ZONEAMENTO AMBIENTAL DINÂMICO PARA BACIA HIDROGRÁFICA

• Ano de defesa: 2023
• Autor(a) principal: Erivelton Pereira Vick
• Orientador(a): Vitor Matheus Bacani
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Fundação Universidade Federal de Mato Grosso do Sul
• País: Brasil
• Palavras-chave em Português: Uso e Cobertura da Terra; Fragilidade Ambiental; RUSLE; CAMarkov.
• Link de acesso: https://repositorio.ufms.br/handle/123456789/6782

The growing human pressure on natural resources in river basins has become a relevant and complex challenge in the field of environmental planning and management. To contribute in this direction, it is essential to adopt an approach that takes into account the dynamics of changes in land use and their effects on environmental fragility. Although several environmental zoning approaches have been developed, the lack of specific sound models for this application is still notable. In this context, the main objective of this work was to create a sound environmental zoning for the Rio Pântano Hydrographic Basin (BHRP) through the simulation of future scenarios of land use and coverage. The methodology was based on the combined approach of the hybrid CA-Markov/multi-criteria model and the RUSLE model. Additionally, the combined analysis of morphometric variables was used to evaluate environmental fragility models. The prediction of future scenarios was carried out based on use and coverage mappings from 1984, 2007, 2013 and 2020 to simulate 2030 and 2050 and support the construction of dynamic zoning. Initially, an environmental fragility model was developed based on the morphometric analysis of the river basin. For this, shape variables, compactness index, circularity index, variation density, hypsometric integral, roughness index, erosivity, erodibility and land use and cover calculated in fuzzy function values were used. The environmental fragility models generated are compared with kernel density values of erosive features applying the Local Moran index. For this purpose, they were compared to Ross's models (1994, 2012); Bacani et al. (2015); Moroz-Caccia Gouveia and Ross (2019) and a proposal developed from morphometric variables. To prepare the sound environmental zoning, the years 1984, 2007, 2013 and 2020 were mapped, with kappa statistics values of 0.865; 0.8874; 0.9024; 0.8400, respectively. The prediction of future scenarios was carried out for the years 2030 and 2050. The results of environmental fragility based on morphometric parameters revealed that the BHRP has the following degrees of fragility: very low (12% - 161.88 km²), low (15 .12% - 203.94 km²), medium (16.82% - 226.86 km²), high (21.68% - 292.42 km²) and very high (34.39% - 463.9 km²). Among the environmental fragility models analyzed, the one that used morphometric variables presented the best Local Moran value (r = 0.413), this being the entrepreneur in the environmental zoning proposal. From the application of the fragility model and RUSLE, an increase in environmental fragility and soil loss was noted between 1984 and 2007, a period in which BHRP underwent intense suppression of natural vegetation for the development of pasture areas. . From 2013 to 2050 there was a reduction in soil fragility and loss values, resulting in an increase in eucalyptus areas. However, this cultivation can cause different impacts in the medium and long term in environmental and social contexts. It is concluded that the dynamic environmental zoning model for the river basin proved to be advantageous in relation to the static model. This is due to the fact that the sound model allows predicting future scenarios and situations of great relevance for decision-making in environmental planning and management. The ability to anticipate and analyze changes in land use and their influence on environmental fragility offers advantages to managers and decision makers, allowing the adoption of proactive measures and more effective strategies to guarantee the environmental sustainability of the river basin.