通过干旱指数探测干旱易发地区

Sangita Pawar, Mahesh Shelke, Nikita Kushare
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This has amplified the frequency of droughts or drought-like conditions worldwide. India, being primarily agrarian, faces significant challenges due to drought, affecting various regions intermittently. Given the urgency of addressing recurring drought issues, it is crucial to determine specific ‘drought-prone’ areas through the analysis of historical and current meteorological data. It is still a challenge to quantitatively understand where and to what extent the impact of rainfall patterns could lead the drought. Whether any region likely comes under drought-prone area or not? Can we help policy makers to apply their knowledge effectively? It will help to undertake the long-term mitigation measures for drought assessment and management which encompasses early warning, monitoring, and relief toward the good health of the society. The present study is a further step in the same direction in which Akola district in Maharashtra, India has been assessed for drought-prone declaration using two drought measuring indices; seasonality index (SI) and aridity index (AI). For this, the measured meteorological data precipitation, and potential evapotranspiration, from 1952 to 2002 is made available from India Water Portal.</p>","PeriodicalId":510893,"journal":{"name":"Journal of Water & Climate Change","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Detecting drought-prone regions through drought indices\",\"authors\":\"Sangita Pawar, Mahesh Shelke, Nikita Kushare\",\"doi\":\"10.2166/wcc.2023.590\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div data- reveal-group-><div><img alt=\\\"graphic\\\" data-src=\\\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/jwcc/15/2/10.2166_wcc.2023.590/1/m_jwc-d-23-00590gf01.png?Expires=1712292145&amp;Signature=C7yXbmBzv4aiKKQ4YnpV7zTB8RakWiBTRNXdUM0Oavk-czKWuq05agoGgqVNGtkGbgZmF5ORBmJCL0G0FQt3MZIBnrYJSte9K89AT4HntCdvQVm1TmEMxZUCwbLQCqjcLxpaDsUaXmXjVeR9qay0wY9eZvD7aVusDK-fRaxAubkGBZmWPTBgiQnspt-P~ZvbPuSmdjX4DlVK00Fw22d-Z0xh8BUD1EjGSuPSvos0Z38YZXrdfeYuiftSLSc266ZH7I2YAYL-A8RQKvwtD1pJzwcYZvNtde5W3eTuDrqfkB8ppfmgWHAtYvXLLfzc6JoUmzNcdQ2b6~wOSyKSQ2LG4A__&amp;Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\\\" path-from-xml=\\\"jwc-d-23-00590gf01.tif\\\" src=\\\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/jwcc/15/2/10.2166_wcc.2023.590/1/m_jwc-d-23-00590gf01.png?Expires=1712292145&amp;Signature=C7yXbmBzv4aiKKQ4YnpV7zTB8RakWiBTRNXdUM0Oavk-czKWuq05agoGgqVNGtkGbgZmF5ORBmJCL0G0FQt3MZIBnrYJSte9K89AT4HntCdvQVm1TmEMxZUCwbLQCqjcLxpaDsUaXmXjVeR9qay0wY9eZvD7aVusDK-fRaxAubkGBZmWPTBgiQnspt-P~ZvbPuSmdjX4DlVK00Fw22d-Z0xh8BUD1EjGSuPSvos0Z38YZXrdfeYuiftSLSc266ZH7I2YAYL-A8RQKvwtD1pJzwcYZvNtde5W3eTuDrqfkB8ppfmgWHAtYvXLLfzc6JoUmzNcdQ2b6~wOSyKSQ2LG4A__&amp;Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\\\"/><div>View largeDownload slide</div></div></div><div content- data-reveal=\\\"data-reveal\\\"><div><img alt=\\\"graphic\\\" data-src=\\\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/jwcc/15/2/10.2166_wcc.2023.590/1/m_jwc-d-23-00590gf01.png?Expires=1712292145&amp;Signature=C7yXbmBzv4aiKKQ4YnpV7zTB8RakWiBTRNXdUM0Oavk-czKWuq05agoGgqVNGtkGbgZmF5ORBmJCL0G0FQt3MZIBnrYJSte9K89AT4HntCdvQVm1TmEMxZUCwbLQCqjcLxpaDsUaXmXjVeR9qay0wY9eZvD7aVusDK-fRaxAubkGBZmWPTBgiQnspt-P~ZvbPuSmdjX4DlVK00Fw22d-Z0xh8BUD1EjGSuPSvos0Z38YZXrdfeYuiftSLSc266ZH7I2YAYL-A8RQKvwtD1pJzwcYZvNtde5W3eTuDrqfkB8ppfmgWHAtYvXLLfzc6JoUmzNcdQ2b6~wOSyKSQ2LG4A__&amp;Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\\\" path-from-xml=\\\"jwc-d-23-00590gf01.tif\\\" src=\\\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/jwcc/15/2/10.2166_wcc.2023.590/1/m_jwc-d-23-00590gf01.png?Expires=1712292145&amp;Signature=C7yXbmBzv4aiKKQ4YnpV7zTB8RakWiBTRNXdUM0Oavk-czKWuq05agoGgqVNGtkGbgZmF5ORBmJCL0G0FQt3MZIBnrYJSte9K89AT4HntCdvQVm1TmEMxZUCwbLQCqjcLxpaDsUaXmXjVeR9qay0wY9eZvD7aVusDK-fRaxAubkGBZmWPTBgiQnspt-P~ZvbPuSmdjX4DlVK00Fw22d-Z0xh8BUD1EjGSuPSvos0Z38YZXrdfeYuiftSLSc266ZH7I2YAYL-A8RQKvwtD1pJzwcYZvNtde5W3eTuDrqfkB8ppfmgWHAtYvXLLfzc6JoUmzNcdQ2b6~wOSyKSQ2LG4A__&amp;Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\\\"/><div>View largeDownload slide</div></div><i> </i><span>Close modal</span></div></div><p>Climate change has led to heightened variability in global rainfall patterns, resulting in greater unpredictability and inconsistency, and it has led to the origin of meteorological drought situation. 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引用次数: 0

