Spatio-temporal clustering of extreme floods in Great Britain

被引:0
|
作者
Formetta, Giuseppe [1 ]
Svensson, Cecilia [2 ]
Stewart, Elizabeth [2 ]
机构
[1] Univ Trento, Dept Civil Environm & Mech Engn, Via Mesiano 77, I-38123 Trento, Italy
[2] UK Ctr Ecol & Hydrol, Wallingford, England
基金
英国自然环境研究理事会;
关键词
flooding; flood spatial dependency; flood temporal clustering; SPATIAL DEPENDENCE; RIVER FLOW; RISK; STREAMFLOW; EUROPE; PRECIPITATION; ATTRIBUTION; ENGLAND; SERIES;
D O I
10.1080/02626667.2024.2367167
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
Quantifying the tendency of flood events to demonstrate clustering in time and space is crucial for flood risk assessments. We analyse the temporal (TC) and spatial (SC) coherence of floods in 554 catchments over Great Britain. TC was assessed using the dispersion-index and Conway-Maxwell-Poisson regression, with both methods applied to aggregation windows of 1-5 years. SC was investigated using the flood susceptibility index. Results show that i) most of the UK peak floods are overdispersed and ii) a positive relationship exists between winter mean North Atlantic Oscillation anomalies and the annual number of peak floods across western Britain. The susceptibility to widespread floods is higher for the southeast parts of Britain and for the Clyde-Forth valleys, and it increases with catchment permeability and with the influence of lakes/reservoirs. These findings are relevant to enhance existing flood hazard estimation methods and, in turn, will lead to more realistic flood risk quantification.
引用
收藏
页码:1288 / 1300
页数:13
相关论文
共 50 条
  • [41] Spatial clustering in the spatio-temporal dynamics of endemic cholera
    Ruiz-Moreno, Diego
    Pascual, Mercedes
    Emch, Michael
    Yunus, Mohammad
    [J]. BMC INFECTIOUS DISEASES, 2010, 10
  • [42] Parallel Clustering of Big Data of Spatio-temporal Trajectory
    Hu, Chunchun
    Kang, Xionghua
    Luo, Nianxue
    Zhao, Qiansheng
    [J]. 2015 11TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC), 2015, : 769 - 774
  • [43] Spatio-temporal modelling of extreme wave heights in the Mediterranean Sea
    Sartini, L.
    Besio, G.
    Cassola, F.
    [J]. OCEAN MODELLING, 2017, 117 : 52 - 69
  • [44] A hierarchical Bayesian spatio-temporal model for extreme precipitation events
    Ghosh, Souparno
    Mallick, Bani K.
    [J]. ENVIRONMETRICS, 2011, 22 (02) : 192 - 204
  • [45] Spatio-temporal variation of daily extreme temperatures over Turkey
    Toros, Huseyin
    [J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2012, 32 (07) : 1047 - 1055
  • [46] A spatio-temporal dynamic regression model for extreme wind speeds
    Behzad Mahmoudian
    Mohsen Mohammadzadeh
    [J]. Extremes, 2014, 17 : 221 - 245
  • [47] Spatio-temporal changes in the mean and extreme temperature indices for Serbia
    Tosic, Ivana
    Tosic, Milica
    Lazic, Irida
    Aleksandrov, Neda
    Putnikovic, Suzana
    Djurdjevic, Vladimir
    [J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2023, 43 (05) : 2391 - 2410
  • [48] Spatio-Temporal Variation of Extreme Heat Events in Southeastern Europe
    Malcheva, Krastina
    Bocheva, Lilia
    Chervenkov, Hristo
    [J]. ATMOSPHERE, 2022, 13 (08)
  • [49] A spatio-temporal dynamic regression model for extreme wind speeds
    Mahmoudian, Behzad
    Mohammadzadeh, Mohsen
    [J]. EXTREMES, 2014, 17 (02) : 221 - 245
  • [50] Controlling spatio-temporal extreme events by decreasing the localized energy
    Du, Lin
    Xu, Wei
    Li, Zhanguo
    Zhou, Bingchang
    [J]. PHYSICS LETTERS A, 2011, 375 (18) : 1870 - 1876