Abstract
Based on the data series location water, Yellow River water, and the South-to-North Water Diversion water which were obtained from 1985 to 2017 in Zhengzhou, China, a joint probability distribution (JPD) model and encounter probability (EP) were established using the optimized t-copula function. The EP was combined, and a risk analysis was performed based on the water shortage situation of each user in different encounters. The results showed that (1) the trivariate JPD could reflect the probability of multisource water supply more precisely than the bivariate JPD; (2) the asynchronous EP was 76.6%, higher than the synchronous EP by 53.2%, indicating that the three water sources were complementary, and the local water exhibited the most significant impact on water supply system in Zhengzhou; and (3) the maximum EP for S1 was 11.7%, all users in S27 experienced varying degrees of water shortage, and the domestic water shortage was (−0.271, −0.33) billion m3. The reservoirs should be converted into joint dispatch, and water rights trading and other water resource management measures should be adopted. The amount of extracted groundwater may be increased if necessary to maintain the urban water supply system.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Explore related subjects
Discover the latest articles and news from researchers in related subjects, suggested using machine learning.References
Cao, G. (2015). Study on the integrated application of information management system of water conservancy and hydropower survey and design based computer. Electron Test. https://doi.org/10.16520/j.cnki.1000-8519.2015.04.040
Chao L, Singh VP, Mishra AK (2013) A bivariate mixed distribution with a heavy-tailed component and its application to single-site daily rainfall simulation. Water Resour Res 49(2). https://doi.org/10.1002/wrcr.20063
Das J, Jha S, Goyal MK (2020) Non-stationary and copula-based approach to assess the drought characteristics encompassing climate indices over the himalayan states in India. J Hydrol 580. https://doi.org/10.1016/j.jhydrol.2019.124356
De Michele C (2003). A generalized pareto intensity-duration model of storm rainfall exploiting 2-copulas. J Geophys Res Atmos 108(D2). https://doi.org/10.1029/2002JD002534
Favre AC, Adlouni SE, Perrault L (2004) Multivariate hydrological frequency using copulas. Water Resour Res 40(12):1–12. https://doi.org/10.1029/2003WR002456
Feng D, Shi B (2003) Inspiration from the successful water transfer project in California, USA. Water Resour Hydropower Express (04). 1–2. https://doi.org/10.15974/j.cnki.slsdkb.2003.04.001
Gao X, Liu Y, Sun B (2018) Water shortage risk assessment considering large-scale regional transfers: a copula-based uncertainty case study in Lunan, China. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-018-2408-1
Gomez EV, Schaalje GB, Fellingham GW (2005) Performance of the Kenward–Roger method when the covariance structure is selected using AIC and BIC. Commun Stat Simul Comput (2). https://doi.org/10.1081/SAC-200055719.
Guo Y, Xiao F (2008) Multivariate hydrological analysis and estimation. Hydrology 03:1–7. https://doi.org/10.3969/j.issn.1000-0852.2008.03.001
Latif S, Mustafa F (2020) Copula-based multivariate flood probability construction: a review. Arab J Geosci. https://doi.org/10.1007/s12517-020-5077-6
Lian J, He W, Ma C, Xu K (2015) Guarantee rate of freshwater in a river mouth intruded by saltwater with respect to the joint impact of runoff and tide. J Hydroinf 17(6):917–929. https://doi.org/10.2166/hydro.2015.038
Lin X (2017) Analysis on the risk of water shortage in irrigation district based on the Copula. (Doctoral dissertation, Zhengzhou University). https://kns.cnki.net/KCMS/detail/detail.aspx?dbname=CMFD201702&filename=1017150509.nh
Li Y, Cui Q, Li C, Wang X, Cai Y, Cui G, Yang Z (2017) An improved multi-objective optimization model for supporting reservoir operation of China’s South-to-North water diversion project. Sci Total Environ 575:970–981. https://doi.org/10.1016/j.scitotenv.2016.09.165
