变化环境下非一致性水文频率分析研究综述
Review on Nonstationary Hydrological Frequency Analysis under Changing Environments

作者: 熊立华 , 江 聪 , 杜 涛 , 郭生练 :武汉大学水资源与水电工程科学国家重点实验室,湖北 武汉; 许崇育 :武汉大学水资源与水电工程科学国家重点实验室,湖北 武汉;挪威奥斯陆大学地学系,挪威 奥斯陆 ;

关键词: 水文频率分析单变量非一致性时变矩法重现期多变量Copula函数Hydrological Frequency Analysis Univariate Nonstationarity Time-Varying Moments Return Period Multivariate Copula

摘要: 水文频率分析计算是水利工程规划设计、施工以及运行管理的基础工作,传统的水文频率分析计算的一个基本前提是水文序列满足一致性假设。近几十年来,受气候变化和人类活动影响,许多河流的径流序列存在非一致性,导致传统基于一致性假设的水文频率计算方法的适用性受到严峻挑战,因此研究非一致性条件下水文频率分析方法具有重要的意义。本文在总结了国内外最新的非一致水文序列频率分析研究成果的基础上,将该研究方向的研究重点、难点和热点归纳为如下四方面:1) 单变量水文序列的非一致性诊断;2) 单变量水文序列非一致性的数学描述与归因分析;3) 非一致性条件下的单变量随机事件重现期定义和估计;4) 多变量非一致水文序列的频率分析。最后,针对这些问题,对今后的研究进行了展望。

Abstract: The assumption of stationarity is a basic premise behind conventional hydrological frequency analysis for hydrological design of water resources projects. Under changing environments, hydrological series in many rivers have been found to exhibit nonstationarity. As a result, the methods for conventional hy-drological frequency analysis based on stationarity assumption may be invalid. In recent years, the fre-quency analysis for nonstationary hydrological series has attracted much attention. In this paper, re-searches on nonstationary hydrological frequency analysis are briefly reviewed in terms of four aspects: 1) detection of the nonstationarity in univariate hydrological series; 2) mathematical description and physical attribution of the nonstationarity in univariate hydrological series; 3) definition and calculation of return period of univariate events under nonstationary conditions; and 4) nonstationary frequency analysis for multivariate hydrological series. Finally, some perspectives are presented for further de-velopment and improvement of the nonstationary hydrological frequency analysis.

文章引用: 熊立华 , 江 聪 , 杜 涛 , 郭生练 , 许崇育 (2015) 变化环境下非一致性水文频率分析研究综述。 水资源研究, 4, 310-319. doi: 10.12677/JWRR.2015.44038

参考文献

[1] MONTANARI, A., YOUNG, G., SAVENIJE, H. H. G., et al. “Panta Rhei—Everything Flows”: Change in hydrology and society—The IAHS Scientific Decade 2013-2022. Hydrological Sciences Journal, 2013, 58(6): 1256-1275.
http://dx.doi.org/10.1080/02626667.2013.809088

[2] 梁忠民, 胡义明, 王军. 非一致性水文频率分析的研究进展[J]. 水科学进展, 2011, 22(6): 864-871. LIANG Zhongmin, HU Yiming and WANG Jun. Advances in hydrological frequency analysis of non-stationary time series. Advances in Water Science, 2011, 22(6): 864-871. (in Chinese)

[3] MILLY, P. C. D., BETANCOURT, J., FALKENMARK, M., et al. Stationarity is dead: Whither water management? Science, 2008, 319(5863): 573-574.
http://dx.doi.org/10.1126/science.1151915

[4] CHOW, V. T., MAIDMENT, D. R. and MAYS, L. W. Applied hydrology. New York: McGrawHill, 1988.

[5] SALAS, J. D. Analysis and modeling of hydrologic time series. In: MAIDMENT. D., Ed., Handbook of Hydrology, New York: McGraw-Hill, 1993: 19.1-19.72.

