Modeling For Optimization of Parameters of Sediment Transport For Cascade Hydropower Projects on Poonch River

Abstract

All lakes and reservoirs created on natural rivers are subjected to sedimentation. This represents a great challenge for the dam engineers and reservoirs’ managers to find appropriate ways and means to slow this phenomenon significantly to improve the sustainability and optimal performance of the reservoirs. Worldwide, there are about 50000 large dams and among them are 25500 storage reservoirs with a storage volume of about 6464 Bm3. Annual reservoir capacity loss due to sedimentation varies between 0.10 and 2.4 percent in the greater parts of the world. Sediment deposition in a reservoir decreases its storage capacity and reduces the life of a hydro power project associated with it which would trigger huge socio-economic impacts. Hence, it is desired to remove the sediment from such reservoirs for which flushing is one of the best techniques. The current study targets to examine sedimentation aspects of two cascade reservoirs on Poonch River; with the help of physical modeling and numerical simulation. The cascade reservoirs, which have smaller storage volume, compared to the annual inflow and shallow water depths than the high head storage reservoirs; without any sediment management, will be silted up over a short period of time. For the sustainability of the project a proper desiltation program is required. For this purpose various techniques can be applied like dredging, hydro suction, dry excavation, sediment by-passing, density current venting, sediment routing, sluicing and flushing sediment through reservoir. Among these approaches, the most economical method for desilting the reservoir is flushing provided that sufficient water discharge is available. This study focuses on investigation of the sediment accumulation, transportation and flushing in cascade reservoirs. Recorded data of Gulpur and Rajdhani Hydro Power Project (HPP) located in a cascade manner on Poonch River in Pakistan administrated Kashmir, was used for this purpose. A physical model of Poonch River was prepared at Nandipur Research Institute to study the sediment transport behavior. After base test the model was used to get data for various scenarios of sediment flushing in the cascade reservoir system. The River geometry, cross-sections, hydraulic structures, river banks and other physical attributes of river were prepared from topographic survey using AutoCAD. These files were used in HEC-RAS and BASEMENT for simulations. Delta profile and flushing were modelled by HEC-RAS 5.0. Simulation showed that life of the un-sluiced Gulpur HPP is about 14-15 years and that of Rajdhani is about 35 years. To enhance the life of project, annually 4-5 days are required for flushing with optimized discharge of about 250 m3/s. Similarly, in the presence of Gulpur HPP, the dead storage of Rajdhani HPP will be filled up in about 57 years (against 35 years without presence of Gulpur HPP) and this will require annual flushing with reference to upstream cascade Gulpur HPP flushing. In cascade HPP the downstream reservoir has to attain an optimum water level (460 masl) before flushing starts in upstream reservoir. The model shows that water level of Rajdhani HPP has to be reduced by 1 meter every year (from 460 to 411 masl for 50 years) to move the delta forming at the tailrace of Gulpur HPP towards the dam face of Rajdhani during annual flushing In addition, the depth-averaged Godunov model was used to simulate a 2D flushing of the reservoir to cross-check the scouring capacity of the reservoir. The solution technique used has shock-capturing characteristics and is particularly suitable for dam breaks with strong deposit transport phenomena. This technique addresses the reservoir erosion and erosion of sediment deposits that produce transient flow conditions in very small time intervals. Model verification was performed by calculating the bed topography and flushing efficiency. This results obtained through the model were consistent with bed changes, demonstrating its suitability for regeneration of regression channels and lateral erosion. The accompanying sensitivity analysis focuses on evaluating the effects of various parameters that are critical for successful flushing simulations.