Downstream Water Level Research Articles

Optimization and Regulation Method for Large Blade-regulating Pump Stations Considering Safety Constraints

Abstract In plain areas, making flood control and drought resistance a heavy task. Large water pumping stations undertake the important task of water lifting and scheduling. Due to the physical characteristics of large pumping stations, they are often affected by the upstream and downstream water levels during water lifting scheduling, resulting in low head operating conditions. Low head operating conditions can easily cause pumping stations to operate at excessive power, thereby affecting the health of pumping station equipment. Based on the head efficiency curve of a large blade regulating pump station in this article, by optimizing the regulating mathematical model and considering constraints such as water level, flow rate, power, efficiency, and blade angle adjustment time interval under low head conditions, a dynamic programming calculation method is adopted to construct an optimized regulating method for the pump station. Based on real-time water level, various operating data of the unit are optimized to ensure the blade angle, power, and the flow rate and other parameters are all within the safety constraint range. And various operating data could be used to guiding the real-time optimization and adjustment of the pumping station, and additionally providing the operating foundation for the intelligent pumping station.

Analysis of the influence of the daily regulation of power stations on navigable flow conditions at river confluences using the LSTM model

The daily operations of large hydropower stations on rivers induce frequent variations in downstream water levels and flow velocities, resulting in unsteady and complex hydraulic characteristics at the confluence of the main stream and its tributaries, which adversely affect navigation safety. The continuity and momentum equations, along with the RNG k-ϵ turbulence model and the VOF model, were employed to simulate the river flow process at the confluence under unsteady flow conditions. The simulated results for water levels and velocity vector fields are in good agreement with experimental data. Variations in hydraulic characteristics, including water level, flow velocity, and longitudinal gradient at the confluence of the main stream and its tributaries, were analysed. The results indicated that the water level at the confluence decreases when the tributary merges with the main stream. As the confluence ratio increases, fluctuations in the water level at the confluence decrease. However, an increase in the staggered period results in greater fluctuations in the water level within this region. Moreover, a crescent-shaped high-speed flow region is formed at the confluence of the tributary and the main stream. As the unsteady flow discharge of the main stream increases, the relative area of this region correspondingly enlarges, reaching its maximum at peak discharge, and subsequently gradually diminishes as the discharge decreases. Based on these simulation data, a Long Short-Term Memory (LSTM) model was developed to effectively predict water levels and flow velocities, providing a more convenient and accurate method for obtaining real-time information on confluence areas than traditional mathematical and statistical approaches. This study provides novel insights into predicting flow characteristics in confluence areas, thereby offering a basis for formulating navigation safety plans.

Research on efficiency simulation model of pumping stations based on data-driven methods

The operational efficiency error of a pumping station unit is affected by several factors, resulting in a large error between the theoretical and actual pumping efficiencies. To solve the problem of accurately simulating the operating efficiency of the pumping station unit, this study conducted research on efficiency simulation models of pumping based on data-driven from three aspects: ①model algorithm, ②feature input and ③response output. In this study, eight machine learning models were introduced to establish pumping unit efficiency simulation models and they were compared with the traditional polynomial regression models, and the models with better performance were selected. Then the experiment proposed using “upstream water level + downstream water level” (UWL + DWL) instead of the traditional “head” (H) as feature input to train the models, and discussed the effects on efficiency simulation accuracy with direct fitting efficiency and fitting power then calculate the efficiency through formula. An example analysis was carried out using the historical data of eight units at Pizhou Station and Suining 2nd Station on the East Line of the South-to-North Water Diversion Project. The experimental results show that ① among all methods, the models based on Gaussian Process Regression (GPR) has the most accurate in ERMS, EMA, R², and EMI indicators, R² is close to 0.92. ②After UWL + DWL was used to train the models, all the test set indicators of the GPR models improved, and the EMA indicator decreased from an average of 0.39–0.26 %. ③ The study found that the fitting efficiency directly is better than the calculation efficiency after fitting the power, but the R² of fitting the power is better than the efficiency, which may provide another idea for the optimal goal of economic operation of pumping stations. ④ On the whole, trainning the GPR models with UWL + DWL to simulate efficiency has the highest precision, for example the EMA and EMI indicators of No.4 unit in Pizhou station can be reduced from 16.49 % and 20.40–0.18 % and 1.55 % respectively. The research results have practical significance and can provide strong support for the economical operation of pump stations.

