Predicting reservoir sediment inflow under land use variation for hydropower sustainability at Ringlet, Cameron Highlands
One of the greatest challenges of running hydropower is reservoir sedimentation. To ensure hydropower sustainability, reservoir sediment inflow and its relation to future storage and life expectancy must be determined. Ringlet Reservoir in Cameron Highlands has suffered from severe sedimentation due...
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| Format: | text::Thesis |
| Language: | English |
| Published: |
2023
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| Summary: | One of the greatest challenges of running hydropower is reservoir sedimentation. To ensure hydropower sustainability, reservoir sediment inflow and its relation to future storage and life expectancy must be determined. Ringlet Reservoir in Cameron Highlands has suffered from severe sedimentation due to active agriculture and urbanization in the catchment, leading to flooding and deaths in Bertam Valley in October 2013. This research focuses on the prediction of sediment inflow into hydropower reservoir based on methods that have been used locally and worldwide such RUSLE – SDR, RR – SRC and SWAT sediment yield model. From the sampling campaign, total sediment load transport by the rivers in Cameron Highlands was higher for a similar range of flow than other rivers studied in Malaysia. SRC developed was accurate with NSE = 0.68 for Sg Bertam and higher for Sg Telom, Sg Habu and Sg Ringlet. Sg Telom carried 38% of sediment load, 32% by Sg Habu, 22% by Sg Bertam and 9% by Sg Ringlet. MIKE NAM and SWAT both perform satisfactorily in calibration and validation with NSE > 0.65, and used to model flow and sediment load variation from 1999 – 2018. Annual sediment load into Ringlet Reservoir modelled in SWAT was 342,614 m3/year, while MIKE NAM RR-SRC and RUSLE – SDR produced 177, 962 m3/year and 288,132 m3/year respectively. Comparing to the records by TNB, SWAT performed the best with 97% accuracy, as SWAT simulated the impact of land use change on rainfall runoff and sediment yield accordingly, using MUSLE, SCS Curve No and Modified Bagnold sediment transport equation. Prediction by MIKE NAM RR – SRC can be improved by collecting more sediment samples at the downstream part of Sg Bertam. Reservoir storage were also predicted using SWAT, MIKE NAM RRSRC and RUSLE – SDR with 94%, 59% and 84% accuracy. From this study, annual storage loss was 1.2% per year, higher than the world annual rate of 1% and more than 10 times higher than the original design estimate. This puts Ringlet Reservoir as high risk reservoir, which required immediate sediment management plan. With forecast uncertainty of 1.5%-10%, Ringlet reservoir will cease by 2029. Measures such as flushing, sluicing, hydro suction and dredging are most feasible based on RESCON 2 but requires hundreds of million investment from TNB. From this study, sediment yield rate for Cameron Highlands range from 33.1 to 56.9 ton/ha/year, with Lower Bertam, Habu, and Ringlet being the most sediment prone area. These rates are higher than any other areas in Malaysia and it also shows that sediment yield was greatly influenced by land use, slope, catchment area and runoff. Check dams and catchment management in Cameron Highlands are difficult to control sediment yield due to lack of commitment and uncertain source of funding. Nonetheless, methods that were explored in this study should be extended into reservoir sedimentation guideline as per MyDAMS and should be tested on other reservoirs in Malaysia to develop national sedimentation rates for reservoirs in Malaysia. |
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