Fast and direct nonparametric procedures in the L-moment homogeneity test

被引:16
作者
Masselot, Pierre [1 ]
Chebana, Fateh [1 ]
Ouarda, Taha B. M. J. [1 ,2 ]
机构
[1] INRS, Ctr Eau Terre Environm ETE, 490 Couronne, Quebec City, PQ G1K 9A9, Canada
[2] Masdar Inst Sci & Technol, Inst Ctr Water & Environm IWATER, POB 54224, Abu Dhabi, U Arab Emirates
关键词
Regional frequency analysis; Bootstrap; Hypothesis testing; Permutation methods; Polya resampling; Homogeneity; REGIONAL FREQUENCY-ANALYSIS; BAYESIAN BOOTSTRAP; FLOOD; STATISTICS; DISTRIBUTIONS; AUSTRALIA; SELECTION; RAINFALL; EVENTS; COPULA;
D O I
10.1007/s00477-016-1248-0
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Regional frequency analysis is an important tool to properly estimate hydrological characteristics at ungauged or partially gauged sites in order to prevent hydrological disasters. The delineation of homogeneous groups of sites is an important first step in order to transfer information and obtain accurate quantile estimates at the target site. The Hosking-Wallis homogeneity test is usually used to test the homogeneity of the selected sites. Despite its usefulness and good power, it presents some drawbacks including the subjective choice of a parametric distribution for the data and a poorly justified rejection threshold. The present paper addresses these drawbacks by integrating nonparametric procedures in the L-moment homogeneity test. To assess the rejection threshold, three resampling methods (permutation, bootstrap and Plya resampling) are considered. Results indicate that permutation and bootstrap methods perform better than the parametric Hosking-Wallis test in terms of power as well as in time and procedure simplicity. A real-world case study shows that the nonparametric tests agree with the HW test concerning the homogeneity of the volume and the bivariate case while they disagree for the peak case, but that the assumptions of the HW test are not well respected.
引用
收藏
页码:509 / 522
页数:14
相关论文
共 62 条
[1]  
[Anonymous], 2005, Permutation, Parametric and Bootstrap Tests of Hypotheses
[2]  
[Anonymous], 1993, An introduction to the bootstrap
[3]   Climatic and physical factors that influence the homogeneity of regional floods in southeastern Australia [J].
Bates, BC ;
Rahman, A ;
Mein, RG ;
Weinmann, PW .
WATER RESOURCES RESEARCH, 1998, 34 (12) :3369-3381
[4]   BOOTSTRAP METHODS FOR TESTING HOMOGENEITY OF VARIANCES [J].
BOOS, DD ;
BROWNIE, C .
TECHNOMETRICS, 1989, 31 (01) :69-82
[5]   The formation of groups for regional flood frequency analysis [J].
Burn, DH ;
Goel, NK .
HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES, 2000, 45 (01) :97-112
[6]   Annual runoff regional frequency analysis in Sicily [J].
Cannarozzo, M. ;
Noto, L. V. ;
Viola, F. ;
La Loggia, G. .
PHYSICS AND CHEMISTRY OF THE EARTH, 2009, 34 (10-12) :679-687
[7]   Homogeneity testing: How homogeneous do heterogeneous cross-correlated regions seem? [J].
Castellarin, A. ;
Burn, D. H. ;
Brath, A. .
JOURNAL OF HYDROLOGY, 2008, 360 (1-4) :67-76
[8]   SHIFTED LEGENDRE DIRECT METHOD FOR VARIATIONAL-PROBLEMS [J].
CHANG, RY ;
WANG, ML .
JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, 1983, 39 (02) :299-307
[9]   Depth and homogeneity in regional flood frequency analysis [J].
Chebana, F. ;
Ouarda, T. B. M. J. .
WATER RESOURCES RESEARCH, 2008, 44 (11)
[10]   Multivariate L-moment homogeneity test [J].
Chebana, F. ;
Ouarda, T. B. M. J. .
WATER RESOURCES RESEARCH, 2007, 43 (08)