Evaluation of a Coupled CFD and Multi-Body Motion Model for Ice-Structure Interaction Simulation

The interaction of water flow, ice, and structures is common in fluvial ice processes, particularly around Ice Control Structures (ICSs) that are used to manage and prevent ice jam floods. To evaluate the effectiveness of ICSs, it is essential to understand the complex interaction between water flow, ice and the structure. Numerical modeling is a valuable tool that can facilitate such understanding. Until now, classical Eulerian mesh-based methods have not been evaluated for the simulation of ice interaction with ICS. In this paper we evaluate the capability, accuracy, and efficiency of a coupled Computational Fluid Dynamic (CFD) and multi-body motion numerical model, based on the mesh-based FLOW-3D V.2023 R1 software for simulation of ice-structure interactions in several benchmark cases. The model’s performance was compared with results from meshless-based models (performed by others) for the same laboratory test cases that were used as a reference for the comparison. To this end, simulation results from a range of dam break laboratory experiments were analyzed, encompassing varying numbers of floating objects with distinct characteristics, both in the presence and absence of ICS, and under different downstream water levels. The results show that the overall accuracy of the FLOW-3D model under various experimental conditions resulted in a RMSE of 0.0534 as opposed to an overall RMSE of 0.0599 for the meshless methods. Instabilities were observed in the FLOW-3D model for more complex phenomena that involve open boundaries and a larger number of blocks. Although the FLOW-3D model exhibited a similar computational time to the GPU-accelerated meshless-based models, constraints on the processors speed and the number of cores available for use by the processors could limit the computational time.

The influence mechanism of the submerged dikes on the three-dimensional hydrodynamic characteristics at the 90° confluence

The confluence area serves as the pivotal control unit in natural rivers, and the implementation of spur dikes at the confluence enables regulation of flow patterns, influences pollutant mixing, and safeguards against river scouring. This study establishes a three-dimensional hydrodynamic model for the 90° confluence with dikes, aiming to explore the impact of the number, angle, and spacing of the dikes on hydrodynamic characteristics at 90° confluence. The results show that (i) the closer the spacing between the dikes, the wider the range of low water level area upstream becomes. An increased number of dikes makes it easier for the downstream water level to recover. (ii) The area of the high turbulent kinetic energy region increases with the increase in the number of dikes. Among the three angle deployments, the dike deployment angle of 60° corresponds to the largest area of high turbulent kinetic energy. When the spacing between dikes is 0.225 m, it results in the largest area of high turbulent kinetic energy. (iii) The number or spacing of dikes exhibits a negative correlation with the shape parameters of the separation and backflow behind the dikes, whereas there is a positive correlation between the angle of dikes and these shape parameters. (iv) Influenced by the deployment of dikes, novel helical flows will be generated around the dikes at the confluence. The helicity of the clockwise helical flow is comparatively smaller than that of its counterclockwise counterpart. Subsequently, newly generated helical flows undergo fusion and division as it progresses downstream.

