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The study of rainfall trends is crucial for food security and water availability in Alagoas state, Northeast of Brazil. In this work, monthly, seasonal and annual rainfall trends have been studied (1960–2016) for homogeneous rainfall regions over the eastern part of the Northeast Brazil (ENEB) and later related to climate variability. Cluster analysis was applied to identify homogeneous rainfall regions while the Mann–Kendall (MK), modified Mann–Kendall (MMK) and Pettitt tests were used in the analysis and identification of trends on a spatial and temporal scale. To relate rainfall and climate variability modes, Spearman's correlation was used in each homogeneous region. The rainfall series provided evidence of a general decrease in rainfall in the rainy period and an increase in the dry period, mainly over the driest region. The break points of time series occurred mostly in periods of great variations in values of modes of climate variability, especially the Monthly Niño3.4 Index and the Southern Oscillation Index (SOI), both having a robust influence across the region. Moreover, the probable rainfall in the time series with trends was different in most months before and after the breakpoint. After the breakpoint, probable rainfall was lower, influenced by the breakpoint year (size of the series before and after the breakpoint), which mainly occurred in the 1980s and 1990s and presented a warm phase and a greater number of El Niño events. The MK and MMK trend tests showed the ability to detect trends, although there is no established standard on which test or version to use due to self‐correlated, nonhomogeneous series with nonrandom or nonindependent data. Rainfall is an important variable for water and food security and in the monitoring of natural disasters. The changes detected in this study can be used as reference information for public policies on water resources and future studies for Alagoas and similar regions.
The study of rainfall trends is crucial for food security and water availability in Alagoas state, Northeast of Brazil. In this work, monthly, seasonal and annual rainfall trends have been studied (1960–2016) for homogeneous rainfall regions over the eastern part of the Northeast Brazil (ENEB) and later related to climate variability. Cluster analysis was applied to identify homogeneous rainfall regions while the Mann–Kendall (MK), modified Mann–Kendall (MMK) and Pettitt tests were used in the analysis and identification of trends on a spatial and temporal scale. To relate rainfall and climate variability modes, Spearman's correlation was used in each homogeneous region. The rainfall series provided evidence of a general decrease in rainfall in the rainy period and an increase in the dry period, mainly over the driest region. The break points of time series occurred mostly in periods of great variations in values of modes of climate variability, especially the Monthly Niño3.4 Index and the Southern Oscillation Index (SOI), both having a robust influence across the region. Moreover, the probable rainfall in the time series with trends was different in most months before and after the breakpoint. After the breakpoint, probable rainfall was lower, influenced by the breakpoint year (size of the series before and after the breakpoint), which mainly occurred in the 1980s and 1990s and presented a warm phase and a greater number of El Niño events. The MK and MMK trend tests showed the ability to detect trends, although there is no established standard on which test or version to use due to self‐correlated, nonhomogeneous series with nonrandom or nonindependent data. Rainfall is an important variable for water and food security and in the monitoring of natural disasters. The changes detected in this study can be used as reference information for public policies on water resources and future studies for Alagoas and similar regions.
The current study aimed to examine the interseasonal characteristics of meteorological drought. For this purpose, a new comprehensive framework is proposed. The framework consists of two major stages. In the first stage of the framework, the K-means method is utilized to identify homogeneous clusters. Besides, the Monte Carlo feature selection (MCFS) is applied to select more important stations from the varying clusters. In the second stage, the standardized precipitation index at a three-time scale (SPI-3), the conditional fixed effect binary logistic regression model (CFEBLRM), and the random effect binary logistic regression model (REBLRM) are utilized. The significance of CFEBLRM and REBLRM is measured by log-likelihood values, log-likelihood ratio chi-square test (LRCST), Wald chi-square tests (WCT), and p values. The Hausman test (HT) is applied to identify endogeneity and suggests the appropriate model in CFEBLRM and REBLRM. The results from the proposed framework indicate that the drought persists in the summer to autumn and autumn to winter seasons between 90 and 99 percent. The odds ratio of CFEBLRM for the summer-autumn season indicates that the increment in precipitation will decrease the drought persistence in the autumn season. The result of the current study facilitates the decision-makers to understand the effects of meteorological drought occurrences better and improve strategies for mitigating drought effects and managing seasonal crops in the Punjab province in Pakistan.
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