Sensoriamento remoto e modelagem aplicados à estimativa de atributos hidrológicos no semiárido brasileiro

• Autor(a) principal: ARAÚJO, Diego Cézar dos Santos
• Data de Publicação: 2020
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UFRPE
• Texto Completo: http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/9077
• topic: Semiárido; Recurso hídrico; Sensoriamento remoto; Seca; CIENCIAS AGRARIAS::ENGENHARIA AGRICOLA

The Brazilian Northeast is the region most vulnerable to water scarcity due to the predominance of the semiarid climate, marked by the deficit and irregularity of rainfall, characteristics that directly affect water security. According to the new National Water Security Plan, 2019, the Northeast is the region with the lowest degree of water security planned for 2035, which leads to the need for studies focusing on the monitoring of hydrological processes and management of water resources. This study aimed to evaluate some hydrological processes in the Northeast using data from remote sensing and hydrological modeling, with a primary focus on estimating and monitoring drought events. For this, precipitation data from the Tropical Rainfall Measuring Mission (TRMM) were validated and used to calculate the Standardized Precipitation Index (SPI) in Pernambuco, for the years 1998 to 2017, as well as soil moisture data from Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) were also validated in Pernambuco and the semiarid region in search of the best instrument for estimating the Soil Water Deficit Index (SWDI), for the period from 2015 to 2018. In addition, a distributed hydrological model, FEST-EWB, was used to spatially model soil moisture and soil surface temperature in the Una River Basin, inserted in a climate transition zone. The results indicated the high potential of TRMM, SMAP and SMOS to estimate rainfall and soil moisture, showing that drought based on SPI and SWDI can be continuously monitored in Pernambuco and in the semiarid region, with wide application. The FEST-EWB model showed great potential in modeling soil moisture and temperature, generating matrix data (maps) with high spatial and temporal resolution that can directly assist in agricultural and water resources management. The data generated in this study is essential because it indicates diversified ways of estimating and monitoring hydrological processes that have great potential in the management of water resources in Northeast Brazil.