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Impact of soil moisture over Palmer Drought Severity Index and its future projections in Brazil

posted on 26.12.2018, 03:32 by Luciana Rossato, José Antônio Marengo, Carlos Frederico de Angelis, Luciana Bassi Marinho Pires, Eduardo Mario Mendiondo

ABSTRACT Soil moisture is a main factor for the study of drought impacts on vegetation. Drought is a regional phenomenon and affects the food security more than any other natural disaster. Currently, the monitoring of different types of drought is based on indexes that standardize in temporal and regional level allowing, thus, comparison of water conditions in different areas. Therefore, in order to assess the impact of soil moisture during periods of drought, drought Palmer Severity Index was estimated for the entire region of the territory. For this were used meteorological data (rainfall and evapotranspiration) and soil (field capacity, permanent wilting point and water storage in the soil). The data field capacity and wilting point were obtained from the physical properties of soil; while the water storage in soil was calculated considering the water balance model. The results of the PSDI were evaluated during the years 2000 to 2015, which correspond to periods with and without occurrence of drought. In order to assess the future drought projections, considering the set of the Coupled Model Intercomparison rainfall data Project Phase 5 (CMIP5). Climate projections precipitation in CMIP5 for the period 2071-2100 was extracted generating entitled forcing scenarios Representative Concentration Pathways - RCPs, and referred to as RCOP 8.5, corresponding to an approximate radiative forcing the end the twenty-first century of 8.5 Wm-2. The results showed that the PDSI is directly associated with climatological patterns of precipitation and soil moisture in any spatial and temporal scale (including future projections). Therefore, it is concluded that the PDSI is an important index to assess soil moisture different water conditions, as well as the association with economic and social information to create risk maps for subsidies to decision makers.