Multivariate groundwater drought analysis using copulas

Drought characteristics are among major inputs in the planning and management of water resources. Although numerous studies on probabilistic aspects of meteorological drought characteristics and their joint distribution functions have been reported, multivariate analysis of groundwater (GW) drought...

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Main Authors: Bahram Saghafian, Hamid Sanginabadi
Format: Article
Language:English
Published: IWA Publishing 2020-08-01
Series:Hydrology Research
Subjects:
Online Access:http://hr.iwaponline.com/content/51/4/666
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spelling doaj-7dede203895c4c28a000f8748ff0733d2020-11-25T03:34:51ZengIWA PublishingHydrology Research1998-95632224-79552020-08-0151466668510.2166/nh.2020.131131Multivariate groundwater drought analysis using copulasBahram Saghafian0Hamid Sanginabadi1 Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran Drought characteristics are among major inputs in the planning and management of water resources. Although numerous studies on probabilistic aspects of meteorological drought characteristics and their joint distribution functions have been reported, multivariate analysis of groundwater (GW) drought is rarely available. In this paper, while proposing a framework for statistical analysis of disturbed hydrological systems, copula-based multivariate GW drought analysis was performed in an over-drafted aquifer. For this purpose, a 1,000-year synthetic time series of naturalized GW level was produced. GW drought was monitored via the Standardized GW Index (SGI) index while the multivariate GW drought probability and return period were determined via copulas. Comparison between the copula and empirical GW drought probabilities using statistical goodness-of-fit tests proved sufficient accuracy of copula models in multivariate drought analysis. The results showed strong dependence among GW drought characteristics. Generally speaking, multivariate GW drought analysis incorporates major drought characteristics and provides concrete scientific basis for planning drought management strategies.http://hr.iwaponline.com/content/51/4/666copulagroundwater droughtmultivariate distributionnaturalized groundwater levelsgi indexsynthetic time series
collection DOAJ
language English
format Article
sources DOAJ
author Bahram Saghafian
Hamid Sanginabadi
spellingShingle Bahram Saghafian
Hamid Sanginabadi
Multivariate groundwater drought analysis using copulas
Hydrology Research
copula
groundwater drought
multivariate distribution
naturalized groundwater level
sgi index
synthetic time series
author_facet Bahram Saghafian
Hamid Sanginabadi
author_sort Bahram Saghafian
title Multivariate groundwater drought analysis using copulas
title_short Multivariate groundwater drought analysis using copulas
title_full Multivariate groundwater drought analysis using copulas
title_fullStr Multivariate groundwater drought analysis using copulas
title_full_unstemmed Multivariate groundwater drought analysis using copulas
title_sort multivariate groundwater drought analysis using copulas
publisher IWA Publishing
series Hydrology Research
issn 1998-9563
2224-7955
publishDate 2020-08-01
description Drought characteristics are among major inputs in the planning and management of water resources. Although numerous studies on probabilistic aspects of meteorological drought characteristics and their joint distribution functions have been reported, multivariate analysis of groundwater (GW) drought is rarely available. In this paper, while proposing a framework for statistical analysis of disturbed hydrological systems, copula-based multivariate GW drought analysis was performed in an over-drafted aquifer. For this purpose, a 1,000-year synthetic time series of naturalized GW level was produced. GW drought was monitored via the Standardized GW Index (SGI) index while the multivariate GW drought probability and return period were determined via copulas. Comparison between the copula and empirical GW drought probabilities using statistical goodness-of-fit tests proved sufficient accuracy of copula models in multivariate drought analysis. The results showed strong dependence among GW drought characteristics. Generally speaking, multivariate GW drought analysis incorporates major drought characteristics and provides concrete scientific basis for planning drought management strategies.
topic copula
groundwater drought
multivariate distribution
naturalized groundwater level
sgi index
synthetic time series
url http://hr.iwaponline.com/content/51/4/666
work_keys_str_mv AT bahramsaghafian multivariategroundwaterdroughtanalysisusingcopulas
AT hamidsanginabadi multivariategroundwaterdroughtanalysisusingcopulas
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