Short-term load distribution model for cascade giant hydropower stations with complex hydraulic and electrical connections

The cascade giant hydropower station system (CGHSS) has been widely applied in countries with abundant water resources. However, the dense hydropower stations and power grids bring complex hydraulic and power connections, including the backwater effect, multiple hydroplants sharing one reservoir and one-reservoir multiple dispatch power grid, which leads to modelling difficulties and inefficient model solving. To address these challenges, a short-term load distribution (SLD) model considering complicated hydraulic and electricity constraints is developed. First, the discharge of each hydroplant and the downstream forebay water level are used as inputs to construct a multivariate nonlinear function, and the average tailwater levels are obtained. Second, a head constraint considering the shared water level is added to the model to calculate the head of each hydroplant, making the output more accurate. Finally, the nonlinear constraints are linearly reconstructed using the Big-M method, triangulation technique and special ordered sets to reduce the model solution time. The SLD model is applied to the Xiluodu-Xiangjiaba cascade hydropower system in the Jinsha River. The results show that the developed model reduces water consumption by 4.02 %, 4.70 %, 5.79 % and 5.28 % compared to the constant proportional distribution model and the real operation, generating a more executable SLD scheme.

Forecasting of compound ocean-fluvial floods using machine learning

Flood modelling and forecasting can enhance our understanding of flood mechanisms and facilitate effective management of flood risk. Conventional flood hazard and risk assessments usually consider one driver at a time, whether it is ocean, fluvial or pluvial, without considering the compound nature of flood events. In this paper, we developed a novel approach for modelling and forecasting compound coastal-fluvial floods using a two-step framework. In step one, a hydrodynamic model is used to simulate floodwater propagation; while in step two, machine learning (ML) models are used to generate flood forecasts. The architecture of hydrodynamic-ML forecasting system incorporates a hydrodynamic model covering a specific domain, with individual ML models trained for each pixel. In total 7 ML models including: Support Vector Regression (SVR), Support Vector Machine (SVM), Radial Basis Function (RBF), Linear Regression (LR), Gaussian Process Regression (GPR), Decision Tree (DT), and Artificial Neural Network (ANN) were applied in this study. Forecasting compound floods is achieved using two sets of inputs: timeseries of river discharges in the upstream fluvial section and downstream ocean water levels in the coastal areas. The accuracy of the flood forecasting system is demonstrated for Cork City, Ireland; and modelling performance was evaluated using several statistical tools. Results show that the proposed models can provide reliable estimates of flood inundation and associated water depths. Overall, the RBF model exhibits the best performance. Despite the complexity of compound multi-driver floods, this study shows that the coupled hydrodynamic-ML approach can forecast coastal-fluvial flood with limited hydraulic and hydrological input data. This system overcomes the limitations of traditional hydrodynamic model-based systems where trade-offs between the always competing numerical model accuracy and computational time prohibit the model to be used for short-term flood forecasting. Once trained, the ML component of the coupled system can perform flood forecasting in near real-time, potentially integrating into a flood early warning system. Accurate flood forecasting has a wide range of positive societal impacts, including improved flood preparedness, increased confidence, better resource allocation, reduced flood damage, and potentially even flood prevention.

Characteristics and causes of water level variations in the Chenglingji–Jiujiang reach of the Yangtze River following the operation of the Three Gorges Dam

ABSTRACT Water level adjustment downstream of dams significantly impacts river regimes and flood control. However, due to constant strong scouring, our quantitative understanding of the characteristics of water level variations and their causes in the Chenglingji–Jiujiang Reach of the Yangtze River remains limited. Here, we analyzed the water level change trend via the Mann–Kendall method and analyzed geomorphic change and river resistance using 406 cross-sectional profiles as well as data on discharge and water levels from 1991 to 2022. Results showed that the critical conversion discharges (CCD) in the Chenglingji-Hankou Reach and the Hankou-Jiujiang Reach were approximately 35,000 and 30,000 m3/s, respectively, after the operation of the Three Gorges Dam. The water level exhibited an overall decline mainly due to river erosion when the discharge was lower than the CCD. The water level exhibited a nonsignificant upward trend mainly due to increased river resistance (7–20%) when the discharge was higher than the CCD. The obvious increase in the floodwater level in individual years was caused by the effect of downstream water level increase. Our findings further the understanding of downstream geomorphic response to dam operation and their impacts on water levels and have important implications for flood management in such rivers worldwide.

