A Method of Multi-Stage Reservoir Water Level Forecasting Systems: A Case Study of Techi Hydropower in Taiwan

Reservoirs in Taiwan often provide hydroelectric power, irrigation water, municipal water, and flood control for the whole year. Taiwan has the climatic characteristics of concentrated rainy seasons, instantaneous heavy rains due to typhoons and rainy seasons. In addition, steep rivers in mountainous areas flow fast and furiously. Under such circumstances, reservoirs have to face sudden heavy rainfall and surges in water levels within a short period of time, which often causes the water level to continue to rise to the full level even though hydroelectric units are operating at full capacity, and as reservoirs can only drain the flood water, this results in the waste of hydropower resources. In recent years, the impact of climate change has caused extreme weather events to occur more frequently, increasing the need for flood control, and the reservoir operation has faced severe challenges in order to fulfil its multipurpose requirements. Therefore, in order to avoid the waste of hydropower resources and improve the effectiveness of the reservoir operation, this paper proposes a real-time 48-h ahead water level forecasting system, based on fuzzy neural networks with multi-stage architecture. The proposed multi-stage architecture provides reservoir inflow estimation, 48-h ahead reservoir inflow forecasting, and 48-h ahead water level forecasting. The proposed method has been implemented at the Techi hydropower plant in Taiwan. Experimental results show that the proposed method can effectively increase energy efficiency and allow the reservoir water resources to be fully utilized. In addition, the proposed method can improve the effectiveness of the hydropower plant, especially when rain is heavy.

Download Full-text

Research and Application of Key Technologies for Dynamic Control of Reservoir Water Level in Flood Season

Water ◽

10.3390/w13243576 ◽

2021 ◽

Vol 13 (24) ◽

pp. 3576

Author(s):

Jun Zhang ◽

Yaowu Min ◽

Baofei Feng ◽

Weixin Duan

Keyword(s):

Water Supply ◽

Water Level ◽

Real Time ◽

Flood Control ◽

Dynamic Control ◽

Water Levels ◽

Reservoir Water ◽

Reservoir Water Level ◽

Danjiangkou Reservoir ◽

Flood Season

In today’s reservoir operation study, it is urgent to solve the issues on improving flood resource utilization, maximizing reservoir impoundment, and guaranteeing water supply through real-time regulation optimization under the premise of ensuring flood control safety and taking risks properly. Based on previous studies, the key real-time operation technologies for dynamic control of reservoir water levels in flood season are summarized. The Danjiangkou Reservoir was taken as an example, the division of flood stages, reservoir water level requirements for improving water supply guarantee, dynamic control indexes of reservoir water level for beneficial use in stages during the flood season, and flood control dispatching indexes are proposed. Moreover, a practicable real-time flood forecast operation scheme for Danjiangkou Reservoir was compiled. Its application in 2017 indicated that the established scheme can provide strong technical support to ensure the overall benefits of Danjiangkou Reservoir, including flood control, water supply, and power generation.

Download Full-text

STUDY ON THE PERFORMANCE OF WONOGIRI RESERVOIR AS FLOOD CONTROL STRUCTURE

Journal of the Civil Engineering Forum ◽

10.22146/jcef.24007 ◽

2015 ◽

Vol 1 (3) ◽

pp. 85

Author(s):

Alexander Armin Nugroho

Keyword(s):

