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The risks assessment via a regional approach using multivariate regional frequency clustering method

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Abstract

Conventional univariate drought frequency analysis should be replaced by the multivariate framework due to the correlated characteristics, such as duration, peak intensity, and severity. Compared to the bivariate case, trivariate analysis would be more considerable. Furthermore, the absence of historical records has a great impact on the reliability of statistical estimates. Multivariate regional frequency analysis approach would be a better choice for providing reliable information for risks assessment and management purpose. Standardized precipitation evapotranspiration index was used in this study to define and detect drought because of the global warming effect. A method based on the cubic spline interpolation was applied to derive drought samples. Applying the multivariate discordancy and homogeneity test, the Pearl River basin was divided into five homogeneous subregions. Regional distributions including marginal distribution and copula function were chosen based on the goodness-of-fit test. Finally, return periods were computed from a regional perspective to assess the different drought risks. The results indicate that high drought risks might exist in the Pearl River basin and the spatial distinction must be taken seriously. Due to the contradiction of water supply and requirement among different districts or provinces, policies needed to be made seriously and urgently to solve the unbalance between water resource and socioeconomic development.

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References

  1. Wilhite, D.A., Glantz, M.H.: Understanding the drought phenomenon: the role of definitions. Water Int. 10, 111–120 (1985)

    Article  Google Scholar 

  2. Sönmez, F.K., Ümran-Kömüscü, A., Erkan, A., Turgu, E.: An analysis of spatial and temporal dimension of drought vulnerability in Turkey using the standardized precipitation index. Nat. Hazards 35, 243–264 (2005). doi:10.1007/s11069-004-5704-7

    Article  Google Scholar 

  3. McKee, T.B., Doeskin, N.J., Klerst, J.: The relationship of drought frequency and duration to time scales. In: Proceedings of the 8th Conference on Applied Climatology, January 17–22, Anaheim, California, pp. 179–184 (1993)

  4. Lloyd-Hughes, B., Saunders, M.A.: A drought climatology for Europe. Int. J. Climatol. 22, 1571–1592 (2002). doi:10.1002/joc.846

    Article  Google Scholar 

  5. Mishra, A.K., Singh, V.P.: A review of drought concepts. J. Hydrol. 391, 202–216 (2010)

    Article  Google Scholar 

  6. Kampragou, E., Apostolaki, S., Manoli, E., Froebrich, J., Assimacopoulos, D.: Towards the harmonization of water-related policies for managing drought risks across the EU. Environ. Sci. Policy 14(7), 815–824 (2011)

    Article  Google Scholar 

  7. Zou, X., Zhai, P., Zhang, Q.: Variations in drought over China: 1951–2003. Geophys. Res. Lett. 32, L04707 (2005). doi:10.1029/2004GL021853

    Google Scholar 

  8. Le Comete, D.: Weather highlights around the world. Weatherwise 47, 23–26 (1994)

    Article  Google Scholar 

  9. Le Comete, D.: Weather highlights around the world. Weatherwise 48, 20–22 (1995)

    Article  Google Scholar 

  10. Ross, T., Lott, N.: A Climatic of 1980–2003 Extreme Weather and Climate Events. National Climatic Data Center, Asheville, NC. http://www.ncdc.noaa.gov/ol/reports/billionz.html (2003)

  11. Bond, N.R., Lake, P.S., Arthington, A.H.: The impacts of drought on freshwater ecosystems: an Australian perspective. Hydrobiologia 600(1), 3–16 (2008)

    Article  Google Scholar 

  12. Shiau, J.T.: Fitting drought duration and severity with two-dimensional copulas. Water Resour. Manag. 20(5), 795–815 (2006)

    Article  Google Scholar 

  13. Yue, S.: Applying bivariate normal distribution to flood frequency analysis. Water Int. 24(3), 248–254 (1999)

    Article  Google Scholar 

  14. Favre, A.-C., Musy, A., Morgenthaler, S.: Two-site modeling of rainfall based on the Neyman–Scott process. Water Resour. Res. 38(12), 1307 (2002). doi:10.1029/2002WR001343

