Changes in water use efficiency related to climatic factors and land use and occupation in the MATOPIBA region

• Autor(a) principal: Santiago, Dimas de Barros
• Data de Publicação: 2021
• Outros Autores: Barbosa, Humberto Alves, Correia Filho, Washington Luiz Félix
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Research, Society and Development
• Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/17891
• topic: Eficiencia en el uso del agua; MATOPIBA; Uso y ocupación de la tierra.; Water Use Efficiency; MATOPIBA; Land use and occupation.; Eficiência do Uso da água; MATOPIBA; Uso e ocupação do solo.

The study aims to: estimate and analyze the spatial-temporal changes of the WUE in MATOPIBA and evaluate the influence of climatic factors and land use and occupation on the variation of the WUE. The study will use the products MOD17A2 (GPP), and MOD16A2 (ET) derived from the MODIS sensor (Moderate Resolution Imaging Spectroradiometer) obtained in the United States Geological Survey (USGS), with spatial resolution 1 km x 1km, for the computation of the annual WUE in the period between 2001 and 2019. Regarding the evaluation of land use based on the MAPBIOMAS maps, with a resolution of 30m x 30m. Precipitation data will come from the Climate Hazard Group InfraRed Precipitation with Station data (CHIRPS) with a spatial resolution of 5.6 km by 5.6 km. The mathematical calculations were developed in R environment software version 3.6-3 and Quantum GIS version 3.4-6. The results show that the highest (lowest) values ​​of WUE occur in agricultural regions and areas of native Amazonian vegetation (non-vegetated surface areas). This WUE pattern is associated with the growing agricultural expansion over the regions (West Bahia and in the Piauí portion), mainly motivated by soy planting. In addition, during dry (wet) years have positive (negative) anomalies of WUE. Concluding that, agricultural areas are prone to higher WUE values ​​due to cultural management helping develop crops. Vegetation responses to dry and rainy events were more sensitive in agricultural areas than in areas of native vegetation.