Abstract:
Drought is a temporary, random and regional climatic phenomenon, originating due to lack of precipitation leading to water
deficit and causing economic loss. Success in drought alleviation depends on how well droughts are defined and their severity
quantified. A quantitative definition identifies the beginning, end, spatial extent and the severity of drought. Among the available
indices, no single index is capable of fully describing all the physical characteristics of drought. Therefore, in most cases it is
useful and necessary to consider several indices, examine their sensitivity and accuracy, and investigate for correlation among
them. In this study, the geographical information system-based Spatial and Time Series Information Modeling (SPATSIM) and
Daily Water Resources Assessment Modeling (DWRAM) software were used for drought analysis on monthly and daily bases
respectively and its spatial distribution in both dry and wet years. SPATSIM utilizes standardized precipitation index (SPI),
effective drought index (EDI), deciles index and departure from long-term mean and median; and DWRAM employs only
EDI. The analysis of data from the Kalahandi and Nuapada districts of Orissa (India) revealed that (a) droughts in this region
occurred with a frequency of once in every 3 to 4 years, (b) droughts occurred in the year when the ratio of annual rainfall
to potential evapotranspiration (Pae/PET) was less than 0Ð6, (c) EDI better represented the droughts in the area than any other
index; (d) all SPI, EDI and annual deviation from the mean showed a similar trend of drought severity. The comparison of
all indices and results of analysis led to several useful and pragmatic inferences in understanding the drought attributes of the
study area. Copyright 2007 John Wiley & Sons, Ltd.