Abstract

The study of embankment breaching is not an easy practice, as it includes various parameters to meet the suitability of the design approach, especially when we consider it for the long term. Embankment breach studies generally include the prediction of different breach parameters. The important physical and hydrodynamic parameters of the flood wave generated from the embankment failure are breach width, breach slope, formation time, peak outflow, and time to failure. Out of these parameters, peak outflow is a very important breach parameter, as it deflects the magnitude of destruction on the downstream side of the embankment and affects the evacuation plans for the downstream population. The prediction of breach peak outflow due to overtopping of the embankment is very essential for dam failure prevention and mitigation, as well as for the design of an early warning system. Many researchers have used dam failure data, comparative studies, experimental studies, or regression techniques to develop various models for predicting peak outflow. The present paper analyzes the results of the design for forty experiments carried out in two different laboratory water channels (flumes). Different embankment models are overtopped with the objective of studying the breach behavior during overtopping. The study was inspired by reports in the open literature of embankment failures that resulted in catastrophic conditions. With experimental data, an efficient model is developed for predicting breach peak outflow (Qp) by correlating with other independent embankment breach parameters for cohesive as well as non-cohesive embankments. The model is validated with historical and laboratory data compiled in the past. For the validation of current investigational work, the experimental data of the present study are compared with the model already developed by other researchers. From the study and analysis, it is observed that breach peak outflow depends upon hydraulic, geometric, and geotechnical parameters of embankments. Being a phenomenon that is active for a short duration only, the manual measurement of various parameters of the modeling process poses some limitations under laboratory conditions.

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