Study of intermittent jets and free-surface-pressurized flow in large hydropower tailrace tunnel

The tailrace tunnel system, as a core component of hydroelectric power stations, directly influences the stability and efficiency of the power generation process. Transient conditions often lead to the occurrence of complex unsteady flow phenomena in the tailrace tunnel. In this study, numerical methods integrating open channel flow, multiphase flow, and compressible models were combined to conduct hydraulic analysis of the tailrace system in large hydroelectric power stations. Under specific conditions, periodic jet phenomena were observed, corroborating field observations. The research revealed that the proximity of downstream water levels to the crest level of the tailrace outlet is a prerequisite for the periodic jetting phenomenon, with a sudden rise in water level serving as a triggering condition. Although the surge shaft effectively mitigates wave action, it fails to entirely eliminate the influence of pressure pulsations, resulting in a 23.2% increase in pressure pulsation amplitude in the turbine area. However, the efficiency of the turbine unit is hardly affected; only a slight loss of energy occurs due to the increase in local turbulent entropy production, deemed inconsequential for the overall system. This study aims to investigate the complex response of tailrace tunnel systems in hydroelectric power generation amidst abrupt changes in downstream river, providing crucial insights for the engineering design and operation of large-scale power stations.

Modeling of an Irrigation Main Canal Pool based on a [formula omitted]-[formula omitted] System Identification

Dynamic models of main irrigation canals are necessary to carry out real-time canal flow control and supervision. Since the hydraulic equations of canal dynamics are nonlinear, their solution involves large computations that impede their use in real-time applications. Then these tasks are often implemented using simple local linear models obtained around an operating point, that are unable to capture the dynamics when large canal operation changes happen.In this paper, we propose a nonlinear dynamic model for main irrigation canal pools based on a new Artificial Neural Network (ANN). This ANN outperforms the above local models because it includes a new input which is the downstream water level of the previous pool. This new architecture with this new input yields models that accurately reproduce the behavior of the canal in a wide range of operations while being simple enough to allow real-time control and supervision. The high accuracy of the proposed model as regards reproducing the observed data is validated for different flow regimes based on experiments developed in a laboratory prototype of the hydraulic canal and in a real main irrigation canal.The contribution of this work is such a general and accurate but simple model of the dynamics of a canal pool. Its novelty is not only being able to reproduce the behavior at different operating points of the canal but also being able to reproduce, in a single model, the free and submerged flow regimes — which are described by dynamic equations with different structures. Moreover, we implement a new classification model to recognize the flow regimes of the irrigation canals using pattern recognition.

Machine Learning-Based Flood Forecasting System for Window Cliffs State Natural Area, Tennessee

The prevalence of unforeseen floods has heightened the need for more accurate flood simulation and forecasting models. Even though forecast stations are expanding across the United States, the coverage is usually limited to major rivers and urban areas. Most rural and sub-urban areas, including recreational areas such as the Window Cliffs State Natural Area, do not have such forecast stations and as such, are prone to the dire effects of unforeseen flooding. In this study, four machine learning model architectures were developed based on the long short-term memory, random forest, and support vector regression techniques to forecast water depths at the Window Cliffs State Natural Area, located within the Cane Creek watershed in Putnam County, Tennessee. Historic upstream and downstream water levels and absolute pressure were used to forecast the future water levels downstream of the Cane Creek watershed. The models were tested with lead times of 3, 4, 5, and 6 h, revealing that the model performances reduced with an increase in lead time. Even though the models yielded low errors of 0.063–0.368 ft MAE, there was an apparent delay in predicting the peak water depths. However, including rainfall data in the forecast showed a promising improvement in the models’ performance. Tests conducted on the Cumberland River in Tennessee showed a promising improvement in model performance when trained with larger data.