Water Level ◽

Flood Control ◽

Control Function ◽

Flood Routing ◽

Control Limit ◽

Reservoir Water ◽

Reservoir Water Level ◽

Catchment Areas ◽

Flood Hydrograph ◽

Reservoir Inflow

The Wonogiri reservoir was built with a primary function as flood control, especially in areas prone to flooding along the Bengawan Solo River. To find out the performance of the Wonogiri reservoir in flood control of Bengawan Solo, a study was conducted on flood hydrograph characteristics of the reservoir inflow by considering the contribution inflow from all sub-watersheds in the reservoir catchment area, at the end of December 2007. Calculation analysis flood hydrograph of Wonogiri Reservoir inflow is done with the calibration of Wuryantoro and Keduang sub-watersheds. Results of the calibration were then used reference to simulate flood hydrograph inflow in each sub-watershed catchment areas. Flood routing in the reservoir was done with the assumption that the inflow of the reservoir was left to face up a height of water in the reservoir 135.3 m (the lower flood control limit) and 138.3 m (the upper flood control limit) and then the spillway gates full-opening. Results of this research indicated that the maximum discharge inflow into the reservoir on the event of Wonogiri flood at the end of December 2007 was ranged from 3,331 to 4,993 m3/s; and it was occurred on December 26, 2007 at between 04:00 - 06:00 am. The most dominant flood hydrograph contribution into the reservoir was derived from Keduang sub-watershed. The flood in the reservoir was simulated as that the spillway gates were closed until water level of reservoir reached the minimum height of 135.3 m and 138.3 m and only until then the spillway gates full-opening. The reservoir water level reached 135.47 m on December 26, 2007 at 6:00 am and outflow was generated when the gates opened to reach 550 m3/s and then increased up to 642 m3/s at 14:00 after then it gradually decreases. The water level simulation was unable to reach 138.3 m because up to December 27, 2007 at 23:00 the water level reservoir reaches only 136.44 m. The Wonogiri reservoir flood control function still can run well and able to reduce the peak flood of 85%.

Download Full-text

Improvement of Downstream Flow by Modifying SWAT Reservoir Operation Considering Irrigation Water and Environmental Flow from Agricultural Reservoirs in South Korea

Water ◽

10.3390/w13182543 ◽

2021 ◽

Vol 13 (18) ◽

pp. 2543

Author(s):

Jinuk Kim ◽

Jiwan Lee ◽

Jongyoon Park ◽

Sehoon Kim ◽

Seongjoon Kim

Keyword(s):

Water Supply ◽

Water Level ◽

Irrigation Water ◽

Reservoir Operation ◽

Rice Paddy ◽

Environmental Flow ◽

Water Levels ◽

Reservoir Water ◽

Reservoir Water Level ◽

Downstream Flow

This study aims to develop a reservoir operation rule adding downstream environmental flow release (EFR) to the exclusive use of irrigation water supply (IWS) from agricultural reservoirs through canals to rice paddy areas. A reservoir operation option was added in the Soil and Water Assessment Tool (SWAT) to handle both EFR and IWS. For a 366.5 km2 watershed including three agricultural reservoirs and a rice paddy irrigation area of 4744.7 ha, the SWAT was calibrated and validated using 21 years (1998–2018) of daily reservoir water levels and downstream flow data at Gongdo (GD) station. For reservoir water level and streamflow, the average root means square error (RMSE) ranged from 19.70 mm to 19.54 mm, and the coefficient of determination (R2) and Nash–Sutcliffe efficiency (NSE) had no effect on the improved SWAT. By applying the new reservoir option, the EFR amount for a day was controlled by keeping the reservoir water level up in order to ensure that the IWS was definitely satisfied in any case. The downstream mean wet streamflow (Q95) decreased to 5.70 m3/sec from 5.71 m3/sec and the mean minimum flow (Q355) increased to 1.05 m3/sec from 0.94 m3/sec. Through the development of a SWAT reservoir operation module that satisfies multiple water supply needs such as IWR and EFR, it is possible to manage agricultural water in the irrigation period and control the environmental flow in non-irrigation periods. This study provides useful information to evaluate and understand the future impacts of various changes in climate and environmental flows at other sites.

Download Full-text

Application of Neural Network Models and ANFIS for Water Level Forecasting of the Salve Faccha Dam in the Andean Zone in Northern Ecuador

Water ◽

10.3390/w13152011 ◽

2021 ◽

Vol 13 (15) ◽

pp. 2011

Author(s):

Pablo Páliz Larrea ◽

Xavier Zapata Ríos ◽

Lenin Campozano Parra

Keyword(s):

Neural Network ◽

Water Level ◽

Clustering Algorithm ◽

Network Models ◽

Water Levels ◽

Subtractive Clustering ◽

Neural Network Models ◽

Reservoir Water ◽

Reservoir Water Level ◽

Maximum Delay

Despite the importance of dams for water distribution of various uses, adequate forecasting on a day-to-day scale is still in great need of intensive study worldwide. Machine learning models have had a wide application in water resource studies and have shown satisfactory results, including the time series forecasting of water levels and dam flows. In this study, neural network models (NN) and adaptive neuro-fuzzy inference systems (ANFIS) models were generated to forecast the water level of the Salve Faccha reservoir, which supplies water to Quito, the Capital of Ecuador. For NN, a non-linear input–output net with a maximum delay of 13 days was used with variation in the number of nodes and hidden layers. For ANFIS, after up to four days of delay, the subtractive clustering algorithm was used with a hyperparameter variation from 0.5 to 0.8. The results indicate that precipitation was not influencing input in the prediction of the reservoir water level. The best neural network and ANFIS models showed high performance, with a r > 0.95, a Nash index > 0.95, and a RMSE < 0.1. The best the neural network model was t + 4, and the best ANFIS model was model t + 6.

