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

IF 4.5 2区 地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES Atmospheric Research Pub Date : 2024-09-04 DOI:10.1016/j.atmosres.2024.107668
Marcos Vinícius da Silva , Jhon Lennon Bezerra da Silva , Maria Beatriz Ferreira , Lizandra de Barros de Sousa , Abelardo Antônio de Assunção Montenegro , Jorge Manuel Guieiro Pereira Isidoro , Héliton Pandorfi , José Francisco de Oliveira-Júnior , Helena Maria Neto Paixão Vazquez Fernandez , Fernando Miguel Granja-Martins , Alexandre Maniçoba da Rosa Ferraz Jardim , Thieres George Freire da Silva , Ada Liz Coronel Canata , Ivonete Alves Bakke , Olaf Andreas Bakke , Arliston Pereira Leite , Mayara Maria de Lima Pessoa , Antônio Lucineudo de Oliveira Freire , Rafael dos Santos Gonçalves , Henrique Fonseca Elias de Oliveira , Guilherme Ferreira de Brito
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Abstract

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.

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通过标准化降水指数对巴西东北部南海岸的降雨模式和干旱月度多尺度特征进行地质统计建模
巴西东北部地区(NEB)的降雨模式变化很大,而且是多区划的,这增加了发生极端干旱和/或洪水事件的可能性。本研究的目的是利用地理统计插值法,使用标准化降水指数(SPI)描述 1990 年至 2019 年巴西东北部南海岸的降雨模式和月干湿期。研究以巴伊亚州沿海地区的气候数据集为基础,该数据集由 112 个气象站收集而成。绘制了研究区域含水层预测图,并确定了 SPI。对数据进行了描述性、多变量和地质统计学统计。绘制了水文地质和水化学地图。10 月至次年 4 月为雨季(大于 300 毫米)。由于大气环流系统的影响,变异系数显示出较低的标准。高斯模型和指数模型是降雨量和 SPI 数据的最佳拟合模型(R > 0.86)。研究区的地下水质量从优到良不等,只有研究区中部偏北的地区地下水质量较差。巴伊亚海岸南部地区发布了关于当地居民安全的警报,包括降雨和洪水导致的山体滑坡风险。
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来源期刊
Atmospheric Research
Atmospheric Research 地学-气象与大气科学
CiteScore
9.40
自引率
10.90%
发文量
460
审稿时长
47 days
期刊介绍: The journal publishes scientific papers (research papers, review articles, letters and notes) dealing with the part of the atmosphere where meteorological events occur. Attention is given to all processes extending from the earth surface to the tropopause, but special emphasis continues to be devoted to the physics of clouds, mesoscale meteorology and air pollution, i.e. atmospheric aerosols; microphysical processes; cloud dynamics and thermodynamics; numerical simulation, climatology, climate change and weather modification.
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