Classification of precipitation series using fuzzy cluster method

被引:47
作者
Dikbas, Fatih [2 ]
Firat, Mahmut [1 ]
Koc, A. Cem [2 ]
Gungor, Mahmud [2 ]
机构
[1] Inonu Univ, Dept Civil Engn, Fac Engn, Malatya, Turkey
[2] Pamukkale Univ, Fac Engn, Dept Civil Engn, Denizli, Turkey
基金
美国国家科学基金会;
关键词
cluster analysis; classification; fuzzy cluster; annual total precipitation; hydrologically homogeneous region; REGIONAL FLOOD FREQUENCY; L-MOMENTS; BASINS; SYSTEM;
D O I
10.1002/joc.2350
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The identification of hydrologically homogeneous regions is one of the most important steps of regional frequency analysis. The hydrologically homogeneous regions should be determined using cluster analysis instead of the geographically close regions or stations. In this study, fuzzy cluster method (Fuzzy C-Means: FCM) is applied to classify the precipitation series and identify the hydrologically homogeneous groups. The choice of appropriate cluster method and the variables that will be used according to the data of the basin is also very important. In the context of this study, total precipitation data of stations operated by National Meteorology Works (DMI) in Turkish basins for cluster analysis are used. The optimal number of groups is determined as six, based on different performance evaluation indexes. Regional homogeneity tests based on L-moments method are applied to check homogeneity of these six regions identified by cluster analysis. Regional homogeneity test results show that regions defined by FCM method are sufficiently homogeneous for regional frequency analysis. According to the results, FCM method is recommended for classifying the precipitation series and for identifying the hydrologically homogenous regions. Copyright (c) 2011 Royal Meteorological Society
引用
收藏
页码:1596 / 1603
页数:8
相关论文
共 32 条
  • [1] A predictive model for well loss using fuzzy logic approach
    Altunkaynak, Abduesselam
    [J]. HYDROLOGICAL PROCESSES, 2010, 24 (17) : 2400 - 2404
  • [2] Andrade E. M., 1999, Engenharia Agricola, V18, P39
  • [3] [Anonymous], Pattern Recognition with Fuzzy Objective Function Algorithms
  • [4] The formation of groups for regional flood frequency analysis
    Burn, DH
    Goel, NK
    [J]. HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES, 2000, 45 (01): : 97 - 112
  • [5] CLUSTER-ANALYSIS AS APPLIED TO REGIONAL FLOOD FREQUENCY
    BURN, DH
    [J]. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT-ASCE, 1989, 115 (05): : 567 - 582
  • [6] Catchment similarity for regional flood frequency analysis using seasonality measures
    Burn, DH
    [J]. JOURNAL OF HYDROLOGY, 1997, 202 (1-4) : 212 - 230
  • [7] REGIONALIZATION OF CATCHMENTS FOR REGIONAL FLOOD FREQUENCY ANALYSIS
    Burn, Donald H.
    Zrinji, Zolt
    Kowalchuk, Michael
    [J]. JOURNAL OF HYDROLOGIC ENGINEERING, 1997, 2 (02) : 76 - 82
  • [8] Annual runoff regional frequency analysis in Sicily
    Cannarozzo, M.
    Noto, L. V.
    Viola, F.
    La Loggia, G.
    [J]. PHYSICS AND CHEMISTRY OF THE EARTH, 2009, 34 (10-12) : 679 - 687
  • [9] Demirel MC, 2007, HYDROLOGY DAYS, V1, P145
  • [10] Dunn J. C., 1973, Journal of Cybernetics, V3, P32, DOI 10.1080/01969727308546046