Developing Short Term Drought Severity-Duration-Frequency Curves for Kerala Meteorological Subdivision, India Using Bivariate Copulas

Adarsh, S.; Karthik, S.; Shyma, M.; Prem, G. Das; Parveen, A. T. Shirin; Sruthi, Narayan

doi:10.1007/s12205-018-1404-9

Cited by 14 publications

(4 citation statements)

References 39 publications

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“…Similarly, using the 6-month and 3-month SPI timescale, the number of drought events was 181 events for SPI-6 and 174 events for SPI-3 respectively. For the 6-month SPI, six (6) events extremely drought was observed in the years , 2002, 2009, 2014and 2018with a peak intensity in 1993. The most intense drought severity event was S = 22.4139 and had a duration of 32 months (from 1996 to 1999), and considered as the longest drought spell during drought events (Figure 5(b)).…”

Section: Standardized Precipitation Index (Spi) For Various Timescale...mentioning

confidence: 99%

“…The results revealed that higher severities occurred with higher durations and lower severities with shorter durations with respect to increase or decrease in the return period Figure 7(c). Previous studies such as (Sahana et al, 2020;Adarsh et al, 2018 andCavus &Aksoy, 2020) stated that when the return period increases, the drought severity is likely to increase owing to the physical process of the drought.…”

Section: Return Period Of Drought Severity and Duration Using The Bes...mentioning

confidence: 99%

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Meteorological Drought Detection and Forecast Using Standardized Precipitation Index and Univariate Distribution Models: Case Study of Bamako, Mali

Sanogo¹,

Owusu²,

Kabange³

et al. 2023

GEP

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As an extended period of unusually dry weather conditions without sufficient rain, drought poses enormous risk on societies. Characterized by the absence of precipitation for long periods of time, often resulting in water scarcity, droughts are increasingly posing significant environmental challenges. Drought is therefore considered an important element in the management of water resources, especially groundwater resources during drought. This study therefore sought to investigate the rainfall variability and the frequency of drought for the period 1991 to 2020 in Bamako based on monthly rainfall data from Bamako-Senou gauge station. The standardized precipitation index (SPI) for 12-month, 6-month and 3-month timescales and the SPI for annual totals were used to characterized drought in the study area (Bamako). Univariate parametric probability distributions such as Normal, Log-normal, Gumbel type I and Pearson type III (P3) distributions were fitted with drought variables (severity and duration) for future planning and management. Nonparametric test such as Mann-Kendall trend test was also used to detect trend in annual rainfall data. The results showed that based on 12-month SPI, Bamako experienced two (02) extreme droughts one in July 2002 (SPI = −2.2165) and another in June 2015 (SPI = −2.0598). Drought years represented 46.67% for the overall periods according to the SPI for annual totals. The result further indicated that based on the goodness of fit test, the P3 distribution represents the best fitted distribution to both drought severity and duration over Bamako. Bamako is expected to experience several severe severities with higher and shorter duration in the future.

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Section: Standardized Precipitation Index (Spi) For Various Timescale...mentioning

confidence: 99%

Section: Return Period Of Drought Severity and Duration Using The Bes...mentioning

confidence: 99%

Meteorological Drought Detection and Forecast Using Standardized Precipitation Index and Univariate Distribution Models: Case Study of Bamako, Mali

Sanogo¹,

Owusu²,

Kabange³

et al. 2023

GEP

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“…Kerala, located in the southwestern coast of India, is one of the high rainfall‐receiving regions (average annual rainfall of ~300 cm) which is known as “gateway of Indian monsoon.” Hence, the region is having distinctly different climatological conditions, in comparison with other three subdivisions. Many studies reported a reduction in rainfall and consequent signature of droughts, in the state of Kerala (Krishnakumar et al , ; Adarsh and Janga Reddy, ; Thomas and Prasannakumar, ; Adarsh et al , ). In order to investigate the similarity or differences in the multifractal behaviour of the spatially aggregated data and individual station data, the monthly data of 50 stations (for 1983–2016 period) in Kerala operated by IMD is used.…”

Section: Study Areas and Data Setsmentioning

confidence: 99%

Multifractal characterization of meteorological drought in India using detrended fluctuation analysis

Adarsh¹,

Kumar

Deepthi³

et al. 2019

Intl Journal of Climatology

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This study presents multifractal detrended fluctuation analysis (MF-DFA) to describe the multifractality of Standardized Precipitation Index (SPI) series from 30 meteorological subdivisions of India estimated at different aggregation timescales (3, 6 and 12 months) based on long-term monthly rainfall data sets of 1871-2016 period. The plots of fluctuation function and generalized Hurst exponents confirmed that multifractality is evident in most of the SPI series; however, it is found that its strength and persistency differ with timescale and space. The Hurst exponents of long-term (SPI-12) and medium-term (SPI-6) drought series of all subdivisions showed long-term persistence irrespective of the climatic conditions of the region, while the short-term droughts (SPI-3) of six subdivisions displayed short-term persistence. Further, the analysis by partitioning the data to four time spells

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“…The drought characteristics namely severity and duration are extracted with the SPEI values. The analysis of drought characteristics can be executed using either a univariate method or a multivariate method (Adarsh et al, 2018) [1] . The univariate method is a conventional drought frequency analysis approach.…”

Section: Introductionmentioning

confidence: 99%

Meteorological drought analysis using multi-scalar SPEI and Copula theory for Jaisalmer district of Rajasthan, India

Kumar,

Kumar

2023

Int. J. Stat. Appl. Math.

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Drought is a natural disaster of creeping phenomenon which is difficulty to understand. This study utilizes multi-scalar SPEI and copula theory to analyze the meteorological drought in Jaisalmer district of Rajasthan, India. Several marginal distributions are fitted to drought duration and severity. Archimedean and Metaelliptical copulas are used to construct the bivariate probability distributions. The univariate and bivariate return periods are calculated to identify the associate drought risks. The results of this study can provide effective information for the study area to assess drought risk and contribute to the decisionmaking process to reduce the associated risks. This can result in optimizing the allocation of water resources and reduce the impact of drought on the Jaisalmer district in the future.

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Developing Short Term Drought Severity-Duration-Frequency Curves for Kerala Meteorological Subdivision, India Using Bivariate Copulas

Cited by 14 publications

References 39 publications

Meteorological Drought Detection and Forecast Using Standardized Precipitation Index and Univariate Distribution Models: Case Study of Bamako, Mali

Meteorological Drought Detection and Forecast Using Standardized Precipitation Index and Univariate Distribution Models: Case Study of Bamako, Mali

Multifractal characterization of meteorological drought in India using detrended fluctuation analysis

Meteorological drought analysis using multi-scalar SPEI and Copula theory for Jaisalmer district of Rajasthan, India

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