An evaluation of existent methods for estimation of embankment dam breach parameters

被引:0
|
作者
Saad Sh. Sammen
T. A. Mohamed
A. H. Ghazali
L. M. Sidek
A. El-Shafie
机构
[1] University Putra Malaysia,Department of Civil Engineering, Faculty of Engineering
[2] Diyala University,Department of Civil Engineering, College of Engineering
[3] University Tenaga Nasional,Department of Civil Engineering, College of Engineering
[4] University Malaya,Department of Civil Engineering, Faculty of Engineering
来源
Natural Hazards | 2017年 / 87卷
关键词
Embankment dam; Dam breach; Breach parameters; Uncertainty analysis;
D O I
暂无
中图分类号
学科分类号
摘要
The study of dam-break analysis is considered important to predict the peak discharge during dam failure. This is essential to assess economic, social and environmental impacts downstream and to prepare the emergency response plan. Dam breach parameters such as breach width, breach height and breach formation time are the key variables to estimate the peak discharge during dam break. This study presents the evaluation of existing methods for estimation of dam breach parameters. Since all of these methods adopt regression analysis, uncertainty analysis of these methods becomes necessary to assess their performance. Uncertainty was performed using the data of more than 140 case studies of past recorded failures of dams, collected from different sources in the literature. The accuracy of the existing methods was tested, and the values of mean absolute relative error were found to be ranging from 0.39 to 1.05 for dam breach width estimation and from 0.6 to 0.8 for dam failure time estimation. In this study, artificial neural network (ANN) was recommended as an alternate method for estimation of dam breach parameters. The ANN method is proposed due to its accurate prediction when it was applied to similar other cases in water resources.
引用
收藏
页码:545 / 566
页数:21
相关论文
共 50 条
  • [21] Software tool for progressive dam breach outflow estimation
    Vetsch, D. F.
    Halso, M. C.
    Seidelmann, L.
    Boes, R. M.
    ROLE OF DAMS AND RESERVOIRS IN A SUCCESSFUL ENERGY TRANSITION, ECS 2023, 2023, : 981 - 988
  • [22] Gene expression models for prediction of dam breach parameters
    Sattar, Ahmed M. A.
    JOURNAL OF HYDROINFORMATICS, 2014, 16 (03) : 550 - 571
  • [23] A study of the overtopping breach of a sand-gravel embankment dam using experimental models
    Li, Yanlong
    Tian, Chao
    Wen, Lifeng
    Chen, Anke
    Wang, Lin
    Qiu, Wen
    Zhou, Heng
    ENGINEERING FAILURE ANALYSIS, 2021, 124
  • [24] SSHAC Evaluation of the Seismic Fragility for an Embankment Dam
    McCann, Martin W., Jr.
    Ruby, Zach
    Beaty, Michael
    Westover, Thomas
    Castro, Gonzalo
    Harder, Leslie
    GEO-RISK 2023: HAZARDS AND CLIMATE CHANGE, 2023, 344 : 318 - 327
  • [25] A probabilistic framework for comparison of dam breach parameters and outflow hydrograph generated by different empirical prediction methods
    Ahmadisharaf, Ebrahim
    Kalyanapu, Alfred J.
    Thames, Brantley A.
    Lillywhite, Jason
    ENVIRONMENTAL MODELLING & SOFTWARE, 2016, 86 : 248 - 263
  • [26] Effect of Breach Parameters and Progression Curves on Dam Failure Hydrograph
    Prastalo, Petar
    Uljarevic, Mato
    Vukomanovic, Radovan
    CIVIL ENGINEERING JOURNAL-TEHRAN, 2024, 10 (02): : 456 - 467
  • [27] An approach to quick and easy evaluation of the dam breach flood
    ZuYu Chen
    ZiYi Ping
    NaiXin Wang
    Shu Yu
    ShuJing Chen
    Science China Technological Sciences, 2019, 62 : 1773 - 1782
  • [28] An approach to quick and easy evaluation of the dam breach flood
    CHEN ZuYu
    PING ZiYi
    WANG NaiXin
    YU Shu
    CHEN ShuJing
    Science China(Technological Sciences), 2019, 62 (10) : 1773 - 1782
  • [29] An approach to quick and easy evaluation of the dam breach flood
    CHEN ZuYu
    PING ZiYi
    WANG NaiXin
    YU Shu
    CHEN ShuJing
    Science China(Technological Sciences) , 2019, (10) : 1773 - 1782
  • [30] An approach to quick and easy evaluation of the dam breach flood
    Chen ZuYu
    Ping ZiYi
    Wang NaiXin
    Yu Shu
    Chen ShuJing
    SCIENCE CHINA-TECHNOLOGICAL SCIENCES, 2019, 62 (10) : 1773 - 1782