Hydrological risk assessment for Mangla Dam: compound effects of instant flow and precipitation peaks under climate change, using HEC-RAS and HEC-GeoRAS

Abstract

Dams play a pivotal role in water resource management by storing and supplying water for a multitude of purposes. However, the looming threat of dam breach floods necessitates meticulous research and the simulation of potential failure scenarios. These endeavors are essential not only for comprehending the gravity of dam break floods but also for identifying vulnerable regions and informing emergency response strategies and land-use planning initiatives. This study employs a two-dimensional hydraulic model within the HEC-RAS (Hydrologic Engineering Center and River Analysis System) software to conduct an extensive dam breach analysis specifically focusing on the Mangla Dam located in Azad Kashmir, Pakistan. The analysis encompasses the prediction of various breach parameters, including the hydrograph of the breach flood, peak flow rates, arrival times of the flood, and the creation of inundation maps. Of primary concern is the Probable Maximum Floo, which drives the dam collapse model under unsteady flow conditions, accounting for both piping and overtopping failure scenarios. This study discerns the breach outflow hydrograph through the utility of HEC-RAS tools and evaluates hydraulic conditions at critical downstream locations. To dynamically route flood waves, the breach outflow hydrographs are harnessed. Furthermore, the HEC-RAS model is executed with breach parameters derived from five distinct empirical approaches, with ensuing outcomes subjected to rigorous comparative analysis. A comprehensive sensitivity study pertaining to breach parameters is also carried out to ascertain the sensitivity of peak flow and maximum stage. The results reveal peak flow rates of 174,850 m3/s and 177,850 m3/s in the downstream vicinity adjacent to the dam, translating into corresponding flooded areas of 379 km2 and 394 km2 attributable to piping and overtopping failures, respectively. The analysis of Land Use Land Cover data demonstrates that in the event of piping failure, 217 km2 of agricultural land and 56 km2 of urban areas would be completely submerged. Conversely, overtopping failure would inundate 220 km2 of agricultural land and 59 km2 of urban areas. The utilization of advanced remote sensing data, combined with flood modeling insights, equips engineers and stakeholders with invaluable knowledge. This knowledge, in turn, underpins strategic planning and well-informed decision-making processes, essential for addressing the potential global repercussions of similar catastrophes.