Sustainable sediment management options for reservoirs: a case study of Chashma Reservoir in Pakistan
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Globally the average annual loss of reservoir capacity is approximately 1%. Pakistan is confronting major issue of sedimentation which is continuously depleting the useful storage of reservoirs. GSTARS3 model was used to determine the rate of deposition and sediment pattern of Chashma Reservoir since its operation. The model was calibrated and validated for bathymetric survey of 2008 and 2012. The results of GSTARS3 were incorporated to a GIS software to visualize sediment accumulation in reservoir. The study reveals that sediment flushing of the Chashma Reservoir can be carried out during flood season at a pond level of 638.15 ft. (194.51 m). However, its negative impact if any on the hydropower generation needs to be analysed. Accordingly, modified operation rules would be required.
KeywordsSedimentation Bathymetric survey GSTARS3 Sediment accumulation Flushing Operational rules
Sedimentation in reservoirs is an outcome of constructing an obstruction in a flowing river, which results in an abatement of the transport capacity of river. The capacity of reservoir diminishes due to silt aggregation and altered sediment balance due to erosion of river downstream. Reservoir sedimentation represents a serious threat to the storage available. Globally, the annual loss rates relative to installed capacity are generally estimated to range between 0.5 and 1% (Mahmood 1987; White 2001; Basson 2009; Schleiss et al. 2010). Pakistan is confronting major issue of sedimentation which is continuously depleting the useful storage of reservoirs. Indus river system has three reservoirs, i.e. Chahsma, Tarbela and Mangla. As per hydrographic survey of 2011–2012, reservoir capacities of Chashma and Terbella have reduced to 60 and 35% of gross storage capacity. Whereas the reservoir capacity for Mangla Reservoir after raising of Mangla dam has been reduced to 1% of gross storage capacity (Pakistan Water and Power Development Authority 2012). All reservoirs trap a portion of the sediment load carried by inflows and, therefore, will experience a continuous reduction in storage volume. The sediment deposition has unfavourable impact, for example, increase in back water level, formation of shoals. Due to the increase in sedimentation flow, regulation diminishes and eventually the reservoir could not achieve its objectives like irrigation, flood mitigation and hydropower generation etc. For a sustainable use of reservoir, it will be necessary to regulate the flows and effective sediment management should be carried out. Since the last few years number of numerical models have been developed and utilized to investigate the reservoir sedimentation problems in rivers and natural streams. Zeleke et al., (2013) used SRH-1D model to predict the sediment inflow to Angereb dam reservoir. The simulation results were in good agreement with the measured sediment deposition in the reservoir. One-dimensional numerical model GSTARS-3 developed by Yang and Simoes (2002) based on theory of minimum stream power has some additional features that it can be applied for determination of channel width while keeping depth as a known parameter for given hydraulic and sediment routing conditions.
Yang and Simoes (2002) applied GSTARS-3 model for simulation of sedimentation and delta movement in Terbela Reservoir in Pakistan. The profile of the bed simulated using GSTARS-3 was in good agreement with the measured profile. In the present study, GSTARS-3 (Generalized Sediment Transport for Alluvial Ricers) sediment transport model along with GIS software was used to determine (1) sediment inflow to Chashma Reservoir, (2) sediment pattern and rate of deposition in the Chashma Reservoir and (3) to explore the ways to enhance the life of reservoir based on various operational scenarios for sediment management.
Location of the study area
The processes involved in this study include data collection, data analysis and selection of suitable transport model. Calibration of the model is done before hydraulic and sediment routing computation for Chahsma Reservoir. GSTRAS-3 is capable of performing hydraulic and sediment routing computations both in longitudinal and lateral directions. Furthermore, it is also capable of computing channel geometry with fixed or movable boundary conditions.
Following necessary data were collected and used for GSTARS3 sediment transport model:
Cross-sectional geometry was defined by X–Y coordinate which is a lateral location and bed elevation. Lateral locations (X) were given using a reference point for each cross section, and the coordinate pair was entered in order of increasing X coordinate, i.e. starting from the left-hand side of the cross section and marching towards the right-hand side (looking downstream). In this study, 15 cross sections were used to cover entire reservoir for modelling purposes.
