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Operational hydrometric network is an essential element in hydropower reservoir operation. The data collected, to be used for reservoir management and decision making require high reliability with automatic data monitoring, processing and retrieval. However, the unique characteristic of every catchment and operational requirements raises the need t...
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... overall objective of this study were to develop a system capable of monitoring rainfall, inflows and lake level at Temengor for hydropower reservoir operated by Tenaga Nasional Berhad (TNB). Figure 1. These dams are used for hydroelectric power generation, operated by Stesen-stesen Janaelektrik Sungai Perak (SSJ Sg Perak). ...
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... One of the critical factors that contribute to successful hydropower reservoir management is through reliable monitoring infrastructure, equipment and technology. Therefore, the continuous monitoring of inflow is an essential tool for hydropower dam operators by providing real-time data for decision making in power generation and planning (Basri et al., 2019). This is the main reason of why most of the governments and water supply companies today continue to face the problems when it comes to the control management of dams. ...
The field investigation of the reservoir area of Baglihar Hydropower project shows that the sediment budget to the reservoir is controlled by fragile rock type like shales, sandstones, phyllites and slates, soil characteristics, steep hill slopes, rainfall and landslides. The rocks are highly weathered, fissile and micaceous in nature and very sensitive to water absorption. The analysed sediments are characterised by dominance of sands, silts and clays with lower values of plasticity (14.3PL), liquidity (23.5 LL), cohesion (118) and shear strength (202 Kpa). The slope wash deposits are highly susceptible to landslides and slope failures and directly contribute to the sediment budget in the reservoir. In addition tributaries of Chenab River also bring sediments in the reservoir from the catchment area. The empirical relationship for estimating the long-term reservoir trap efficiency for large storage based on correlation between the relative reservoir size and trap efficiency was simulated in 3D model which shows that the annual sediment trap efficiency of the Baglihar reservoir is of 0.39%. The extrapolation of the calculated values shows that the total sediment load shall increase by 11% in the next 30 years and 20% in the next 50 years and correspondingly 40% in the next 100 years that shall induce corresponding decrease in the reservoir volume over the time. By applying flushing schemes, life span of the reservoir can be extended. It is estimated that after 100 years the reservoir shall lose ~35.6% storage volume. On further extrapolation, the trap efficiency will decrease from 25.5% after 30 years to 23% after 100 years. The estimated trap efficiency of Baglihar reservoir is 60%, which is greater than that based on numerical results, showing a significant overestimation.
... The findings of this study show that applying the numerical model offers good prediction of the different climate level change impacts on lake basin hydrology and ecosystem. Additional installation of hydrometeorological monitoring equipment will further support the modelling prediction [11]. ...
Climate change is affecting inland waterbodies such as reservoirs worldwide by altering the hydrological processes such as rainfall amount and the surface water evaporation. These changes shape the reservoir water level and subsequently affect dam storage capacity and functioning and the overall lake ecosystem including pattern of aquatic plant occurrence. In this study, the application of numerical modelling was performed to improve understanding on the impact of climate change on lake hydrology and water level in Beris Reservoir, Kedah in Malaysia. By incorporating land use pattern, hydrology, dam characteristics and operations as the variable parameters, hydrologic-hydraulic model was constructed using the integrated catchment model (ICM) approach. Calibration was performed using reservoir water level and rainfall amount at 2 rainfall stations near the catchment over 6 months. Two future hydroclimate projection data at the lake catchment (6 km grid resolution) are used to simulate the climate change impacts on the reservoir. Based on the simulation, the water balance of Beris reservoir is very sensitive to rainfall changes and the river water release for downstream water intakes. Frequency of changes in water level between the two scenarios provided better understanding on the potential occurrence of aquatic plants requiring reservoir management. The findings show that the numerical model predicts well the different climate change impacts on lake basin hydrology and ecosystem.
Catastrophic dam failures result in significant loss of lives and immense property damage worldwide. The causes of dam failures are primarily attributed to three major triggers: climate change, ageing dams, and cyber threats. Understanding the correlation between these factors is vital to provide a comprehensive solution in the dam safety sector. The authors propose a new method called risk-informed decision-making (RIDM). RIDM evaluates the likelihood of loading scenarios, potential failure modes, and economic and social consequences to compute the risks for dams on the Perak River. The study aims to identify probable failure modes, evaluate consequences, and develop mitigation measures and conceptual designs. The study will include several stages, such as gap analysis and dam safety evaluation, followed by a Risk-Based Screening Tool to obtain the initial risk results. Failure mode identification will be made through detailed technical visits and participatory working sessions involving key staff in maintenance, operation, and safety management. Developing a quantitative risk model will quantify the risk according to the specified fundamental failure modes. The final risk results will recommend and evaluate mitigation measures to ensure a resilient dam for a safe community. Additionally, a secure dam safety database system will be developed as an efficient tool to manage various data types to assist the dam owner in decision-making.
The inflow forecasting system is an essential tool to assist dam owners in decision making and planning. Effective and optimized hydropower reservoir operation, monitor and forecast inflows and lake level to provide benefits in maximizing energy revenue, while taking into account dam safety risks. The Temengor Inflow Forecasting System for Temengor dam was developed in a robust system that runs on a real-time modeling platform. Reservoir inflow forecast results must be able to provide a timely and accurate forecast for appropriate reservoir management. Thus, it is essential to monitor the performance of the forecasting system to ensure the developed system is performing to its maximum potential. This paper discussed the performance of the Temengor inflow forecasting system. In general, the comparison of forecast model results with observed data shows that the model is able to provide good forecast accuracy. Continuous model performance monitoring enables reliable forecast results, which can be used for future resource availability for hydropower generation and advance warning of water-related disasters such as a flood.
