Predicting peak breach discharge due to embankment dam failure

Predicting peak breach discharge due to embankment dam failure is of vital importance for dam failure prevention and mitigation. Because, when dams fail, property damage is certain, but loss of life can vary depending on flood area and population. Many parametric breach models based on regression techniques have been developed so far. In this study, an efficient model is proposed to forecast peak discharge from the height of the water and volume of water behind the dam at failure, respectively, by using the Kriging approach. The previous studies, which consist of 13 numerical models, are used as a benchmark for testing the proposed new model, by employing five different error criteria. Moreover, a new database is compiled by extending the previous one. In addition, it is demonstrated that R 2 , which only quantifies the dispersion between measurements and predictions, should not be considered alone for checking the model capabilities. At least, the other criteria should be employed together with R 2 . As a result, it is shown that one can forecast the peak flow discharge with more significant accuracy by the proposed model than other previous models developed so far.

[1]  Tarkan Erdik,et al.  Fuzzy logic approach to conventional rubble mound structures design , 2009, Expert Syst. Appl..

[2]  Li Min Zhang,et al.  Breaching Parameters for Earth and Rockfill Dams , 2009 .

[3]  Mehmet Özger,et al.  Triple diagram method for the prediction of wave height and period , 2007 .

[4]  Abdüsselam Altunkaynak,et al.  Significant wave height prediction by using a spatial model , 2005 .

[5]  Zekâi Şen,et al.  Autorun analysis of hydrologic time series , 1978 .

[6]  Abdüsselam Altunkaynak Streamflow estimation using optimal regional dependency function , 2009 .

[7]  Thomas C. MacDonald,et al.  Breaching Charateristics of Dam Failures , 1984 .

[8]  Z. Şen,et al.  Spatio-temporal drought analysis in the Trakya region, Turkey , 2003 .

[9]  David C. Froehlich,et al.  Peak Outflow from Breached Embankment Dam , 1989 .

[10]  Árni Snorrason,et al.  Sensitivity of outflow peaks and flood stages to the selection of dam breach parameters and simulation models , 1984 .

[11]  P. Krause,et al.  COMPARISON OF DIFFERENT EFFICIENCY CRITERIA FOR HYDROLOGICAL MODEL ASSESSMENT , 2005 .

[12]  T. Erdik,et al.  Artificial neural networks for predicting maximum wave runup on rubble mound structures , 2009, Expert Syst. Appl..

[13]  Stephen G. Evans,et al.  The maximum discharge of outburst floods caused by the breaching of man-made and natural dams , 1986 .

[14]  Triple diagram models for prediction of suspended solid concentration in Lake Okeechobee, Florida , 2010 .

[15]  Ramesh S. V. Teegavarapu,et al.  Estimation of missing precipitation records integrating surface interpolation techniques and spatio-temporal association rules , 2009 .

[16]  Tony L. Wahl,et al.  Uncertainty of predictions of embankment dam breach parameters , 2004 .

[17]  Zekai Sen,et al.  Triple diagram model of level fluctuations in Lake Van, Turkey , 2003 .

[18]  Mehmet Özger,et al.  Fuzzy Logic Model for Equilibrium Scour Downstream of a Dam's Vertical Gate , 2006 .

[19]  V. Singh,et al.  Analysis of Gradual Earth‐Dam Failure , 1988 .

[20]  Steven R. Abt,et al.  Predicting Peak Outflow from Breached Embankment Dams , 2010 .

[21]  G. Matheron Principles of geostatistics , 1963 .