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

U. Surendran (), V. Kumar, S. Ramasubramoniam and P. Raja
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U. Surendran: Water Management (Agriculture) Division, Centre for Water Resources Development and Management
V. Kumar: Tamil Nadu Agricultual University
S. Ramasubramoniam: Indian Space Research Organization
P. Raja: ICAR-Indian Institute of Soil and Water Conservation, Udhagamandalam Research Centre

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2017, vol. 31, issue 11, No 20, 3593-3605

Abstract: Abstract 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.

Keywords: Drought; DrinC; Drought indices; Strategies (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s11269-017-1687-5

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