Geostatistical modeling of the rainfall patterns and monthly multiscale characterization of drought in the South Coast of the Northeast Brazilian via Standardized Precipitation Index

• Published in: Atmospheric research Vol. 311; p. 107668
• Main Authors: Silva, Marcos Vinícius da, Silva, Jhon Lennon Bezerra da, Ferreira, Maria Beatriz, Sousa, Lizandra de Barros de, Montenegro, Abelardo Antônio de Assunção, Isidoro, Jorge Manuel Guieiro Pereira, Pandorfi, Héliton, Oliveira-Júnior, José Francisco de, Fernandez, Helena Maria Neto Paixão Vazquez, Granja-Martins, Fernando Miguel, Jardim, Alexandre Maniçoba da Rosa Ferraz, Silva, Thieres George Freire da, Canata, Ada Liz Coronel, Bakke, Ivonete Alves, Bakke, Olaf Andreas, Leite, Arliston Pereira, Lima Pessoa, Mayara Maria de, Oliveira Freire, Antônio Lucineudo de, Gonçalves, Rafael dos Santos, Oliveira, Henrique Fonseca Elias de, Mesquita, Márcio, Araújo Júnior, George do Nascimento, Carvalho, Ailton Alves de, Battisti, Rafael, Lyra, Gustavo Bastos, Silva, Josef Augusto Oberdan Souza, Salomão, Leandro Caixeta, Silva, Elania Freire da, Brito, Guilherme Ferreira de
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.12.2024
• Subjects: Aquifer projection; Climatological series; Geostatistical interpolation; Meteorological system; Rainfall; ITCZ; Q1; Q3; SDSD; E; SASH; SPI-1; MDSD; FS; SPI; SE; EWD; DSD; Climatological series; G1 and G2; SGB/CPRM; IDW; CA; INMET; R2; PCs; CCC; Geostatistical interpolation; Aquifer projection; ENSO; Rainfall; SPI-12; NEB; IQR; ULCV; PCA; PCC; r; CV; ANA; Meteorological system; WDSD; NC1 and NC2; WDTW; shp; CHIRPS; SRTM
• ISSN: 0169-8095
• DOI: 10.1016/j.atmosres.2024.107668

Variations in rainfall patterns in the Northeast region of Brazil (NEB) are high and multiscalar, increasing susceptibility to extreme drought and/or flood events. The objective of this study was to characterize rainfall patterns and monthly dry-wet periods using the Standardized Precipitation Index (SPI) from 1990 to 2019 in the South Coast of NEB, utilizing geostatistical interpolation methods. The study was based on a climatological dataset from the coastal region of the state of Bahia, collected from 112 weather stations. A map projecting aquifer in the study area was established, and SPI was determined. The data were subjected to descriptive, multivariate, and geostatistical statistics. Hydrogeological and hydrochemical maps were prepared. The months of October to April are characterized as rainy months (>300 mm). The coefficient of variation showed low standards due to atmospheric circulation systems. The Gaussian and exponential models presented the best fits (R2 > 0.86) for rainfall and SPI data. The quality of groundwater in the study area ranges from excellent to good, except for the north center part of the study area, where the groundwater quality is poor. An alert is issued for the southern region of the Bahian coast regarding the safety of the local population, including the risk of landslides resulting from rain and floods. [Display omitted] •Geostatistical interpolation of rainfall data accurately identifies the main risks and challenges regarding water security.•In dry months, rainfall is unevenly distributed, while in rainy months, rainfall is homogeneous.•The rainfall regimes on the coast of Bahia are worrying, with areas of extreme risk, requiring local public administration.