دانلود رایگان مقاله انگلیسی ارزیابی روش های موجود برای برآورد پارامترهای شکست سد خاکی - اشپرینگر 2017

Abstract

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.

7 Conclusion

This study presents a review of the previous studies that covered dam breach parameters estimation and discussed their accuracy. There are many existing approaches to estimate the dam breach parameters. It found that these approaches were based on regression analysis. These approaches were derived using limited data, and this affects the accuracy of the prediction obtained from these approaches. Moreover, the relationships used for determining the dam breach parameters are complex, and any simplification of these relationships will also affect their accuracy.

The prediction from the existing approaches (regression analysis) was validated using data of more than 140 failed dams around the world. The values of the computed MARE for the existing approaches confirm that linear approaches are less accurate than the nonlinear ones. Also, the results confirm the need for a more accurate approach.

The artificial neural network approach is widely applied for solving various types of problems of water resources. Although it is not specifically applied for dam-break analysis, it is possible to use it for such problems. ANN technique can be used instead of regression analysis to estimate the dam breach parameters due to the fact that this technique has ability to simulate the nonlinearity of variables and give accurate results.