Vibration analysis of metallic structure of an innovative dam gate

An analysis of the vibrations that may occur at the gate of a dam is proposed. Thus, the determination of an optimal constructive solution is sought from the point of view of vibration behavior. The dam gate is part of a constructive solution of an oscillating center pivot dam, which closes the gates if the downstream water level rises above a certain limit. This constructive solution is new. The gates are controlled by the water level. Such a system is easy to implement practically and the construction and maintenance costs are lower than in the case of classic dams. The problem that arises is that of the behavior of such a structure to vibrations. The eigenvalues of the gate structure are determined for a constructive solution proposed by the designers and the behavior of the forced vibrations that can stress the gate is studied. The analysis is performed for the case where the dam gates are closed. The work continues previous research on the structure's resistance to static loads and justifies the use of this solution in design. The method used to carry out the study is the finite element method. The advantages of the studied structure consist of lower costs for the proposed relatively simple constructive solution.

Long-term water level dynamics in the Red River basin in response to anthropogenic activities and climate change

Understanding the regular variations in water levels and identifying the potential drivers under the combined pressures of anthropogenic activities and climate change can offer valuable insights into riverine management. In this study, we analyzed long-term daily observational data, including water levels and water discharge, spanning from the ~1950s to 2021 at seven gauging stations within the Red River basin. We investigated the spatiotemporal variation in mean water levels using standard analytical tools, including the Mann-Kendall (MK) test, rating curves, and Empirical Orthogonal Function (EOF). Specifically, we observed a notable and substantial decline in water levels downstream of the major tributaries, including Da, Red, and Lo Rivers, as well as at their confluence, starting at the end of 2008. Notably, a strong correlation between water levels and discharge is found, highlighting the pivotal role of discharge in influencing water levels. Surprisingly, relationships between water levels and climatic factors such as rainfall and air temperature proved less influential. This suggests that water levels are predominantly shaped by discharge and anthropogenic activities, rather than climate change. The study emphasized the substantial impact of human-induced activities, particularly dam operation and sand mining, on downstream water levels in the Red River basin. An intriguing finding revealed that upstream dynamics, particularly at the Hoa Binh dam, led to significant water level increases with the same discharge, attributed to channel deposition and reservoir water storage. The research's novelty is the comprehensive evaluation of long-term water level trends and its elucidation of the combined effects of anthropogenic activities and climate change, offering valuable insights for riverine management and emphasizing the influence of anthropogenic factors, notably dam regulation and sand mining, in driving shifts in water levels.

Using hydraulics to evaluate ecological benefits, risks, and trade‐offs from engineered flooding

AbstractRegulation and water extraction have reduced river flow worldwide. In some rivers, this has led to reductions in the frequency and duration of floodplain inundation and, in turn, declining condition of flood‐dependent vegetation. One management response has been the construction and modification of infrastructure, or ‘regulators’, to engineer floodplain inundation at discharges that do not otherwise cause overbank flooding. Such actions have the potential to benefit floodplain vegetation, yet the atypical hydrodynamics of engineered floods may threaten riverine ecological processes and biota and increase the risk of adverse water quality. We investigated the influence of engineered flooding, and associated reductions to in‐channel hydraulics, on key ecological processes. Specifically, the transport and retention of larvae of an iconic fish species (Murray Cod, Maccullochella peelii), and a common microinvertebrate Trichocerca. Analysis of different flow management scenarios for floodplain inundation indicates that maintaining in‐channel velocities greater than 0.2 m s−1 produces higher Trichocerca densities, while velocities greater than 0.3 m s−1 creates suitable habitat for Murray cod larvae, thereby providing targets for avoiding detrimental effects of engineered floods on in‐channel biota. To evaluate responses to regulator operation, velocity was represented by a hydrological model using pre‐computed results from detailed hydrodynamic models. These results were used to relate upstream discharge and downstream water level to the proportion of each reach in the hydrological model meeting each velocity criterion. The model also represents changes in discharge, inundated area and a water quality parameter, dissolved oxygen. Model scenarios for engineered floodplain inundation were used to demonstrate the potential benefits, impacts and trade‐offs between the different metrics identified. The model framework enables a more holistic evaluation of infrastructure operation, extending analysis beyond discharge and inundated area to risks and benefits to key indicators of the ecosystem. This refined integrated approach to the management of regulated river systems may become critical in the future where water resources are projected to further decline under a changing climate.

