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Proposal of an Agricultural Vulnerability Stochastic Model for the Rural Population of the Northeastern Region of Brazil.

Authors :
Silva, Bruce Kelly da Nóbrega
Costa, Rafaela Lisboa
Silva, Fabrício Daniel dos Santos
Vanderlei, Mário Henrique Guilherme dos Santos
da Silva, Helder José Farias
Júnior, Jório Bezerra Cabral
Costa Júnior, Djailson Silva da
Pedra, George Ulguim
Pérez-Marin, Aldrin Martin
Silva, Cláudio Moisés Santos e
Source :
Climate (2225-1154); Oct2023, Vol. 11 Issue 10, p211, 13p
Publication Year :
2023

Abstract

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 (R<subscript>drought</subscript>) 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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22251154
Volume :
11
Issue :
10
Database :
Complementary Index
Journal :
Climate (2225-1154)
Publication Type :
Academic Journal
Accession number :
173266126
Full Text :
https://doi.org/10.3390/cli11100211