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评估印度中部河流流域的气候变化和干旱地区。

Evaluating climate shifts and drought regions in the central Indian river basins.

作者信息

Singh Shekhar, Jain Vijay, Goyal Manish Kumar

机构信息

Department of Civil Engineering, Indian Institute of Technology Indore, Simrol, Indore, 453552, Madhya Pradesh, India.

出版信息

Sci Rep. 2025 Aug 13;15(1):29701. doi: 10.1038/s41598-025-15231-1.

DOI:10.1038/s41598-025-15231-1
PMID:40804117
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12350630/
Abstract

Climate change, characterized by erratic rainfall patterns and rising temperatures, is enhancing the severity and intensity of drought across India. Considering this impact, assessment of these changes is critical for developing effective adaptation and mitigation strategies. This study employs a stochastic entropy-based approach to compute the inter- and intra-annual rainfall variability for multiple temporal scales. Considering this assessment, we identified winter, pre-monsoon, and post-monsoon seasons as key contributors to annual rainfall variability. Furthermore, using the entropy approach, we prepared a water resource availability map. It presents that 53.88% of the Betwa's water resources and 54.57% of the Kshipra's resources fall under Classes B and C, highlighting significant vulnerability to drought conditions in both basins. Subsequently, meteorological and hydrological droughts were evaluated using SPI, SPEI, and SRI indices. It showed that the Southern and Central regions of the Kshipra and the Northern and Central regions of the Betwa are highly drought prone. The outcome of the present study provides vulnerable drought regions with prolonged duration and high severity and intensity regions across the basin. It will support policymakers in implementing timely and targeted interventions for water resource management, facilitating the development of effective drought action plans.

摘要

气候变化以降雨模式不稳定和气温上升为特征,正在加剧印度各地干旱的严重程度和强度。考虑到这种影响,评估这些变化对于制定有效的适应和缓解策略至关重要。本研究采用基于随机熵的方法来计算多个时间尺度上的年际和年内降雨变率。基于这一评估,我们确定冬季、季风前和季风后季节是年降雨变率的主要贡献因素。此外,利用熵方法,我们绘制了水资源可利用性地图。结果表明,贝特瓦河53.88%的水资源和克希普拉河54.57%的水资源属于B类和C类,这突出了两个流域对干旱条件的显著脆弱性。随后,使用标准化降水指数(SPI)、标准化降水蒸散指数(SPEI)和标准化径流指数(SRI)评估了气象干旱和水文干旱。结果表明,克希普拉河的南部和中部地区以及贝特瓦河的北部和中部地区极易发生干旱。本研究的结果提供了整个流域干旱持续时间长、严重程度和强度高的脆弱干旱地区。它将支持政策制定者对水资源管理实施及时和有针对性的干预措施,促进制定有效的干旱行动计划。

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2
Longitudinal assessment of extreme climate events in Kinnaur district, Himachal Pradesh, north-western Himalaya, India.印度喜马拉雅山西北部喜马偕尔邦金瑙尔地区极端气候事件的纵向评估。
Environ Monit Assess. 2024 May 20;196(6):557. doi: 10.1007/s10661-024-12693-0.
3
Drought Atlas of India, 1901-2020.印度干旱图集,1901-2020 年。
Sci Data. 2024 Jan 2;11(1):7. doi: 10.1038/s41597-023-02856-y.
4
The influence of variations in actual evapotranspiration on drought in China's Southeast River basin.实际蒸散量变化对中国东南流域干旱的影响。
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5
River interlinking alters land-atmosphere feedback and changes the Indian summer monsoon.河流连通改变了陆地-大气反馈并影响了印度夏季风。
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6
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7
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8
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Sci Total Environ. 2022 Sep 10;838(Pt 2):156021. doi: 10.1016/j.scitotenv.2022.156021. Epub 2022 May 16.
9
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10
Propagation of meteorological to hydrological drought for different climate regions in China.气象-水文干旱在中国不同气候区的传播。
J Environ Manage. 2021 Apr 1;283:111980. doi: 10.1016/j.jenvman.2021.111980. Epub 2021 Jan 19.