Análise de incertezas associado ao emprego do modelo chuva-vazão SCS : estudo de caso da Bacia Hidrográfica do Córrego Águas Claras
Ano de defesa: | 2024 |
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Autor(a) principal: | |
Orientador(a): | |
Banca de defesa: | |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade Federal do Espírito Santo
BR Mestrado Profissional em Gestão e Regulação de Recursos Hídricos Centro Tecnológico UFES Programa de Pós-Graduação em Gestão Regulação Recursos Hídricos |
Programa de Pós-Graduação: |
Não Informado pela instituição
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Departamento: |
Não Informado pela instituição
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País: |
Não Informado pela instituição
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Palavras-chave em Português: | |
Link de acesso: | http://repositorio.ufes.br/handle/10/18215 |
Resumo: | Human activities related to land use and occupation have significantly impacted the hydrological cycle, contributing to climate change and, consequently, increasing the frequency of natural disasters. To evaluate the impacts of these changes on watersheds, it is essential to employ hydrological models capable of simulating surface runoff. However, there is a certain scarcity of data and uncertainties associated with the measurement of hydrological variables and the determination of coefficients and parameters of the models used to estimate peak flow. This study aims to analyze the behavior of peak flows in the Águas Claras watershed, located in the municipality of Águia Branca, Espírito Santo, incorporating uncertainty analysis conducted using the Monte Carlo method into the rainfall-runoff model proposed by the Soil Conservation Service (SCS). The results demonstrate that the approach for estimating intense rainfall can lead to significant differences in simulated flows. In this study, intense rainfall estimated using the Plúvio software resulted in substantially higher peak flows compared to those obtained using an intense rainfall equation calibrated with the Chow-Gumbel method. The evaluation of peak flows, considering the incorporation of uncertainty analysis into the rainfall-runoff model, showed greater variations in simulations where precipitation-related variables, such as duration and precipitation depth, were perturbed. Although the distribution of peak flows differed when changing the probability distribution used in the random generation process of the perturbed variables, the extreme flow values did not vary significantly. Additionally, increasing the number of simulations did not significantly influence the distribution of estimated peak flows. The integration of uncertainty analysis into the SCS rainfall-runoff model revealed that significant variations can occur in peak flow estimates, emphasizing the importance of incorporating uncertainty analysis into hydrological assessments |