow calculation based on rainfall values in a given region. In addition to the mathematical hydrological models, there are models based on Artificial Neural Networks (ANN). In this sense, in the present work, the mathematical model Soil Moisture Accounting Procedure (SMAP) and an ANN-based model will be used to calculate the influent flow in the Taperoá river sub-basin and in the Piancó river sub-basin, in the State of Paraíba . The modeling of the Taperoá river sub-basin followed the temporal scope comprising the period of available data from 01/01/1970 to 12/01/2014, while the modeling of the Piancó river sub-basin comprised the period of available data from 05/01/1969 to 12/01/2014. The data were used on a monthly time scale. To fill gaps in rainfall series, the regional vector method was used. The SMAP model generated as a result Nash coefficients of 0.67 and 0.40, in the total period, for the Taperoá and Piancó river sub-basins, respectively. The ANNs generated Nash coefficients of 0.84 and 0.64, in the total period, for the Taperoá and Piancó river sub-basins, respectively. Compared to the SMAP model, the ANNs were more accurate in the rainfall-runoff modeling for the sub-basins studied.