    Article  Google Scholar 

  15. Yue, S., Ouarda, T.B.M.J., Bobée, B.: A review of bivariate gamma distribution for hydrological application. J. Hydrol. 246, 1–18 (2001)

    Article  Google Scholar 

  16. Adamson, P.T., Metcalfe, A.V., Parmentier, B.: Bivariate extreme value distributions: an application of the Gibbs sampler to the analysis of floods. Water Resour. Res. 35, 2825–2832 (1999)

    Article  Google Scholar 

  17. Favre, A.-C., Adlouni, S.E., Perreault, L., Thiémonge, N., Bobée, B.: Multivariate hydrological frequency analysis using copulas. Water Resour. Res. 40, W01101 (2004). doi:10.1029/2003WR002456

    Article  Google Scholar 

  18. Yevjevich, V.M.: An objective approach to definitions and investigations of continential hydrologic drought. Hydrology Paper 23, Colorado (1967)

  19. Shiau, J.T., Feng, S., Nadarajah, S.: Assessment of hydrological droughts for the Yellow River, China, using copulas. Hydrol. Process. 21(16), 2157–2163 (2007)

    Article  Google Scholar 

  20. Mirabbasi, R., Fakheri-Fard, A., Dinpashoh, Y.: Bivariate drought frequency analysis using the copula method. Theor. Appl. Climatol. (2011). doi:10.1007/s00704-011-0524-7

    Google Scholar 

  21. Ganguli, P., Reddy, M.J.: Risk assessment of droughts in Gujarat using bivariate copulas. Water Resour. Manag. 26, 3301–3327 (2012)

    Article  Google Scholar 

  22. González, J., Valdés, J.: Bivariate drought recurrence analysis using tree ring reconstructions. J. Hydrol. Eng. 8(5), 247–258 (2003)

    Article  Google Scholar 

  23. Serinaldi, F., Grimaldi, S.: Fully nested 3-copula: procedure and application on hydrological data. J. Hydrol. Eng. 12(4), 420–430 (2007)

    Article  Google Scholar 

  24. Ganguli, P., Reddy, M.J.: Probabilistic assessment of flood risks using trivariate copulas. Theor. Appl. Climatol. 111, 341–360 (2013)

    Article  Google Scholar 

  25. Zhang, L., Singh, V.P.: Gumbel–Hougaard copula for trivariate rainfall frequency analysis. J. Hydrol. Eng. 12(4), 409–419 (2007)

    Article  Google Scholar 

  26. Kao, S.-C., Govindaraju, R.S.: Trivariate statistical analysis of extreme rainfall events via the Plackett family of copulas. Water Resour. Res. 44, W02415 (2008). doi:10.1029/2007WR006261

    Article  Google Scholar 

  27. Wong, G., Lambert, M.F., Leonard, M., Metcalfe, A.V.: Drought analysis using trivariate copulas conditional on climatic states. J. Hydrol. Eng. 15(2), 129–141 (2010)

    Article  Google Scholar 

  28. Song, S.B., Singh, V.P.: Frequency analysis of drought using the Plackett copula and parameter estimation by genetic algorithm. Stoch. Environ. Res. Risk Assess. 24, 783–805 (2010)

    Article  Google Scholar 

  29. Ma, M.W., Song, S.B., Ren, L.L., Jiang, S.H., Song, J.L.: Multivariate drought characteristics using trivariate Gaussian and Student t copula. Hydrol. Process. 27(8), 1175–1190 (2012)

    Article  Google Scholar 

  30. Kite, G.W.: Frequency and Risk Analysis in Hydrology. Water Resources Publications, Littleton (1988)

    Google Scholar 

  31. Hosking, J.R.M., Wallis, J.R.: Some statistics useful in regional frequency analysis. Water Resour. Res. 29, 271–281 (1993)

