Citation

Vaani N, Porchelvan P. Disaster Adv. 2017; 10(1): 1-10.

Copyright

(Copyright © 2017, Shankar Gargh)

DOI

unavailable

PMID

unavailable

Abstract

The study of long term meteorological drought for monsoon dependent countries like India is very essential for planners and policy makers to develop various strategies to improve the agricultural productivity in future. In recent years, an average of nine farmer suicides per day is reported which indicates the severity of the problem due to increasing drought prone areas in India. Spatio-temporal analysis of meteorological drought for Tamilnadu state in India was attempted in the present study using one of the widely used indices called Standard Precipitation Index (SPI) with 30 years of rainfall data (1980-2009) as input and year wise drought intensity maps were prepared using Geographic Information Systems (GIS). It was found that the year 2002 is the worst affected year as more than 20 districts have experienced extreme drought conditions due to insufficient rainfall. It was noticed from drought intensity maps that extreme drought conditions do not occur all of a sudden in one year and occurs over a period of at least 2-3 years. This necessitates the government to be alert and to take suitable preventive measures whenever the trace of severe or extreme drought conditions is felt in a year. Modelling of SPI using rainfall deviation as independent variable was also attempted using regression analysis as strong positive correlation exists between SPI and rainfall deviation with Pearson's correlation coefficient of above 0.98 was obtained for most of the districts. Second order and third order polynomial models were fitted for various districts and state respectively with R2 values of above 0.8. The developed regression models can be used to determine well in advance, the district wise or state as a whole, the level of dryness or wetness in future years which will facilitate planners and policy makers to take suitable steps for drought preparedness and mitigation. © 2017, Disaster Advances. All rights reserved.

Language: en

Keywords

Drought intensity maps; Geographic Information Systems (GIS); Meteorological drought; Rainfall deviation; Regression analysis; Standard Precipitation Index (SPI)