Multivariate Copula-Based Joint Probability Distribution of Water Supply and Demand in Irrigation District

详细信息    查看全文

• 作者：Jinping Zhang ; Xiaomin Lin ; Bingtuo Guo
• 关键词：Multivariate analysis ; Student t ; copula ; Joint probability distribution ; Water supply and demand ; Water shortage risk
• 刊名：Water Resources Management
• 出版年：2016
• 出版时间：May 2016
• 年：2016
• 卷：30
• 期：7
• 页码：2361-2375
• 全文大小：747 KB
• 参考文献：Ariff NM, Jemain AA, Ibrahim K, Wan Zin WZ (2012) IDF relationships using bivariate copula for storm events in Peninsular Malaysia. J Hydrol 470–471(12):158–171CrossRef
  Dalezios NR, Loukas A, Vasiliades L, Liakopoulos E (2000) Severity-duration –frequency analysis of droughts and wet periods in Greece. Hydrol Sci J 45(5):751–770CrossRef
  Durocher M, Chebana F, Ouarda Taha BMJ (2016) On the prediction of extreme flood quantiles at ungauged locations with spatial copula. J Hydrol 533:523–532CrossRef
  Fan YR, Huang WW, Huang GH, Li YP, Huang K, Li Z (2016) Hydrologic risk analysis in the Yangtze River basin through coupling Gaussian mixtures into copulas. Adv Water Resour 88:170–185CrossRef
  Feng J, Yan DH, Li CHZH, Yu FL, Zhang CH (2014) Assessing the impact of climatic factors on potential evapotranspiration in droughts in North China. Quat Int 336(26):6–12CrossRef
  Froebrich (2013) Short-term rainfall forecasts as a soft adaptation to climate change in irrigation management in North-East India. Water Resour Manag 127:97–106CrossRef
  Fu GT, Butler D (2014) Copula-based frequency analysis of overflow and flooding in urban drainage systems. J Hydrol 10:49–58CrossRef
  Fu DZ, Li YP, Huang GH (2013) A factorial-based dynamic analysis method for reservoir operation under fuzzy-stochastic uncertainties. Water Resour Manag 27(13):4591–4610CrossRef
  Genest C, Favre AC (2007) Everything you always wanted to know about copula modeling but were afraid to ask. J Hydrol Eng 12(4):347–368CrossRef
  Genest C, Ghoudi K, Rivest LP (1995) A semiparametric estimation procedure of dependence parameters in multivariate families of distributions. Biometrika 82(3):543–552CrossRef
  Goel NK, Seth SM, Chandra S (1998) Multivariate modeling of flood flows. J Hydraul Eng 124(2):146–155CrossRef
  Grimaldi S, Serinaldi F (2006) Asymmetric copula in multivariate flood frequency analysis. Adv Water Resour 29:1155–1167CrossRef
  Guttman NB (1998) Comparing the Palmer drought index and the standardized precipitation index. J Am Water Resour Assoc 34(1):113–121CrossRef
  Gyasi-Agyei Y (2012) Use of observed scaled daily storm profiles in a copula based rainfall disaggregation model. Adv Water Resour 45:26–36CrossRef
  Jan R, Broder B, Nikolai S, Winfried S (2016) Modelling regional variability of irrigation requirements due to climate change in Northern Germany. Sci Total Environ 541(15):329–340
  Kalinga-Chirwa R, Ngongondo C, Kalanda-Joshua M, Kazembe L, Pemba D, Kululanga E (2011) Linking rainfall and irrigation to clinically reported malaria cases in some villages in Chikhwawa District, Malawi. Phys Chem Earth 36(14–15):887–894CrossRef
  Kao SHCH, Govindaraju RS (2010) A copula-based joint deficit index for droughts. J Hydrol 380(1–2):121–134CrossRef
  Kurothe RS, Goel NK, Mathur BS (1997) Derived flood frequency distribution of negative correlated rainfall intensity and duration. Water Resour Res 33(9):2103–2107CrossRef
  Kushan CP, Andrew WW, Bandara N, Biju G (2014) Forecasting daily reference evapotranspiration for Australia using numerical weather prediction outputs. Agric For Meteorol 194(15):50–63
  Luis SP, Paula P, Gonçalo CR, Manuela N (2015) Modeling malt barley water use and evapotranspiration partitioning in two contrasting rainfall years. Assessing AquaCrop and SIMDualKc models. Agric Water Manag 159:239–254CrossRef
  Masina M, Lamberti A, Archetti R (2015) Coastal flooding: a copula based approach for estimating the joint probability of water levels and waves. Coast Eng 97:37–52CrossRef
  Moazami S, Golian S, Kavianpour MR, Hong Y (2014) Uncertainty analysis of bias from satellite rainfall estimates using copula method. Atmos Res 137:145–166CrossRef
  Neung-Hwan O, Brian AP, Bachand PAM, Peter JH, Sandra MB, Noriaki O, Levent Kavvas M, Brian AB, William RH (2013) The role of irrigation runoff and winter rainfall on dissolved organic carbon loads in an agricultural watershed. Agric Ecosyst Environ 179(1):1–10
  Paulo AA, Pereira LS (2007a) Prediction of SPI drought class transitions using markov chains. Water Resour Manag 21(10):1813–1827CrossRef
  Paulo AA, Pereira LS (2007b) Stochastic prediction of SPI drought class transition. Water Resour Manag 22:1277–1527CrossRef
  Salvadori G, Michele CD (2015) Multivariate real-time assessment of droughts via copula-based multi-site Hazard Trajectories and Fans. J Hydrol 526:101–115CrossRef
  Serinaldi F, Grimaldi S, Napolitano F, Ubertini L (2004) A 3-coptula function application to flood frequency analysis. In: proceedings of the IASTED international conference environmental modeling and simulation, St. Thomas, US Virgin Islands, November 22–24: 202–206
  Seyed AB, Davar K (2013) Factors influencing markov chains predictability characteristics, utilizing SPI, RDI, EDI and SPEI drought indices in different climatic zones. Water Resour Manag 27(11):3911–3928CrossRef
  Shiau JT (2006) Fitting drought duration and severity with two-dimensional copulas. Water Resour Manag 20:795–815CrossRef
  Sklar A (1959) Fonctions de repartition an dimensions et leurs marges. Publ Inst Stat Univ Paris 8(1):11–12
  Tabrizi AA, Khalili D, Kamgar-Haghighi AA, Zand-Parsa S (2010) Utilization of time-based meteorological droughts to investigate occurrence of stramflow droughts. Water Resour Manag 24:4287–4306CrossRef
  Tao XE, Chen H, Xu CHY, Hou YK, Jie MX (2015) Analysis and prediction of reference evapotranspiration with climate change in Xiangjiang River Basin, China. Water Sci Eng 8(4):273–281CrossRef
  Vangelis H, Spiliotis M, Tsakiris G (2011) Drought severity assessment based on bivariate probability analysis. Water Resour Manag 25:357–371CrossRef
  Wang F, Hessel R, Mu XM, Maroulis J, Zhao GJ, Geissen V, Coen R (2015) Distinguishing the impacts of human activities and climate variability on runoff and sediment load change based on paired periods with similar weather conditions: a case in the Yan River. China J Hydrol 527:884–893CrossRef
  Xu K, Yang DW, Xu XY, Lei HM (2015) Copula based drought frequency analysis considering the spatio-temporal variability in Southwest China. J Hydrol 527:630–640CrossRef
  Yue S (1999) Applying bivariate normal distribution to flood frequency analysis. Water Int 24(3):248–254CrossRef
  Yue S (2000) Joint probability distribution of annual maximum storm peaks and amounts as represented by daily rainfalls. Hydrol Sci J 45(2):315–326CrossRef
  Yue S, Rasmussen P (2002) Bivariate frequency analysis: discussion of some useful concepts for hydrological application. Hydrol Process 16(14):811–819CrossRef
  Zhang L, Singh VP (2007) Bivariate rainfall frequency distributions using Archimedean copulas. J Hydrol 332:93–109CrossRef
  Zhang JP, Zhao Y, Xiao WH (2014) Study on markov joint transition probability and encounter probability of rainfall and reference crop evapotranspiraton in the irrigation district. Water Resour Manag 28:5543–5553CrossRef
  Zhang KX, Pan SHM, Zhang W, Xu YH, Cao LG, Hao YP, Wang Y (2015) Influence of climate change on reference evapotranspiration and aridity index and their temporal-spatial variations in the Yellow River Basin, China, from 1961 to 2012. Quat Int 380–381(4):75–82CrossRef
  Zhao YF, Zou XQ, Zhang JX, Cao LG, Xu XW, Zhang KX, Chen YY (2014) Spatio-temporal variation of reference evapotranspiration and aridity index in the Loess Plateau Region of China, during 1961–2012. Quat Int 349(28):196–206CrossRef
  
