Cenários futuros da deficiência hídrica na região do Matopiba / Welinagila Grangeiro de Sousa

Abstract

Extreme climatic events are a reality in various regions over time, and their impacts affect different sectors, especially agriculture. A recently highlighted area is MATOPIBA, formed by the union of the states of Maranhão, Tocantins, Piauí, and Bahia, which has undergone significant social and environmental transformations due to the expansion of intensive agriculture. This study aimed to evaluate the spatial and temporal patterns of climate variability in the MATOPIBA region for the period from 1961 to 2100 under different projected climate change scenarios. Historical monthly data series on precipitation and air temperature for the period from 1961 to 2018 were used, obtained from CRU-TS-4.03 reanalyses, which are part of the WorldClim 2.1 database. Future monthly data (2020 to 2100) on precipitation and temperature were sourced from the Global Climate Model (GCM) HadGEM2-ES (The Hadley Global Environmental Model version 2), which incorporates bias correction through the Coupled Model Intercomparison Project Phase 5 (CMIP5). Initially, the variability of droughts was analyzed using the Standardized Precipitation and Evapotranspiration Index (SPEI) from 1961 to 2018 on a 12-month time scale, employing geoprocessing techniques and time series analysis to understand the historical drought patterns in the region. A progressive increase in events was observed throughout the region, especially in more recent periods, with significant upward trends over the years. Subsequently, the seasonality of rainfall and reference evapotranspiration for future projections during the period from 2020 to 2099 was analyzed, considering an intermediate scenario (RCP4.5) and a pessimistic scenario (RCP8.5). The results indicated a reduction in rainfall, especially during the dry period of the region, and significant increases in reference evapotranspiration, highlighting the pessimistic RCP8.5 scenario as the most impactful for the studied region. This information is relevant to guide decision-makers in adopting mitigation measures for the potential impacts of these events.