Proposal of an Agricultural Vulnerability Stochastic Model for the Rural Population of the Northeastern Region of Brazil
Bruce Kelly da Nóbrega Silva,
Rafaela Lisboa Costa,
Fabrício Daniel dos Santos Silva,
Mário Henrique Guilherme dos Santos Vanderlei,
Helder José Farias da Silva,
Jório Bezerra Cabral Júnior,
Djailson Silva da Costa Júnior,
George Ulguim Pedra,
Aldrin Martin Pérez-Marin,
Cláudio Moisés Santos e Silva
Affiliations
Bruce Kelly da Nóbrega Silva
National Institute of the Semiarid, Campina Grande 58434-700, Brazil
Rafaela Lisboa Costa
Institute of Atmospheric Sciences, Federal University of Alagoas, Maceió 57072-900, Brazil
Fabrício Daniel dos Santos Silva
Institute of Atmospheric Sciences, Federal University of Alagoas, Maceió 57072-900, Brazil
Mário Henrique Guilherme dos Santos Vanderlei
Institute of Atmospheric Sciences, Federal University of Alagoas, Maceió 57072-900, Brazil
Helder José Farias da Silva
Institute of Atmospheric Sciences, Federal University of Alagoas, Maceió 57072-900, Brazil
Jório Bezerra Cabral Júnior
Institute of Geography, Development and Environment, Federal University of Alagoas, Maceió 57072-900, Brazil
Djailson Silva da Costa Júnior
National Institute of the Semiarid, Campina Grande 58434-700, Brazil
George Ulguim Pedra
National Institute for Space Research, São José dos Campos, São Paulo 12227-010, Brazil
Aldrin Martin Pérez-Marin
National Institute of the Semiarid, Campina Grande 58434-700, Brazil
Cláudio Moisés Santos e Silva
Center for Exact and Earth Sciences, Department of Atmospheric and Climate Sciences, Federal University of Rio Grande do Norte, Natal 59078-970, Brazil
Agriculture is the world’s main economic activity. According to the Intergovernmental Panel on Climate Change, this activity is expected to be impacted by drought. In the Northeast region of Brazil (NEB), most agricultural activity is carried out by small rural communities. Local socio-economic data were analyzed using multivariate statistical techniques in this study to determine agricultural sensitivity to drought events (SeA) and agricultural vulnerability to drought extremes (VaED). The climate data used to develop the risk factor (Rdrought) were the drought indicator with the Standard Precipitation Index (SPI) and the average number of drought disasters from 1991 to 2012. Conditional probability theory was applied to determine agricultural vulnerability to drought extremes (VaED). Characterization of the risk of agricultural drought using the proposed methodology showed that the rainy season presents high risk values in the central region, covering areas of the states of Ceará, Piauí, Pernambuco and Rio Grande do Norte, as well as all areas of the semi-arid region. The risk ranged from high to medium. The results also indicated that part of the south of Bahia and the west of Pernambuco have areas of extreme agro-climatic sensitivity. Consequently, these states have an extreme degree of climate vulnerability during the region’s rainy season.
