Trends and periodicities in Krishna Basin rainfall/extremes found via hierarchical analysis

HydroResearch Pub Date : 2025-01-01 DOI:10.1016/j.hydres.2024.12.004

Gaurav Pakhale, Rakesh Khosa, A.K. Gosain

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引用次数: 0

Abstract

Analysing the spatiotemporal changes in long-term rainfall and extreme events at a river basin scale is crucial for optimal water resource management. This study examines trends in long-term rainfall and extreme event indices in the Krishna River Basin (KRB) using Indian Meteorological Department (IMD) 0.25° resolution daily precipitation data from 1951 to 2019. Methods include the Mann–Kendall trend test, Innovative Trend Analysis (ITA), Hurst's Rescaled Range (H_e) Analysis, and Wavelets.

The results show variations in rainfall and extreme event patterns across KRB subsystems. Overall, Annual Rainfall (AR) is decreasing, with significant trends in Ghatprabha (K3), Lower Bhima (K6), and Vedavati (K9). Seasonal and monthly rainfall trends are not significant. Extreme event indices (Daily rainfall greater than 10 mm [R10], Daily rainfall greater than 20 mm [R20], and Daily rainfall greater than 40 mm [R40], the annual maximum for 1 to 7 days and starting days of such events showed the non-significant trend in some of the subsystems when analysed with statistical methods; however, graphical analysis using ITA indicates clear trends. H_e construed a sustainable decreasing trend and predicted a future rainfall reduction. The wavelet power spectra for different indices infer periods between 2 and 16, predominantly concentrated around 2–4 year bands. Decreasing annual rainfall in most headwater catchments, captured by most methods, suggests that KRB will experience less rainfall and fewer rainy days in the future.

By discerning long-term rainfall trends and periodic patterns in the KRB, future water availability can be predicted, and extreme events can be better analysed. This analysis will be the basis for devising robust flood control measures, mitigating flood risks, and optimizing water resource allocation across sectors, thereby enhancing resilience to climate variability in future.

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克里希纳盆地降雨/极端事件的趋势和周期性

在流域尺度上分析长期降雨和极端事件的时空变化对优化水资源管理具有重要意义。本研究利用1951年至2019年印度气象局（IMD） 0.25°分辨率日降水数据，研究了克里希纳河流域（KRB）长期降雨和极端事件指数的趋势。方法包括Mann-Kendall趋势检验、创新趋势分析（ITA）、Hurst's rescaledrange （He）分析和小波分析。结果表明，降水和极端事件模式在KRB子系统之间存在差异。总体而言，年降雨量（AR）正在减少，其中Ghatprabha （K3）、下Bhima （K6）和Vedavati （K9）的趋势显著。季节和月降雨量趋势不显著。极端事件指数（日降雨量大于10 mm [R10]、日降雨量大于20 mm [R20]、日降雨量大于40 mm [R40]）、极端事件1 ~ 7天的年最大值和事件发生日在部分子系统中呈不显著趋势；然而，使用ITA的图形分析显示了清晰的趋势。他解释了一个持续减少的趋势，并预测了未来的降雨量减少。不同指数的小波功率谱推断周期在2 ~ 16年之间，主要集中在2 ~ 4年的波段。通过大多数方法捕获的大多数水源集水区的年降雨量减少表明，KRB未来将经历更少的降雨量和更少的雨天。通过识别KRB的长期降雨趋势和周期性模式，可以预测未来的水可用性，并可以更好地分析极端事件。这一分析将成为制定强有力的洪水控制措施、减轻洪水风险和优化各部门水资源分配的基础，从而增强未来应对气候变化的能力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

HydroResearch

CiteScore

9.20

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0.00%

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