• 作者单位：Jinping Zhang (1)
  Xiaomin Lin (1)
  Bingtuo Guo (2)
  
  1. Institute of Water Resources and Environment, Zhengzhou University, High-tech District, No. 100 Science Road, Zhengzhou City, 450001, Henan Province, China
  2. Yellow River Engineering Consulting Co. Ltd., Zhengzhou, 450003, China
  
• 刊物类别：Earth and Environmental Science
• 刊物主题：Earth sciences
  Hydrogeology
  Geotechnical Engineering
  Meteorology and Climatology
  Civil Engineering
  Environment
  
• 出版者：Springer Netherlands
• ISSN：1573-1650

文摘

Based on the data series of rainfall, reference crop evapotranspiration and irrigation water from 1970 to 2013 in the Luhun irrigation district of China, the multivariate joint probability of water supply and demand are constructed with student t-copula function. The results show that student t-copula function can indicate the associated dependence structure amongst these variables well, and the constructed multivariate copula-based joint probability distribution reveal the statistical characteristics and occurrence probability of different combinations of water supply and water demand. Moreover, the trivariate joint probability distribution is more reasonable than the bivariate distribution to reflect the water shortage risk, and these joint distribution values of different combinations of water supply and demand can provide the technological support for water shortage risk evaluation in the irrigation district.