MODELO EMPÍRICO DE DEMANDA HÍDRICA SETORIAL BASEADO NA OCUPAÇÃO DE BACIAS HIDROGRÁFICAS

Detalhes bibliográficos
Ano de defesa: 2023
Autor(a) principal: Vinícius Vieira de Moraes
Orientador(a): Dulce Buchala Bicca Rodrigues
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Fundação Universidade Federal de Mato Grosso do Sul
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Brasil
Palavras-chave em Português:
Link de acesso: https://repositorio.ufms.br/handle/123456789/6543
Resumo: The evolution of water uses in hydrographic basins is linked to processes of regional human settlement, encompassing various socio-economic activities and distinct land cover patterns. This study proposes the development of empirical mathematical models to depict sectoral water demand and its relationship with environmental and socioeconomic aspects of hydrographic basins. We assessed the correlation between sectoral water demand data, land cover classes, and socio-economic indicators, all of which were made available through institutional databases. Empirical models for urban and livestock water demand were constructed using multiple regression. The calibration and validation stages were executed in the Paraíba do Sul River Basin, located in southeastern Brazil, involving historical and future simulation of water use behaviors. The findings demonstrated that the normalized empirical model for urban water demand yielded satisfactory results, relying on data related to urbanized area and urban population. Meanwhile, the semi-logarithmic model for livestock water demand emerged from data involving livestock area and the agricultural sector's GDP. Therefore, the proposed empirical mathematical models enable the estimation of current and future water demands based on changes in land cover within hydrographic basins, thereby providing support for integrated land use and water resource management.