[6] KHALIQ, M. N., OUARDA, T. B. M. J., ONDO, J. C., et al. Frequency analysis of a sequence of dependent and/or non-sta- tionary hydro-meteorological observations: A review. Journal of Hydrology, 2006, 329(3): 534-552.
http://dx.doi.org/10.1016/j.jhydrol.2006.03.004

[7] 谢平, 陈广才, 雷红富, 等. 变化环境下地表水资源评价方法[M]. 北京: 科学出版社, 2009. XIE Ping, CHEN Guangcai, LEI Hongfu, et al. Surface water resources evaluation methods on changing environment. Beijing: Science Press, 2009. (in Chinese)

[8] THERESIA, P., BRUNO, M. Trends in flood magnitude, frequency and seasonality in Germany in the period 1951-2002. Journal of Hydrology, 2009, 371(1-4): 129-141.
http://dx.doi.org/10.1016/j.jhydrol.2009.03.024

[9] XIONG, L., GUO, S. Trend test and change-point detection for the annual discharge series of the Yangtze River at the Yichang hydrological station. Hydrological Sciences Journal, 2004, 49(1): 99-112.
http://dx.doi.org/10.1623/hysj.49.1.99.53998

[10] LI, D., XIE, H. and XIONG, L. Temporal change analysis based on data characteristics and nonparametric test. Water Resources Management, 2014, 28(1): 227-240.
http://dx.doi.org/10.1007/s11269-013-0481-2

[11] XIONG, L., DU, T., XU, C. Y., GUO, S. L., JIANG, C. and GIPPEL, C. J. Non-stationary annual maximum flood frequency analysis using the norming constants method to consider non-stationarity in the annual daily flow series. Water Resources Management, 2015, 29(10): 3615-3633.
http://dx.doi.org/10.1007/s11269-015-1019-6

[12] 谢平, 陈广才, 雷红富, 武方圆. 水文变异诊断系统[J]. 水力发电学报, 2010, 29(1): 85-91. XIE Ping, CHEN Guangcai, LEI Hongfu and WU Fangyuan. Hydrological alteration diagnosis system. Journal of Hydroelectric Engineering, 2010, 29(1): 85-91. (in Chinese)

[13] KOUTSOYIANNIS, D. Nonstationarity versus scaling in hydrology. Journal of Hydrology, 2006, 324(1-4): 239-254.
http://dx.doi.org/10.1016/j.jhydrol.2005.09.022

[14] MONTANARI, A., KOUTSOYIANNIS, D. Modeling and mitigating natural hazards: Stationarity is immortal! Water Resources Research, 2014, 50(12): 9748-9756.
http://dx.doi.org/10.1002/2014WR016092

[15] STRUPCZEWSKI, W. G., SINGH, V. P. and FELUCH, W. Non-stationary approach to at-site flood frequency modeling I. Maximum likelihood estimation. Journal of Hydrology, 2001, 248(1): 123-142.
http://dx.doi.org/10.1016/S0022-1694(01)00397-3

[16] STRUPCZEWSKI, W. G., KACZMAREK, Z. Non-stationary approach to at-site flood frequency modeling II. Weighted least squares estimation. Journal of Hydrology, 2001, 248(1): 143-151.
http://dx.doi.org/10.1016/S0022-1694(01)00398-5

[17] STRUPCZEWSKI, W. G., SINGH, V. P. and MITOSEK, H. T. Nonstationary approach to at-site flood frequency modeling III. Flood analysis of Polish rivers. Journal of Hydrology, 2001, 248(1-4): 152-167.
http://dx.doi.org/10.1016/S0022-1694(01)00399-7

[18] KATZ, R. W., PARLANG, M. B. and NAVEAU, P. Statistics of extremes in hydrology. Advances in Water Resources, 2002, 25(8): 1287-1304.
http://dx.doi.org/10.1016/S0309-1708(02)00056-8

[19] KHARIN, V. V., ZWIERS, F. W. Estimating extremes in transient climate change simulations. Journal of Climate, 2005, 18(8): 1156-1173.
http://dx.doi.org/10.1175/JCLI3320.1