摘要

查看大尺寸下 载幻灯片查看大尺寸下 载幻灯片 关闭模态气候变化导致全球降雨模式的变异性增加,造成更大的不可预测性和不一致性,并引发了气象干旱状况。这加剧了全球干旱或类似干旱情况的发生频率。印度以农业为主,面临着干旱带来的巨大挑战,干旱时断时续地影响着各个地区。鉴于解决经常性干旱问题的紧迫性,通过分析历史和当前气象数据来确定具体的 "干旱易发 "地区至关重要。要从数量上了解降雨模式会在哪里以及在多大程度上导致干旱,仍然是一项挑战。是否有任何地区可能属于干旱易发区?我们能否帮助决策者有效运用他们的知识?这将有助于在干旱评估和管理方面采取长期的缓解措施,其中包括预警、监测和救助,以促进社会的健康发展。本研究朝同一方向迈进了一步,使用两个干旱测量指数(季节性指数 (SI) 和干旱指数 (AI))对印度马哈拉施特拉邦阿科拉地区进行了干旱易发宣言评估。为此,印度水门户网站提供了 1952 年至 2002 年的降水量和潜在蒸散量气象数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detecting drought-prone regions through drought indices
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Climate change has led to heightened variability in global rainfall patterns, resulting in greater unpredictability and inconsistency, and it has led to the origin of meteorological drought situation. This has amplified the frequency of droughts or drought-like conditions worldwide. India, being primarily agrarian, faces significant challenges due to drought, affecting various regions intermittently. Given the urgency of addressing recurring drought issues, it is crucial to determine specific ‘drought-prone’ areas through the analysis of historical and current meteorological data. It is still a challenge to quantitatively understand where and to what extent the impact of rainfall patterns could lead the drought. Whether any region likely comes under drought-prone area or not? Can we help policy makers to apply their knowledge effectively? It will help to undertake the long-term mitigation measures for drought assessment and management which encompasses early warning, monitoring, and relief toward the good health of the society. The present study is a further step in the same direction in which Akola district in Maharashtra, India has been assessed for drought-prone declaration using two drought measuring indices; seasonality index (SI) and aridity index (AI). For this, the measured meteorological data precipitation, and potential evapotranspiration, from 1952 to 2002 is made available from India Water Portal.

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