Reservoir sedimentation analysis using empirical methods and HEC-RAS: Panchet Dam, Jharkhand

Abstract

Dams have played a vital role in the development of the economy of the country. Currently, India stands third in the number of dams worldwide, with 5745 large dams, including 411 dams under construction (NLRD, 2019). These dams should be managed to sustain the benefits for humankind and the environment. Sedimentation in reservoirs is one of the significant deterrents for dams. Further, the sedimentation rates have increased due to extreme events. The process of sedimentation not only reduces the reservoir's storage capacity but also affects its proper operation. Traditional management strategies adopted by the dam authorities are check dam, sluicing, flushing, density current venting, sediment replenishment, hydraulic dredging, dry excavation, etc. However, for the practical applicability of these management strategies, reservoir modelling and sediment distribution analysis is vital. Empirical methods and Numerical modelling using HEC-RAS are used to predict the sediment deposition pattern in the reservoir. Initially, a study is carried out on the Bhima reservoir in the Krishna basin, having a gross storage capacity of 3320 MCM, to understand the change in the sedimentation pattern of the reservoir from 1977 to 2011. CWC published Compendium 2020 on Reservoir Sedimentation which showed a cumulative percentage loss of 12.77% in overall reservoir capacity across India with an average rate of sedimentation of 0.815 Th. cum/sq. km/yr. Only empirical methods such as Empirical Area Reduction method and Area Increment method is used. Due to the unavailability of inflow discharge data at the Bhima dam, the study area is changed to the Panchet dam. Further study is conducted for the Panchet reservoir in the Damodar basin using both the empirical methods and HEC-RAS simulation. For the numerical simulation in HEC-RAS, inflow series data, sediment load data, bed gradation are required. The reservoir has data related to past capacity surveys (seven numbers) and inflow data series from 1961 to 2021. For the Bhima reservoir, Empirical Area Reduction method gives the revised capacity as 2896.30 MCM whereas the observed revised capacity is 2896.96MCM. The shape of the reservoir is Type 2 Floodplain foothill type in 1977 which changed to Type 1 Lake type reservoir in 2011. For the Panchet reservoir, EAR method and AI methods are applied for the year 1962,1964,1975,1985,1996 and 2020. For 2020, EAR method shows a correlation of 0.996 and AI method shows a correlation of 0.98. Further, for the prediction of new zero elevation for 2030,2040,2050 Moody’s method is used and EAR method is used for the sediment distribution. For 1D quasi unsteady simulation in HEC-RAS, initially the model is run with taking Larsen (Copeland) as the transport function. After the simulation of model, rating curve analysis is done 5 taking seven different transport functions and comparison is done between the predicted and the observed rating curve. Acker-White gives better result as compared to other transport functions. Also, the sediment deposition of 31.19 MCM is predicted for simulation from 2020-2030. However, the reservoir volume loss for different methods comes out to be different. It is concluded that, using both the empirical methods and the numerical method HEC-RAS, 50 percent of the sediment is deposited in the upper 30-35 percent of depth resulting in the deposition in head reaches, thus observing a longitudinal deposition pattern of delta in the dam. Further, this study emphasizes the importance of sedimentation modelling for proper planning of reservoirs.