[20] CUNDERLIK, J. M., OUARDA, T. B. M. J. Regional flood-duration-frequency modeling in a changing environment. Journal of Hydrology, 2006, 318(1-4): 276-291.
http://dx.doi.org/10.1016/j.jhydrol.2005.06.020

[21] 杜涛, 熊立华, 江聪. 渭河流域降雨时间序列非一致性频率分析[J]. 干旱区地理, 2014, 37(3): 468-479. DU Tao, XIONG Lihua and JIANG Cong. Nonstationary frequency analysis of rainfall time series in Weihe River basin. Arid Land Geography, 2014, 37(3): 468-479. (in Chinese)

[22] RIGBY, R. A., STASINOPOULOS, D. M. Generalized additive models for location, scale and shape. Journal of the Royal Statistical Society: Series C (Applied Statistics), 2005, 54(3): 507-554.
http://dx.doi.org/10.1111/j.1467-9876.2005.00510.x

[23] VILLARINI, G., SMITH, J. A., SERINALDI, F., BALES, J., BATES, P. D. and KRAJEWSKI, W. F. Flood frequency analysis for nonstationary annual peak records in an urban drainage basin. Advance in Water Resource, 2009, 32(8): 1255-1266.
http://dx.doi.org/10.1016/j.advwatres.2009.05.003

[24] VILLARINI, G., SERINALDI, F., SMITH, J. A. and KRAJEWSKI, W. F. On the stationarity of annual flood peaks in the continental United States during the 20th century. Water Resources Research, 2009, 45(8): W08417.
http://dx.doi.org/10.1029/2008WR007645

[25] 江聪, 熊立华. 基于GAMLSS模型的宜昌站年径流序列趋势分析[J]. 地理学报, 2012, 67(11): 1505-1514. JIANG Cong, XIONG Lihua. Trend analysis for the annual discharge series of the Yangtze River at the Yichang hydrological station based on GAMLSS. Acta Geographica Sinica, 2012, 67(11): 1505-1514. (in Chinese)

[26] SERINALDI, F., KILSBY, C. G. Stationarity is undead: Uncertainty dominates the distribution of extremes. Advances in Water Resources, 2015, 77: 17-36.

[27] VILLARINI, G., SERINALDI, F. Development of statistical models for at-site probabilistic seasonal rainfall forecast. International Journal of Climatology, 2012, 32(14): 2197-2212.

[28] LÓPEZ, J., FRANCÉS, F. Non-stationary flood frequency analysis in continental Spanish rivers, using climate and reservoir indices as external covariates. Hydrology and Earth System Sciences, 2013, 17(8): 3189-3203.
http://dx.doi.org/10.5194/hess-17-3189-2013

[29] XIONG, L., JIANG, C. and DU, T. Statistical attribution analysis of the nonstationarity of the annual runoff series of the Weihe River. Water Science & Technology, 2014, 70(5): 939-946.
http://dx.doi.org/10.5194/hess-17-3189-2013

[30] LIU, D. D., GUO, S. L., LIAN, Y. Q., XIONG, L. H. and CHEN, X. H. Climate-informed low-flow frequency analysis using nonstationary modeling. Hydrological Processes, 2014, 29(9): 2112-2124.
http://dx.doi.org/10.1002/hyp.10360

[31] 熊立华, 江聪. 考虑非一致性的渭河流域设计洪水过程线研究[J]. 水资源研究, 2015, 4(2): 109-119. XIONG Lihua, JIANG Cong. Designing flood hydrograph of the Weihe River considering nonstationarity. Journal of Water Resources Research, 2015, 4(2): 109-119. (in Chinese)

[32] GOTTSCHALK, L., YU, K. X., LEBLOIS, E. and XIONG, L. H. Statistics of low flow: Theoretical derivation of the distribution of minimum streamflow series. Journal of Hydrology, 2013, 481: 204-219.

[33] YU, K. X., XIONG, L. and GOTTSCHALK, L. Derivation of low flow distribution functions using copulas. Journal of Hydrology, 2014, 508: 273-288.

