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METEOROLOGICAL DROUGHT ANALYSIS USING COPULA FUNCTION FOR MARATHWADA REGION, MAHARASHTRA STATE, INDIA

By: Contributor(s): Publication details: Roorkee Indian Water Resources Society 2021Edition: Vol, 41(2), AprDescription: 20-27pSubject(s): Online resources: In: Journal of indian water resource societySummary: Drought is an extreme climatic event, which is recurring in nature. Drought occurs when the amount of precipitation is less than average precipitation for the region. Drought analysis is important due to its direct impact on water supply, agriculture and industry along with social and economic impact.Duration and severity are major characteristics of drought. In this study, the bivariate joint distribution of drought duration and severity is defined using bivariate copula function. 6-month Standardized Precipitation Index (SPI) is used to calculate drought duration and severity for average precipitation of the whole study area. The logistic and Birnbaum-saunders distributions are best fitted distribution for univariate frequency analysis of drought duration and severity. Student ‘t’, Galambos, Clayton, Gumbel, Frank, AMH copula functions are used to find joint multivariate distribution. AIC, RMSE and NSE values are used to select the best fit copula function. Considering AIC, RMSE, NSE values and the dependence structure i.e closeness of isolines, the Galambos copula is found to be the best fit for time series data. Drought analysis is carried out using joint probability distribution between drought duration and severity. Drought risk is estimated based on a joint return period which gives important information for water resource planning and management.
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Drought is an extreme climatic event, which is recurring in nature. Drought occurs when the amount of precipitation is less than average
precipitation for the region. Drought analysis is important due to its direct impact on water supply, agriculture and industry along with
social and economic impact.Duration and severity are major characteristics of drought. In this study, the bivariate joint distribution of
drought duration and severity is defined using bivariate copula function. 6-month Standardized Precipitation Index (SPI) is used to calculate
drought duration and severity for average precipitation of the whole study area. The logistic and Birnbaum-saunders distributions are best
fitted distribution for univariate frequency analysis of drought duration and severity. Student ‘t’, Galambos, Clayton, Gumbel, Frank, AMH
copula functions are used to find joint multivariate distribution. AIC, RMSE and NSE values are used to select the best fit copula function.
Considering AIC, RMSE, NSE values and the dependence structure i.e closeness of isolines, the Galambos copula is found to be the best fit
for time series data. Drought analysis is carried out using joint probability distribution between drought duration and severity. Drought risk
is estimated based on a joint return period which gives important information for water resource planning and management.

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