Large-scale stochastic flood hazard analysis applied to the Po River

被引:6
|
作者
Curran, A. [1 ,2 ]
De Bruijn, Karin [2 ]
Domeneghetti, Alessio [3 ]
Bianchi, Federica [3 ]
Kok, M. [1 ]
Vorogushyn, Sergiy [4 ]
Castellarin, Attilio [3 ]
机构
[1] Delft Univ Technol, Civil Engn Fac, Delft, Netherlands
[2] Deltares, Delft, Netherlands
[3] Univ Bologna, Bologna, Italy
[4] GFZ German Res Ctr Geosci, Hydrol Sect, Potsdam, Germany
关键词
Flood risk; Hazard analysis; Dike breaching; Copula; System behaviour; Failure probabilities; FRAGILITY CURVES; RISK;
D O I
10.1007/s11069-020-04260-w
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Reliable hazard analysis is crucial in the flood risk management of river basins. For the floodplains of large, developed rivers, flood hazard analysis often needs to account for the complex hydrology of multiple tributaries and the potential failure of dikes. Estimating this hazard using deterministic methods ignores two major aspects of large-scale risk analysis: the spatial-temporal variability of extreme events caused by tributaries, and the uncertainty of dike breach development. Innovative stochastic methods are here developed to account for these uncertainties and are applied to the Po River in Italy. The effects of using these stochastic methods are compared against deterministic equivalents, and the methods are combined to demonstrate applications for an overall stochastic hazard analysis. The results show these uncertainties can impact extreme event water levels by more than 2 m at certain channel locations, and also affect inundation and breaching patterns. The combined hazard analysis allows for probability distributions of flood hazard and dike failure to be developed, which can be used to assess future flood risk management measures.
引用
收藏
页码:2027 / 2049
页数:23
相关论文
共 50 条
  • [42] Markovian descriptors based stochastic analysis of large-scale climate indices
    Asif Iqbal
    Tanveer Ahmed Siddiqi
    Stochastic Environmental Research and Risk Assessment, 2022, 36 : 955 - 968
  • [43] Multidomain Formulation of BEM Analysis Applied to Large-Scale Polycrystalline Materials
    Galvis, A. F.
    Rodriguez, R. Q.
    Sollero, P.
    Alburquerque, E. L.
    CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES, 2013, 96 (02): : 103 - 115
  • [44] Stochastic approximation EM for large-scale exploratory IRT factor analysis
    Camilli, Gregory
    Geis, Eugene
    STATISTICS IN MEDICINE, 2019, 38 (21) : 3997 - 4012
  • [45] Stochastic model and synchronization analysis for large-scale oscillator networks and their applications
    Chen, X.
    Zhai, G.
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING, 2008, 222 (I7) : 711 - 720
  • [46] Markovian descriptors based stochastic analysis of large-scale climate indices
    Iqbal, Asif
    Siddiqi, Tanveer Ahmed
    STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2022, 36 (04) : 955 - 968
  • [47] ACCIDENT ANALYSIS OF LARGE-SCALE TECHNOLOGICAL DISASTERS APPLIED TO AN ANESTHETIC COMPLICATION
    EAGLE, CJ
    DAVIES, JM
    REASON, J
    CANADIAN JOURNAL OF ANAESTHESIA-JOURNAL CANADIEN D ANESTHESIE, 1992, 39 (02): : 118 - 122
  • [48] Effectively manage large-scale process hazard assessments
    Shah, G.C.
    Chemical Processing, 2019, 81 (08):
  • [49] An urban drainage scheme for large-scale flood models
    Getirana, Augusto
    Mandarino, Felipe
    Montezuma, Patricia Ney de
    Kirschbaum, Dalia
    JOURNAL OF HYDROLOGY, 2023, 627
  • [50] Flood Risk Assessment for Large-scale Dike Systems
    Cheng Wei-shuai
    Ji Chang-ming
    Liu Dan
    NEW PERSPECTIVES ON RISK ANALYSIS AND CRISIS RESPONSE, 2009, : 413 - +