[34] XIONG, L., YU, K. and GOTTSCHALK, L. Estimation of the distribution of annual runoff from climatic variables using copulas. Water Resources Research, 2014, 50(9): 7134-7152.
http://dx.doi.org/10.1002/2013WR015159

[35] WIGLEY, T. M. L. The effect of climate change on the frequency of ab-solute extreme events. Climate Monitor, 1988, 17(1-2): 44-55.

[36] WIGLEY, T. M. L. The effect of changing climate on the frequency of absolute extreme events. Climatic Change, 2009, 97(1-2): 67-76.
http://dx.doi.org/10.1007/s10584-009-9654-7

[37] PAREY, S., MALEK, F., LAURENT, C. and DACUNHA-CASTELLE, D. Trends and climate evolution: Statistical approach for very high temperatures in France. Climatic Change, 2007, 81(3-4): 331-352.
http://dx.doi.org/10.1007/s10584-006-9116-4

[38] PAREY, S., HOANG, T. T. H. and DACUNHA-CASTELLE, D. Dif-ferent ways to compute temperature return levels in the climate change context. Environmetrics, 2010, 21(7-8): 698-718.
http://dx.doi.org/10.1002/env.1060

[39] SALAS, J. D., OBEYSEKERA, J. Revisiting the concepts of return period and risk for nonstationary hydrologic extreme events. Journal of Hydrologic Engineering, 2014, 19(3): 554-568.
http://dx.doi.org/10.1061/(ASCE)HE.1943-5584.0000820

[40] HAAN, C. T. Statistical methods in hydrology. 2nd Edition, Ames: Iowa State University Press, 2002.

[41] MOOD, A., GRAYBILL, F. and BOES, D. C. Introduction to the theory of statistics. 3rd Edition, New York: McGraw-Hill, 1974.

[42] COOLEY, D. Return periods and return levels under climate change. In: AGHAKOUCHAK, A., EASTERLING, D., HSU, K., SCHUBERT, S. and SOROOSHIAN, S., Eds., Extremes in a chang-ing climate, Dordrecht: Springer, 2013: 97-114.
http://dx.doi.org/10.1007/978-94-007-4479-0_4

[43] OLSEN, J. R., LAMBERT, J. H. and HAIMES, Y. Y. Risk of ex-treme events under nonstationary conditions. Risk Analysis, 1998, 18(4): 497-510.
http://dx.doi.org/10.1111/j.1539-6924.1998.tb00364.x

[44] DU, T., XIONG, L., XU, C. Y., GIPPEL, C. J., GUO, S. L. and LIU, P. Return period and risk analysis of nonstationary low- flow series under climate change. Journal of Hydrology, 2015, 527: 234-250.

[45] CHEBANA, F., OUARDA, T. B. M. J. and DUONG, T. C. Testing for multivariate trends in hydrologic frequency analysis. Journal of Hydrology, 2013, 486: 519-530.

[46] BEN AISSIA, M. A., CHEBANA, F., OUARDA, T. B. M. J., ROY, L., BRUNEAU, P. and BARBET, M. Dependence evolution of hydrological characteristics, applied to floods in a climate change context in Québec. Journal of Hydrology, 2014, 519(Part A): 148-163.

[47] SALVADORI, G., DE MICHELE, C. Analytical calculation of storm volume statistics involving Pareto-like intensity-duration marginals. Geophysical Research Letters, 2004, 31(4): L045024.
http://dx.doi.org/10.1029/2003GL018767

[48] FAVRE, A. C., EL ADLOUNI, S. and PERREAULT, L. Multivariate hydrological frequency analysis using copulas. Water Resources Research, 2004, 40(1): W011011.
http://dx.doi.org/10.1029/2003WR002456

[49] 熊立华, 郭生练, 肖义, 袁汉芳. Copula 联结函数在多变量水文频率分析中的应用[J]. 武汉大学学报(工学版), 2005, 38(6): 16-19. XIONG Lihua, GUO Shenglian, XIAO Yi and YUAN Hanfang. Application of copulas to multivariate hydrological frequency analysis. Engineering Journal of Wuhan University, 2005, 38(6): 16-19. (in Chinese)

[50] SALVADORI, G., DE MICHELE, C., KOTTEGODA, N. T. and ROSSO, R. Extremes in nature: An approach using Copulas. Dordrecht: Springer, 2007.