    Article  Google Scholar 

  32. Hosking, J.R.M., Wallis, J.R.: Regional Frequency Analysis: An Approach Based on L-Moments. Cambridge University Press, Cambridge (1997)

    Book  Google Scholar 

  33. Mirakbari, M., Ganji, A., Fallah, S.R.: Regional bivariate frequency analysis of meteorological droughts. J. Hydrol. Eng. 15(12), 985–1000 (2010)

    Article  Google Scholar 

  34. Yoo, J.Y., Kwon, H.-H., Kim, T.-W., Ahn, J.-H.: Drought frequency analysis using cluster analysis and bivariate probability distribution. J. Hydrol. 420–421, 102–111 (2012)

    Article  Google Scholar 

  35. Chebana, F., Ouarda, T.B.M.J.: Multivariate L-moment homogeneity test. Water Resour. Res. 43, W08406 (2007). doi:10.1029/2006WR005639

    Article  Google Scholar 

  36. Chebana, F., Ouarda, T.B.M.J.: Index flood-based multivariate regional frequency analysis. Water Resour. Res. 45, W10435 (2009). doi:10.1029/2008WR007490

    Article  Google Scholar 

  37. Zhang, Q., Singh, V.P., Peng, J.T., Chen, Y.Q., Li, J.F.: Spatial-temporal changes of precipitation structure across the Pearl River basin, China. J. Hydrol. 440–441(10), 113–122 (2012)

    Article  Google Scholar 

  38. Yan, Q.: Drought, highlights the contradiction between supply and demand of water resources in the Pearl River basin. Pearl River Water Resources Commission, Ministry of Water Resources of China. http://www.zwsw.gov.cn/zjls/13680.shtml (2009)

  39. Gemmer, M., Fischer, T., Su, B., Liu, L.L.: Trends of precipitation extremes in the Zhujiang River basin, south China. J. Clim. 24, 750–761 (2011)

    Article  Google Scholar 

  40. Zargar, A., Sadiq, R., Naser, B., Khan, F.I.: A review of drought indices. Environ. Rev. 19, 333–349 (2011)

    Article  Google Scholar 

  41. Guttman, N.B.: Comparing the Palmer drought index and the standardized precipitation index. J. Am. Water Resour. Assoc. 34(1), 113–121 (1998)

    Article  MathSciNet  Google Scholar 

  42. IPCC: Climate Change: The Physical Science Basis. Cambridge University Press, Cambridge (2007)

  43. Cai, W., Cowan, T.: Evidence of impacts from rising temperature on inflows to the Murray–Darling basin. Geophys. Res. Lett. (2008). doi:10.1029/2008GL033390

  44. Koutroulis, A.G., Tsanis, I.K., Daliakopoulos, I.N., Jacob, D.: Impact of climate change on water resources status: a case study for Crete Island, Greece. J. Hydrol. 479(13), 146–158 (2013)

    Article  Google Scholar 

  45. Vicente-Serrano, S.M., Beguería, S., López-Moreno, J.I.: A multi-scalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index SPEI. J. Clim. 23, 1696–1718 (2010)

    Article  Google Scholar 

  46. Thornthwaite, C.W.: An approach toward a rational classification of climate. Geogr. Rev. 38(1), 55–94 (1948)

    Article  Google Scholar 

  47. Kao, S.-C., Govindaraju, R.S.: A copula-based joint deficit index for droughts. J. Hydrol. 380(1), 121–134 (2010)

    Article  Google Scholar 

  48. Svoboda, M., LeComte, D., Hayes, M., Heim, R., Gloeason, K., Angel, J., Rippey, B., Tinker, R., Palecki, M., Stooksbury, D., Stephens, S.: The drought monitor. Bull. Am. Meteorol. Soc. 83(8), 1181–1190 (2002)

