Assessment of dynamic hydrological drought risk from a non-stationary perspective

被引:0
|
作者
Chen, Chen [1 ,2 ]
Peng, Tao [1 ,2 ]
Singh, Vijay P. [3 ,4 ,5 ]
Wang, Youxin [1 ,2 ]
Zhang, Te [6 ]
Dong, Xiaohua [1 ,2 ]
Lin, Qingxia [1 ,2 ]
Guo, Jiali [1 ,2 ]
Liu, Ji [1 ]
Fan, Tianyi [7 ]
Wang, Gaoxu [8 ]
机构
[1] China Three Gorges Univ, Hubei Prov Key Lab Construction & Management Hydro, Yichang, Hubei, Peoples R China
[2] China Three Gorges Univ, Engn Res Ctr Ecoenvironm Three Gorges Reservoir Re, Minist Educ, Yichang, Hubei, Peoples R China
[3] Texas A&M Univ, Dept Biol & Agr Engn, College Stn, TX USA
[4] Texas A&M Univ, Zachry Dept Civil & Environm Engn, College Stn, TX USA
[5] UAE Univ, Natl Water & Energy Ctr, Al Ain, U Arab Emirates
[6] Northwest A&F Univ, Coll Water Resources & Architectural Engn, Yangling, Shaanxi, Peoples R China
[7] Hunan Prov Water Resources & Hydropower Survey Des, Changsha, Hunan, Peoples R China
[8] Nanjing Hydraul Res Inst, State Key Lab Hydrol Water Resources & Hydraul Eng, Nanjing, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
dynamic copula; GAMLSS; hydrological drought; non-stationary standardized runoff index; risk assessment; FLOOD FREQUENCY; RIVER-BASIN; RESERVOIR INDEXES; CLIMATE INDEXES; PRECIPITATION; STATIONARITY; VARIABILITY; DESIGN; MODELS; SERIES;
D O I
10.1002/hyp.15267
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
The stationarity hypothesis of hydrometeorological elements has been questioned in the context of global warming and intense human disturbance. The conventional drought index and methods of frequency analysis may no longer be applicable for hydrological drought risk evaluation under a changing environment. In this study, a new dynamic hydrological drought risk evaluation framework is proposed for application to the Hanjiang River basin (HRB), which simultaneously considers the non-stationarity in the construction of drought index as well as in the frequency analysis. First, a non-stationary standardized runoff index (NSRI) is developed using a generalized additive model for location, scale and shape (GAMLSS) framework. Then, hydrological drought characteristics including duration and severity are identified, and their marginal distributions are established. Finally, based on the dynamic copula, considering the non-stationarity of the dependence structure, the dynamic joint probability distribution, conditional probability distribution and return period of the bivariate hydrological drought properties are analysed. Results showed that NSRI, which integrates the impacts of climate change and anthropogenic activities on the non-stationarity of runoff series, had a better ability to capture runoff extremes than had SRI. In addition, it is indispensable to consider the non-stationarity of the dependence structure between variables when discussing the multivariate joint risk of hydrological drought. The risk of hydrological drought in the study area has shown an increasing trend in the past 65 years, and the drought conditions from upstream to downstream have been alleviated first and then intensified. This study provides valuable information for regional drought risk estimation and water resources management from a non-stationary perspective. The NSRI constructed using a log-normal function with non-linear changes in location parameters with CI and MRI, as well as scale parameters with non-linear variation in CI, had better ability to characterize extreme runoff values than the conventional SRI. For multivariate risk assessment of hydrological drought, it is necessary to consider the non-stationarity in the dependence structure of variables. The hydrological drought risk in the HRB has increased in recent decades. image
引用
收藏
页数:17
相关论文
共 50 条
  • [41] Solutions of Non-stationary Dynamic Problems of Linear Viscoelasticity
    Korovaytseva, E. A.
    Pshenichnov, S. G.
    LOBACHEVSKII JOURNAL OF MATHEMATICS, 2019, 40 (03) : 328 - 334
  • [42] Testing for autocorrelation in non-stationary dynamic systems of equations
    Hussain, S
    Shukur, G
    JOURNAL OF APPLIED STATISTICS, 2003, 30 (04) : 441 - 454
  • [43] Dynamic modelling for non-stationary bearing vibration signals
    Galli, Federica
    Sircoulomb, Vincent
    Fiore, Giuseppe
    Hoblos, Ghaleb
    Weber, Philippe
    2023 31ST MEDITERRANEAN CONFERENCE ON CONTROL AND AUTOMATION, MED, 2023, : 49 - 54
  • [44] Non-stationary dynamic structural response to thunderstorm outflows
    Ciano, Matteo
    Gioffre, Massimiliano
    Gusella, Vittorio
    Grigoriu, Mircea Dan
    PROBABILISTIC ENGINEERING MECHANICS, 2020, 62
  • [45] Tracking non-stationary appearances and dynamic feature selection
    Yang, M
    Wu, Y
    2005 IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOL 2, PROCEEDINGS, 2005, : 1059 - 1066
  • [46] Sequential non-stationary dynamic classification with sparse feedback
    Lowne, D. R.
    Roberts, S. J.
    Garnett, R.
    PATTERN RECOGNITION, 2010, 43 (03) : 897 - 905
  • [47] A Time-Dependent Drought Index for Non-Stationary Precipitation Series
    Yixuan Wang
    Jianzhu Li
    Ping Feng
    Rong Hu
    Water Resources Management, 2015, 29 : 5631 - 5647
  • [48] Dynamic Power Management for non-stationary service requests
    Chung, EY
    Benini, L
    Bogliolo, A
    De Micheli, G
    DESIGN, AUTOMATION AND TEST IN EUROPE CONFERENCE AND EXHIBITION 1999, PROCEEDINGS, 1999, : 77 - 81
  • [49] A Time-Dependent Drought Index for Non-Stationary Precipitation Series
    Wang, Yixuan
    Li, Jianzhu
    Feng, Ping
    Hu, Rong
    WATER RESOURCES MANAGEMENT, 2015, 29 (15) : 5631 - 5647
  • [50] Improved non-stationary SPEI and its application in drought monitoring in China
    Zhang, Qiang
    Wang, Danzhou
    Feng, Anlan
    Wang, Gang
    Hu, Lei
    Xu, Chong-Yu
    Singh, Vijay P.
    JOURNAL OF HYDROLOGY, 2025, 652