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Development of Drought Indices for Semi-Arid Region Using Drought Indices Calculator (DrinC) - A Case Study from Madurai District, a Semi-Arid Region in India

机译:使用干旱指数计算器(DrinC)开发半干旱地区的干旱指数-以印度半干旱地区的马杜赖地区为例

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摘要

Drought is considered as a major natural hazard/disaster, affecting several sectors of the economy and the environment worldwide. Drought, a complex phenomenon can be characterised by its severity, duration, and areal extent. Drought indices for the characterization and the monitoring of drought simplify the complex climatic functions and can quantify climatic anomalies for their severity, duration, and frequency. With this as background drought indices were worked out for Madurai district of Tamil Nadu using DrinC (Drought Indices Calculator) software. DrinC calculates the drought indices viz., deciles, Standard Precipitation Index (SPI), Reconnaissance Drought Index (RDI), Streamflow Drought Index (SDI) by providing a simple, though flexible interface by considering all the factors. The drought of 3, 6 and 9 months as time series can also be estimated. The results showed that drought index of Madurai region by decile method revealed that among the 100 years, 20 years were affected by drought and it is cyclic in nature and occurring almost every 3 to 7 years once repeatedly, except for some continuous period, i.e., 1923, 1924 and 1985, 1986, etc. During the last five decades, the incidence is higher with 13 events, whereas in the first five decades it was only 7. The SPI and RDI index also followed the similar trend of deciles. However, under SPI and RDI, the severely dry and extremely dry category was only seven years and all other drought years of deciles were moderately dry. Our study indicated that SPI is a better indicator than deciles since here severity can be understood. SDI did not follow the trend similar to SPI or RDI. Regression analysis showed that the SPI and RDI are significantly correlated and if 1st 3 months rainfall data is available one can predict yearly RDI drought index. The results demonstrated that these approaches could be useful for developing preparedness plan to combat the consequences of drought. Findings from such studies are useful tools for devising strategic preparedness plans to combat droughts and mitigate their effects on the activities in the various sectors of the economy.
机译:干旱被认为是主要的自然灾害/灾害,影响到世界范围内的经济和环境的多个部门。干旱是一种复杂现象,其严重性,持续时间和面积范围都可以表征。用于表征和监测干旱的干旱指数可简化复杂的气候功能,并可量化其异常程度,持续时间和频率的气候异常。以此为背景,使用DrinC(干旱指数计算器)软件为泰米尔纳德邦马杜赖区确定了干旱指数。通过考虑所有因素,DrinC通过提供简单但灵活的界面来计算干旱指数,即十分位数,标准降水指数(SPI),侦察干旱指数(RDI),水流干旱指数(SDI)。还可以估计3、6和9个月的干旱时间序列。结果表明,采用十分位数法对马杜赖地区的干旱指数显示,在100年中,20年受到干旱的影响,它是周期性的,几乎每3至7年发生一次,除了一些连续的时期,即1923、1924和1985、1986等。在过去的五个十年中,发生率较高,有13个事件,而在最初的五个十年中,发生率仅为7个事件。SPI和RDI指数也遵循类似的趋势。但是,在SPI和RDI下,极度干旱和极度干旱类别只有7年,而其他干旱年份的十分之多则属于中等干旱。我们的研究表明,SPI是比十进制更好的指标,因为可以理解此处的严重性。 SDI没有遵循类似于SPI或RDI的趋势。回归分析表明,SPI和RDI显着相关,如果有第一个3个月的降雨数据,则可以预测RDI的年度干旱指数。结果表明,这些方法可能有助于制定应对干旱后果的备灾计划。这些研究的结果是制定战略性备灾计划以抗旱并减轻其对经济各部门活动影响的有用工具。

著录项

  • 来源
    《Water Resources Management》 |2017年第11期|3593-3605|共13页
  • 作者单位

    Ctr Water Resources Dev & Management, Water Management Agr Div, Kozhikode, Kerala, India;

    Tamil Nadu Agr Univ, Agr Coll & Res Inst, Madurai Campus, Coimbatore, Tamil Nadu, India;

    Indian Space Res Org, Reg Remote Sensing Ctr, Bangalore, Karnataka, India;

    ICAR Indian Inst Soil & Water Conservat, Udhagamandalam Res Ctr, Coimbatore, Tamil Nadu, India;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Drought; DrinC; Drought indice; Strategies;

    机译:干旱;DrinC;干旱指数;策略;

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