RESUMO
The primary purpose of this study was to evaluate the hydraulic coefficient of coarse aggregate grain size beds and hydraulic parameters under random and perpendicular bed configurations, as well as to explore the discharge coefficient for rectangular weirs. The research objectives were to compare flow resistance coefficients, evaluate the discharge coefficient for rectangular weirs, investigate the relationship between roughness coefficient and hydraulic parameters, and validate the theoretical hydraulic equation for the rectangular weir. This was achieved by analysing different bed configurations, bed slopes, and 20 and 30-mm bed materials. Sieve analysis was conducted on bed materials using American-standard sieves to determine their particle size distribution. The experiment was performed in a rectangular flume measuring 12 m in length, 0.31 m in width, and 0.45 m in depth. In a laboratory experiment, water was pumped into a flume using centrifugal pumps, and a rectangular weir was attached downstream for discharge measurement. The experiment investigated factors such as Manning roughness coefficient, bed material geometry, bed slope, and weir shapes. Approximately 1680 tests were conducted to analysed the impact of these factors on discharge and the coefficient of discharge. The average Manning's roughness coefficients for a grain size of 20 mm were 0.019 (with weir) and 0.019 (without weir) in a random bed configuration, and 0.028 (with weir) and 0.027 (without weir) in a perpendicular flow bed configuration. For a grain size of 30 mm, the coefficients were 0.023 (with weir) and 0.022 (without weir) in a random bed configuration, and 0.033 (with weir) and 0.026 (without weir) in a perpendicular flow bed configuration. The presence of a weir has affected Manning's roughness coefficients and discharge coefficients. With a weir, the roughness coefficients have generally been higher compared to without a weir, indicating increased roughness in the channel. The discharge coefficient for a rectangular weir with a grain size of 20 mm ranged from 0.39 to 0.84 (random bed) and 0.27 to 0.68 (perpendicular flow bed), while for a grain size of 30 mm it ranged from 0.31 to 0.81 (random bed) and 0.23 to 0.48 (perpendicular flow bed). The discharge coefficients have varied depending on the grain size and bed configuration, reflecting different flow efficiencies over the weir. Rough particles influenced flow and Manning's roughness coefficient value, then reduced discharge and velocity values. Under two bed configurations and slopes, beds with a grain size of 30 mm have higher roughness coefficients compared to those with a grain size of 20 mm. The models have shown that the roughness coefficient is inversely proportional to the discharge and directly proportional to the tailgate water levels. The coefficient of roughness and discharge coefficient are mainly influenced by the channel slopes, bed roughness, bed grain size, and bed configuration. A randomly configured bed with a 20 mm grain size gravel bed is preferred over a perpendicular bed configuration to handle high discharges. Using a 20 mm grain-size gravel bed in open-channel flow is more suitable than a 30 mm grain-size bed. Relying on the constant friction factor, Manning's n, is not recommended as it may result in design errors. These findings have the potential to improve hydraulic engineering design practices, enhancing the accuracy and efficiency of open-channel flow systems.
RESUMO
The research aims at determining the optimal release rule to increase the capacity of Rib reservoir. The reservoir inflow using HBV-light hydrological model embracing optimal reservoir operation through HEC-ResSim model were used to prepare an optimum operational plan. The potential of the river for hydropower generation prioritise the demand at a specified level regarding storage capacity (m3), level of reservoir (m), and the relation between inflow and outflow of the reservoir. From the model performance features, the coefficient of correlation (R2) and Nash Sutcliffe Efficiency (NSE) were determined to be, respectively, 0.77 and 0.73 for calibration and 0.72 and 0.70 for validation. The Sobol approach was used for detailed sensitivity analysis of DROP model parameters based on the performance of C2M on outflows and volumes. The results suggest that the threshold coefficient characterizing the demand-controlled release level is the most significant parameter. According to the simulation's findings, the reservoir's average regulated release is calculated to be 22.86 m3/s, and its average monthly hydropower output is 6.73 MW. Average annual hydropower energy was estimated as 58.955 GW h/year and mean annual inflow of reservoir volume of water to be 223.54 Mm3. This volume of water is adequate to accommodate total annual irrigation demand, environmental obligation, and other respective requirements in the downstream. The demand for hydropower and irrigation and supply from reservoir capacity can be counterbalanced from the simulated result without any hindrance.