Hydrological data include water discharges, temperatures and water surface elevations. Daily discharge data for Chashma Barrage for the year 1971–2012 was collected from surface water hydrology project (SWHP), WAPDA. Mean annual flow for Chashma Reservoir is 117,000 ft3/s (3313 m3/s) whereas the peak annual discharge is 313,627 ft3/s (8881 m3/s). Discharge required for flushing of reservoir should be twice of mean annual flow available. Therefore, flushing of Chahsma Reservoir was performed for an available discharge of 2,340,000 ft3/s (6626 m3/s). Flushing discharge is available during flood season for two months, i.e. July–August.
Calibration of model
Validation of model
After calibration and validation model was applied for future application from 2013 to 2054 for five different operational scenarios. The adjusted GSTARS3 model was applied for 10-, 20- and 42-year simulation period. The results of above five scenarios are as follows:
Performance of GSTARS3 sediment transport model was assessed statistically using MAPE, Nash–Sutcliffe efficiency and R2. Nash–Sutcliffe efficiency is a statistical tool which is used to compare the simulated results with the actually observed bathymetric survey data. NSE values for calibration and validation of sediment transport model were found as 0.64 and 0.45 with the coefficient of determination 0.67 and 0.70. The difference between measured and simulated thalweg for calibration and validation of sediment transport model was found as 0.55 and 1.5%. Yang (2008) compared the sediment simulation results of Tarbela Reservoir with the bathymetric survey in Pakistan and concluded that the error less than 20% is acceptable between the measured and simulated results.
GSTARS-3 software is capable to determine the amount of sediment accumulated in the reservoir as well as the amount of sediments that exit the river reach. Amount of sediments deposited in the Chashma Reservoir during calibration and validation of model were 9.283 × 108 and 9.437 × 108 Ton, respectively. However, it is reasonable to compare this with Terbela Reservoir in Pakistan where amount of sediments entered into the reservoir were 1.01 × 1010 Ton from 1976 to 1994. Similarly, the amount of sediments deposited in Tapu Reservoir in Thailand was 2.3 × 106 Ton from 1987 to 1990. Both of these reservoirs were also modelled using GSTARS-3 sediment transport model.
Sediment trap efficiencies
Sediment trap efficiency (%)
Integrating GSTARS3 results to GIS software
Average sedimentation rate in reservoir till 2012 is estimated as 0.0124 MAF/year (0.015 BCM/year).
The storage capacity of Chashma Reservoir would deplete to 0.233 MAF (0.287 BCM) (73% loss) in the year 2054 for scenario-1 (under existing conditions).
Scenario-2 is more effective as 23% of reservoir capacity was recovered after 15 days of flushing and sediment trapped in the reservoir was lesser than the other flushing scenarios. The trap efficiency for Scenario-2 ranges between 43 and 11%.
Depositional patterns in Chashma Reservoir showed that sediment movement towards the power channel increases. This would cause the negative effect on the power generation and also wear and tear of turbines.
Authors are highly thankful to the SWHP (WAPDA) for providing inflows and sediment data and Mangla dam organization (MDO) for providing hydrographic surveys and reservoir levels. Furthermore, this research was made for partial fulfilment of M.Sc. thesis requirement.
- Basson GR (2009) Management of siltation in existing and new reservoirs. General Report, paper presented at the 23rd congress of the international commission on large dams, Int. Com. on Large Dams, BrasiliaGoogle Scholar
- Batuca DG, Jordaan JM Jr (2000) Silting and desilting of reservoirs. CRC Press, 1 Jan 2000Google Scholar
- Mahmood K (1987) Reservoir sedimentation, impact, extent, and mitigation. World Bank technical paper no 71, Washington, DC, USAGoogle Scholar
- Pakistan Water and Power Development Authority (2012) 5th Hydrographic survey of Chashma Reservoir. International Sedimentation Research Institute, Pakistan (ISRIP)Google Scholar
- Schleiss A, De Cesare G, Althaus JJ (2010) Verlandung der Stauseen gef€ahrdet die nachhaltige Nutzung der Wasserkraft. Wasser Energ. Luft 102(1):31–40Google Scholar
- Shah MU (2010) Assessment of Chashma Reservoir sedimentation using HEC-RAS. MSc thesis, University of Engineering and Technology, Lahore, p 148Google Scholar
- Yang CT, Simoes FJM (2002) User’s manual for GSTARS3 (Generalized sediment transport model for alluvial river simulation version 3.0). U.S. Bureau of Reclamation Technical Service Center, Denver, ColoradoGoogle Scholar
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