    Article  Google Scholar 

  49. Angrew, C.T.: Using SPI to identify drought. Drought Netw. News 12, 6–12 (2000)

    Google Scholar 

  50. Santos, J.F., Pulido-Calvo, I., Portela, M.M.: Spatial and temporal variability of droughts in Portugal. Water Resour. Res. 46, W03503 (2010). doi:10.1029/2009WR008071

    Article  Google Scholar 

  51. Nelson, R.B.: An Introduction to Copulas, 2nd edn. Springer, New York (2006)

    Google Scholar 

  52. Sklar, A.: Fonctionsdé repartition àn dimensions et leurs margins. Publ. Inst. Statist. Univ. Paris 8, 229–231 (1959)

    MathSciNet  Google Scholar 

  53. Grimaldi, S., Serinaldi, F.: Asymmetric copula in multivariate flood frequency analysis. Adv. Water Resour. 29(8), 1155–1167 (2006)

    Article  Google Scholar 

  54. Genest, C., Rivest, L.-P.: On the multivariate probability integral transformation. Stat. Probab. Lett. 53(4), 391–399 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  55. Salvadori, G., De Michele, C., Durante, F.: On the return period and design in a multivariate framework. Hydrol. Earth Syst. Sci. 15, 3293–3305 (2011)

    Article  Google Scholar 

  56. Salvadori, G., De Michele, C.: Frequency analysis via copulas: theoretical aspects and applications to hydrological events. Water Resour. Res. 40, W12511 (2004). doi:10.1029/2004WR003133

    Article  Google Scholar 

  57. Hosking, J.R.M.: L-Moments: analysis and estimation of distributions using linear combinations of order statistics. J. R. Stat. Soc. B 52(1), 105–124 (1990)

    MATH  MathSciNet  Google Scholar 

  58. Serfling, R., Xiao, P.: A contribution to multivariate L-moments: L-moment matrices. J. Multivar. Anal. 98(9), 1765–1781 (2007)

    Article  MATH  Google Scholar 

  59. Horn, R.A., Johnson, C.R.: Matrix Analysis. Cambridge University Press, Cambridge (1990)

    MATH  Google Scholar 

  60. Akaike, H.: A new look at the statistical model identification. IEEE Trans. Autom. Control 19(6), 716–723 (1974)

    Article  MATH  MathSciNet  Google Scholar 

  61. Salvadori, G., De Michele, C.: Multivariate multiparameter extreme value models and return period: a copula approach. Water Resour. Res. 46, W10501 (2010). doi:10.1029/2009WR009040

    Article  Google Scholar 

  62. Dalrymple, T.: Flood frequency method. U.S. Geological Survey, Water Supply Paper, 1543A, pp. 11–51 (1960)

  63. Hannachi, A., Jolliffe, I.T., Stephenson, D.B.: Empirical orthogonal functions and related techniques in atmospheric science: a review. Int. J. Climatol. 27, 1119–1152 (2007)

    Article  Google Scholar 

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Acknowledgements

The data used in this study was supported by China Meteorological Administration. We thank the people who have given advice on our study, and also express our gratitude to those who make careful improvements to this paper.

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Authors and Affiliations

  1. Department of Water Resource and Environment, Sun Yat-sen University, Guangzhou, China

    Qiang Huang

  2. School of Construction and Environmental Engineering, Shenzhen Polytechnic, Shenzhen, China

    Qiang Huang & Jingsi Gao

  3. College of Mathematics and Statistics, Wuhan University, Wuhan, China

    Jiahan Li

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  1. Qiang Huang
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Correspondence to Qiang Huang.

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Huang, Q., Li, J. & Gao, J. The risks assessment via a regional approach using multivariate regional frequency clustering method. Cluster Comput 20, 3441–3457 (2017). https://doi.org/10.1007/s10586-017-1126-7

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