[51] SERINALDI, F., GRIMALDI, S. Fully nested 3-Copula: Procedure and application on hydrological data. Journal of Hydrologic Engineering, 2007, 12(4): 420-430.
http://dx.doi.org/10.1061/(ASCE)1084-0699(2007)12:4(420)

[52] GRIMALDI, S., SERINALDI, F. Asymmetric copula in multivariate flood frequency analysis. Advances in Water Resources, 2006, 29(8): 1115-1167.
http://dx.doi.org/10.1016/j.advwatres.2005.09.005

[53] GRÄLER, B., VAN DEN BERG, M., VANDENBERGHE, S., PETROSELLI, A., GRIMALDI, S., DE BAETS, B. and Verhoest, N. E. C. Multivariate return periods in hydrology: A critical and practical review focusing on synthetic design hydrograph estimation. Hydrology and Earth System Sciences, 2013, 17(4): 1281-1296.
http://dx.doi.org/10.5194/hess-17-1281-2013

[54] SALVADORI, G., DE MICHELE C. Multivariate multi-parameter extreme value models and return periods: A copula approach. Water Resources Research, 2010, 46(10): W10501.
http://dx.doi.org/10.1029/2009WR009040

[55] ZHANG, L., SINGH, V. P. Bivariate rainfall frequency distributions using Archimedean copulas. Journal of Hydrology, 2007, 332(1-2): 93-109.
http://dx.doi.org/10.1016/j.jhydrol.2006.06.033

[56] 刘章君, 郭生练, 李天元, 等. 基于Copula函数的梯级水库设计洪水地区组成研究[J]. 水资源研究, 2014, 3(2): 124-135. LIU Zhangjun, GUO Shenglian, LI Tianyuan, et al. Regional flood composition of cascade reservoirs based on copula function. Journal of Water Resources Research, 2014, 3(2): 124-135. (in Chinese)
http://dx.doi.org/10.12677/JWRR.2014.32018

[57] 刘章君, 郭生练, 李天元, 胡瑶, 李立平. 设计洪水地区组成的区间估计方法研究[J]. 水利学报, 2015, 46(5): 543-550. LIU Zhangjun, GUO Shenglian, LI Tianyuan, HU Yao and LI Liping. Interval estimation method for design flood region composition. Journal of Hydraulic Engineering, 2015, 46(5): 543-550. (in Chinese)

[58] 刘章君, 郭生练, 李天元, 徐长江. 梯级水库设计洪水最可能地区组成法计算通式[J]. 水科学进展, 2014, 25(4): 549-558. LIU Zhangjun, GUO Shenglian, LI Tianyuan and XU Changjiang. General formula derivation of most likely regional composi-tion method for design flood estimation of cascade reservoirs system. Advances in Water Science, 2014, 25(4): 549-558. (in Chinese)

[59] 冯平, 李新. 基于Copula函数的非一致性洪水峰量联合分析[J]. 水利学报, 2013, 44(10): 1137-1147. FENG Ping, LI Xin. Bivariate frequency analysis of non-stationary flood time series based on Copula methods. Journal of Hy-draulic Engineering, 2013, 44(10): 1137-1147. (in Chinese)

[60] BENDER, J., WAHL, T. and JENSEN, J. Multivariate design in the presence of non-stationarity. Journal of Hydrology, 2014, 514: 123-130.

[61] JIANG, C., XIONG, L., XU, C. Y. and GUO, S. L. Bivariate frequency analysis of nonstationary low-flow series based on the time-varying copula. Hydrological Processes, 2015, 29(6): 1521-1534.
http://dx.doi.org/10.1002/hyp.10288

[62] STASINOPOULOS, D. M., RIGBY, R. A. and AKANTZILIOTOU, C. Instructions on how to use the GAMLSS package in R. Accompanying documentation in the current GAMLSS help files, 2008.

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