Multivariate groundwater drought analysis using copulas

被引:0
|
作者
Saghafian, Bahram [1 ]
Sanginabadi, Hamid [1 ]
机构
[1] Department of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
来源
Hydrology Research | 2020年 / 51卷 / 04期
关键词
Drought;
D O I
10.2166/NH.2020.131
中图分类号
学科分类号
摘要
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. © 2020 IWA Publishing. All rights reserved.
引用
收藏
页码:666 / 685
相关论文
共 50 条
  • [41] Estimating Multivariate Discrete Distributions Using Bernstein Copulas
    Fossaluza, Victor
    Esteves, Luis Gustavo
    de Braganca Pereira, Carlos Alberto
    [J]. ENTROPY, 2018, 20 (03)
  • [42] Multivariate frequency analysis of urban rainfall characteristics using three-dimensional copulas
    Liu, Chenglin
    Zhou, Yuwen
    Sui, Jun
    Wu, Chuanhao
    [J]. WATER SCIENCE AND TECHNOLOGY, 2018, (01) : 206 - 218
  • [43] An approach based on multivariate distribution and Gaussian copulas to predict groundwater quality using DNN models in a data scarce environment
    Nafii, Ayoub
    Lamane, Houda
    Taleb, Abdeslam
    El Bilali, Ali
    [J]. METHODSX, 2023, 10
  • [44] A class of multivariate copulas with bivariate Frechet marginal copulas
    Yang, Jingping
    Qi, Yongcheng
    Wang, Ruodu
    [J]. INSURANCE MATHEMATICS & ECONOMICS, 2009, 45 (01): : 139 - 147
  • [45] A class of multivariate copulas based on products of bivariate copulas
    Mazo, Gildas
    Girard, Stephane
    Forbes, Florence
    [J]. JOURNAL OF MULTIVARIATE ANALYSIS, 2015, 140 : 363 - 376
  • [46] Investigating 'risk' of groundwater drought occurrences by using reliability analysis
    Sadeghfam, Sina
    Ehsanitabar, Ali
    Khatibi, Rahman
    Daneshfaraz, Rasoul
    [J]. ECOLOGICAL INDICATORS, 2018, 94 : 170 - 184
  • [47] Geochemical classification of groundwater using multivariate statistical analysis in Latvia
    Retike, Inga
    Kalvans, Andis
    Popovs, Konrads
    Bikse, Janis
    Babre, Alise
    Delina, Aija
    [J]. HYDROLOGY RESEARCH, 2016, 47 (04): : 799 - 813
  • [48] Semiparametric estimation of the error distribution in multivariate regression using copulas
    Kim, Gunky
    Silvapulle, Mervyn J.
    Silvapulle, Paramsothy
    [J]. AUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, 2007, 49 (03) : 321 - 336
  • [49] Construction of asymmetric multivariate copulas
    Liebscher, Eckhard
    [J]. JOURNAL OF MULTIVARIATE ANALYSIS, 2008, 99 (10) : 2234 - 2250
  • [50] Application of Archimedean Copulas to the Analysis of Drought Decadal Variation in China
    Zuo, Dongdong
    Feng, Guolin
    Zhang, Zengping
    Hou, Wei
    [J]. ASIA-PACIFIC JOURNAL OF ATMOSPHERIC SCIENCES, 2018, 54 (02) : 125 - 143