Sensitivity analysis of factors affecting gravity dam anti-sliding stability along a foundation surface using Sobol method

The anti-sliding stability of a gravity dam along its foundation surface is a key problem in the design of gravity dams. In this study, a sensitivity analysis framework was proposed for investigating the factors affecting gravity dam anti-sliding stability along the foundation surface. According to the design specifications, the loads and factors affecting the stability of a gravity dam were comprehensively selected. Afterwards, the sensitivity of the factors was preliminarily analyzed using the Sobol method with Latin hypercube sampling. Then, the results of the sensitivity analysis were verified with those obtained using the Garson method. Finally, the effects of different sampling methods, probability distribution types of factor samples, and ranges of factor values on the analysis results were evaluated. A case study of a typical gravity dam in Yunnan Province of China showed that the dominant factors affecting the gravity dam anti-sliding stability were the anti-shear cohesion, upstream and downstream water levels, anti-shear friction coefficient, uplift pressure reduction coefficient, concrete density, and silt height. Choice of sampling methods showed no significant effect, but the probability distribution type and the range of factor values greatly affected the analysis results. Therefore, these two elements should be sufficiently considered to improve the reliability of the dam anti-sliding stability analysis.

Combining process-based model and machine learning to predict hydrological regimes in floodplain wetlands under climate change

Climate change has remarkable effects on the hydrological regime in floodplain wetlands. However, the hydrodynamic simulation under climate change conditions suffers from the uncertainty of the downstream water level boundary. In this study, an effective approach was developed by integrating an advanced machine learning algorithm and a process-based watershed hydrological model to predict the lake level under climate change. The developed approach was validated in a vital conservation wetland in the Ramsar Convention, the Poyang Lake floodplain wetland in China and utilized to simulate the hydrological regime in climate change. We found that the Long Short–term Memory (LSTM) performed relatively well in the simulation of water level, with coefficients of determination (R2) of 0.94 and 0.83 in the training and testing periods, respectively. The mean cumulative flooding time in the future period was slightly less than that in the baseline period, with a decreased range of 1.01 ∼ 12.05 days/year. The highest and mean water levels rose significantly in the wet season, with a risen range of 1.01 ∼ 3.3 and 1.56 ∼ 2.44 m, respectively, and the appearance of extreme flood events became more frequent. The maximum, minimum, and mean inflows for Poyang Lake in the dry season exhibited a remarkable reduction trend, especially for the minimum inflow, with a reduced range of 59.37%∼79.22%, indicating that more serious extreme drought events would appear in Poyang Lake. The developed approach has good performance for water level simulation and extreme runoff prediction, thus providing a viable way for future water resources management in floodplain wetlands.

Study on the Hydraulic Response of an Open-Channel Water Transmission Project after Flow Switching

For the complex and changing water transfer conditions along the nullah water transfer project, it is of great significance to analyze the hydraulic response characteristics of the channel pool to ensure the safe and efficient operation of the project. In this paper, using the adjustable reservoir capacity of the channel pool, combined with the earliest and latest regulation time, a method is proposed to determine the optimal regulation time of water conservancy engineering structures through the hydraulic response characteristics. In order to validate the method, the hydraulic response characteristics of the channel pool during the whole regulation period were investigated using an actual river diversion project as an example. By using the Sobol global sensitivity analysis method, the sensitivity analysis of three variables (water transfer flow, upstream initial flow, and downstream water level) was conducted, and the results showed that the change of water transfer flow was the most-critical factor affecting the optimal regulation time. In order to quantitatively study the correlation between the water transfer flow and the optimal regulation time, the water transfer flow factor was coupled to the existing prediction model, and the results showed that the coupled model can efficiently predict the optimal regulation time, and the NSE coefficient can reach 0.98. In addition, the coupled model can be efficiently used to serve on-site dispatchers for accurately predicting the optimal regulation time and making the corresponding safety decisions.