Li Y, Gu W, Cui W et al (2015) Exploration of copula function use in crop meteorological drought risk analysis: a case study of winter wheat in Beijing, China. Nat Hazards (2). https://doi.org/10.1007/s11069-015-1649-2
Lu C, Liu B, Sun Q et al (2016) Analysis of inner and outer flood encounter in north bank area of the huaihe river midstream. J Nat Dis. https://doi.org/10.13577/j.jnd.2016.0103
Lu K (2000) Determination of seasonal water price for irrigation districts and implementation. Rural Water Conserv Hydropower China 000(010):9–10. https://doi.org/10.3969/j.issn.1007-2284.2000.10.005
Pandey PK, Das L, Jhajharia D, Pandey V (2018) Modelling of interdependence between rainfall and temperature using copula. Modell Earth Syst Environ. https://doi.org/10.1007/s40808-018-0454-9
Rauf UFA, Zeephongsekul P (2014) Copula based analysis of rainfall severity and duration: a case study. Theoret Appl Climatol. https://doi.org/10.1007/s00704-013-0877-1
Ren CF, Li RH, Zhang LD, Guo P (2016) Multiobjective stochastic fractional goal programming model for water resources optimal allocation among industries. J Water Resour Plan Manag 142(10):04016036. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000681
Shumilova O, Tockner K, Thieme M, Koska A, Zarfl C (2018) Global water transfer megaprojects: a potential solution for the water-food-energy nexus? Front Environ Sci 6. https://doi.org/10.3389/fenvs.2018.00150
Wu Z, He C, Wang H, Qian Z (2020) Reservoir inflow synchronization analysis for four reservoirs on a mainstream and its tributaries in flood season based on a multivariate copula model. Water Resour Manage 34(9):2753–2770. https://doi.org/10.1007/s11269-020-02572-x
Yuan Z, Xu JJ, Huo JJ, Hong XF (2017) Drought-waterlog encounter probability research between the diversion region and benefited region in the middle route of south-to-north water transfer project. IOP Conference Series: Earth Environ Sci (1). https://doi.org/10.1088/1755-1315/82/1/012044
Zhang J, Lin X, Guo B (2016) Multivariate copula-based joint probability distribution of water supply and demand in irrigation district. Water Resour Manage 30(7):2361–2375. https://doi.org/10.1007/s11269-016-1293-y
Zhang J (2019) Research on potential evaluation and transaction model of inter-regional water right trading in Henan Province. https://kns.cnki.net/KCMS/detail/detail.aspx?dbname=CMFD201902&filename=1019128068.nh
Zhang Q, Wu z, Lv C, Guo X, Gao S (2019) The compensation characteristics of external water supply in Zhengzhou based on copula function. The People’s Yellow River 041(004):37–41. https://doi.org/10.3969/j.issn.1000-1379.2019.04.009
Zhong M, Zeng T, Jiang T, Wu H, Hong Y (2021) A copula-based multivariate probability analysis for flash flood risk under the compound effect of soil moisture and rainfall. Water Resour Manage 35(4):1–16. https://doi.org/10.1007/s11269-020-02709-y
Funding
This work was supported by the National Natural Science Foundation of China [No. 51879239], and the Program for key Science & Technology projects in Universities of Henan Province [No. 21A570008].
Author information
Authors and Affiliations
Contributions
ChenAn: Analyze data, and write drafts; Ming Dou: Research and investigtion, methods, draft revision; Jianling Zhang: Experimental Conjecture Verification, Method; Guiqiu Li: Error checking, draft revision.
Corresponding author
Ethics declarations
Ethics Approval
Not applicable.
Consent to Participate
Consent.
Consent to Publish
Consent.
Competing Interests
The authors declare no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
An, C., Dou, M., Zhang, J. et al. Method for Analyzing Copula-Based Water Shortage Risk in Multisource Water Supply Cities. Water Resour Manage 35, 4877–4894 (2021). https://doi.org/10.1007/s11269-021-02975-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11269-021-02975-4