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.

中文翻译：

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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每月多尺度干旱进行地质统计建模


巴西东北部地区 （NEB） 的降雨模式变化很大且具有多尺度，增加了对极端干旱和/或洪水事件的敏感性。本研究的目的是利用地统计插值方法，使用标准化降水指数 （SPI） 描述 1990 年至 2019 年 NEB 南海岸的降雨模式和每月干湿期。该研究基于从巴伊亚州沿海地区收集的 112 个气象站的气候数据集。建立了研究区含水层投影图，并确定了 SPI。数据经过描述性、多变量和地统计统计。制作了水文地质和水化学图。10 月至 4 月的特点是雨季 （x3E300 mm）。由于大气环流系统，变异系数显示标准较低。高斯和指数模型为降雨和 SPI 数据提供了最佳拟合 （R2 > 0.86）。研究区地下水质量由优到好不等，但研究区北部中心部分地下水质量较差。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山体滑坡的风险。