Flow-Through Short-Crested Trapezoidal Weirs: Effect of Downstream Slope

Trapezoidal profiled weirs and barrages are employed extensively in agrarian countries like India and Pakistan for diverting river water for canal-fed irrigation. The downstream slope of a weir is designed as 1V∶3H, although in some older structures, slopes as mild as 1V∶5H are noticed. Downstream slopes of 1V∶5H also exist for the barrages on the Nile in Egypt and in the standard Crump weir used in the UK and some European countries. This study explores the effect of the downstream slope of a short-crested trapezoidal weir on its flow hydraulics and conveyance properties. Irrigation barrages and weirs, apart from diverting water to a canal, also help in measuring the discharge of a river, which is a function of the up- and downstream water levels. For large discharges during floods, the gates of a barrage are withdrawn to ensure an uncontrolled flow that may either be free or submerged, depending on the downstream water level. Although past studies on uncontrolled flows have recognized the effect of the upstream slope of a weir on the coefficient of discharge, Cd, this study establishes that it is also influenced by a weir’s downstream slope. An equation of Cd for free flows and a flow reduction factor for submerged flows are proposed considering both weir-face angles. For free flows, Cd is seen to increase with the steepness of a weir’s downstream slope; for submerged flows, the discharge reduction factor is observed to improve as the slope becomes milder, leading to a greater conveyance. Data from our own laboratory experiments, past publications, and results derived from a 2D RANS-VOF multiphase computational fluid dynamics model are used in arriving at the conclusions reported in the study.

Investigation of flow characteristics downstream vertical sluice gates of Bahr Yousef regulator physical model

ABSTRACT In the present time, the Ministry of Water Resources and Irrigation starts to construct new barrages across the Nile River and the main canals to replace the oldest ones, which are not able to withstand the requirements of increasing head difference between the upstream and downstream water levels upon the gates. This paper is focused on investigating experimentally the flow characteristics downstream the vertical sluice gates of Bahr Yousef regulator in case of flow over gate and flow under gate and the proper design for stilling basin with high efficiency in dissipation of water energy downstream the vertical gate with low cost. In the present study experimental work was carried out on a 2-D flume with 1.0 m wide, 26.0 m long, and 1.2 m deep, with discharges range from 22 to 395 l/s at the Hydraulics Research Institute laboratory. This experiment is physically based with scale 1:8.5. The experimental tests involved the observations and measurements of hydraulic phenomena in one single bay of the regulator in case of flow under/over gate. In these tests, there was a group of variables such as; the gate opening, flow rate, pressure head, upstream and downstream water levels, number of gates opening, and D50 of riprap protection. The influence of these parameters on downstream flow characteristics and the rip-rap size was investigated downstream the stilling basin. Comparative analysis between flow under the gate and flow over the gate was carried out. The results showed that the case of flow under gate gave more normal velocity distribution with low turbulent and high efficiency in dissipation of water energy downstream the vertical gates, and it was recommended for the operation of the regulator. Also, the obtained results showed that the size of riprap protection with D50 equal 0.2 m are stable, economic, and reduced the stilling basin length.

AUTOMATIC VALVE SLUICE GATE DESIGN MADE OF FIBERGLASS IN TIDAL AGRICULTURAL AREA

Water control technology aims to provide a sufficient water supply to avoid overflow. An automatic valve sluice gate made from fiberglass is preferred for water control in tidal agriculture. The mechanical valve sluice gate model can automatically release and close water discharge at a precise angle to optimize water control in tidal agriculture. The advantage of this sluice gate design is its utilization of the difference between upstream and downstream water levels on the sluice gate. A sluice gate design with a slope angle of 15° is recommended for tidal agriculture. The upstream water level should reach a height of 1.67 m for the sluice gate to open, while the downstream side should be at 0.82 m. The sluice gate will automatically open if the water level difference is 0.85 m in height and close if there is no water level difference. It is known that the flood level from the ground is 1 m to 2 m. It is suggested to elevate the land to prevent flooding for residents.