土耳其杰伊汉河流域极端干旱事件趋势分析综合评价

Musa Eşit, M. Yuce
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引用次数: 1

摘要

极端气象干旱事件的调查对灾害防范和区域水资源管理至关重要。研究了杰伊汉盆地极端干旱事件的变化趋势,即年最大干旱严重程度(AMDS)和年最大干旱持续时间(AMDD)。利用标准降水指数(SPI)对土耳其杰伊汉盆地23个气象站1、3、6、9和12个月的多时间尺度进行了极端事件分析。采用Wallis-Moore和Wald-Wolfowitz方法来确定数据集的同质性,而使用Mann-Kendall和Spearman Rho检验进行趋势分析。趋势的大小由Sen 's斜率和线性回归定义,变化点采用标准正态齐性检验、Buishand 's极差检验和Pettitt 's检验。虽然大多数监测站都有上升趋势,但只有9个监测站的显著性达到95%。研究结果可为杰伊汉河流域水资源管理决策者提供有价值的信息,以评估干旱影响,并制定缓解干旱的措施,以避免未来的干旱风险。在时间序列中发生重大变化的时期。本研究采用标准正态齐性检验(SNHT)、Buishand极差检验(BRT)和Pettitt检验(PT)检测时间序列的变化点。
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Comprehensive evaluation of trend analysis of extreme drought events in the Ceyhan River Basin, Turkey
The investigation of extreme meteorological drought events is crucial for disaster preparedness and regional water management. In this study, trends in extreme drought events, namely annual maximum drought severity (AMDS) and annual maximum drought duration (AMDD), were examined for the Ceyhan Basin. The analyses of extreme events were conducted using the standard precipitation index (SPI) index for multiple-time scales of 1, 3, 6, 9, and 12 months for 23 meteorological stations located in the Ceyhan Basin, Turkey. The Wallis-Moore and Wald-Wolfowitz methods were employed to determine the homogeneity of the data sets, whereas trend analyses were conducted using Mann-Kendall and Spearman Rho tests. The magnitude of trends was defined by Sen’s slope and linear regression, and change points were detected using the standard normal homogeneity test , Buishand’s range test, and Pettitt’s test. Although increasing trends were detected in most of the stations, only in nine of them , statistically significant results were noted at a significance level of 95%. The results of this paper provide valuable information to water resource management decision-makers in the Ceyhan River Basin for evaluating the effect of droughts and preparing for drought mitigation measures to avoid future drought risks. period in which a significant change occurs in a time series. In this study, the standard normal homogeneity test (SNHT), Buishand’s range test (BRT), and Pettitt’s test (PT) were employed to detect change points in the time series.
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