Download Full-text

Optimal Operation of Floodwater Resources Utilization of Lakes in South-to-North Water Transfer Eastern Route Project

Sustainability ◽

10.3390/su13094857 ◽

2021 ◽

Vol 13 (9) ◽

pp. 4857

Author(s):

Zitong Yang ◽

Xianfeng Huang ◽

Jiao Liu ◽

Guohua Fang

Keyword(s):

Water Level ◽

Resource Utilization ◽

Flood Control ◽

Optimal Operation ◽

Water Transfer ◽

Water Levels ◽

Reservoir Storage ◽

Flood Season ◽

Hongze Lake ◽

North Water

In order to meet the demand of emergency water supply in the northern region without affecting normal water transfer, considering the use of the existing South-to-North Water Transfer eastern route project to explore the potential of floodwater resource utilization in the flood season of Hongze Lake and Luoma Lake in Jiangsu Province, this paper carried out relevant optimal operating research. First, the hydraulic linkages between the lakes were generalized, then the water resources allocation mode and the scale of existing projects were clarified. After that, the actual available amount of flood resources in the lakes was evaluated. The average annual available floodwater resources in 2003–2017 was 1.49 billion m3, and the maximum available capacity was 30.84 billion m3. Then, using the floodwater resource utilization method of multi period flood limited water levels, the research period was divided into the main flood season (15 July to 15 August) and the later flood season (16 August to 10 September, 11 September to 30 September) by the Systematic Clustering Analysis method. After the flood control calculation, the limited water level of Hongze Lake in the later flood season can be raised from 12.5 m to 13.0 m, and the capacity of reservoir storage can increase to 696 million m3. The limited water level of Luoma Lake can be raised from 22.5 m to 23.0 m (16 August to 10 September), 23.5 m (11 September to 30 September), and the capacity of reservoir storage can increase from 150 to 300 million m3. Finally, establishing the floodwater resource optimization model of the lake group with the goals of maximizing the floodwater transfer amount and minimizing the flood control risk rate, the optimal water allocation scheme is obtained through the optimization algorithm.

Download Full-text

Hydraulic Optimization of Double Chamber Surge Tank Using NSGA-II

Water ◽

10.3390/w12020455 ◽

2020 ◽

Vol 12 (2) ◽

pp. 455 ◽

Cited By ~ 1

Author(s):

Resham Dhakal ◽

Jianxu Zhou ◽

Sunit Palikhe ◽

Khem Prasad Bhattarai

Keyword(s):

Water Level ◽

Optimization Method ◽

Water Levels ◽

Transient Processes ◽

Objective Functions ◽

Surge Tank ◽

Nsga Ii ◽

Reservoir Water ◽

High Head ◽

Double Chamber

A surge tank effectively reduces water hammer but experiences water level oscillations during transient processes. A double chamber surge tank is used in high head plants with appreciable variations in reservoir water levels to limit the maximum amplitudes of oscillation by increasing the volume of the surge tank near the extremes of oscillation. Thus, the volume of the chambers and the design of an orifice are the most important factors for controlling the water level oscillations in a double chamber surge tank. Further, maximum/minimum water level in the surge tank and damping of surge waves have conflicting behaviors. Hence, a robust optimization method is required to find the optimum volume of chambers and the diameter of the orifice of the double chamber surge tank. In this paper, the maximum upsurge, the maximum downsurge, and the damping of surge waves are considered as the objective functions for optimization. The worst condition of upsurge and downsurge is determined through 1-D numerical simulation of the hydropower system by using method of characteristics (MOC). Moreover, the sensitivity of dimensions of a double chamber surge tank is studied to find their impact on objective functions; finally, the optimum dimensions of the double chamber surge tank are found using non-dominated sorting genetic algorithm II (NSGA-II) to control the water level oscillations in the surge tank under transient processes. The volume of the optimized double chamber surge tank is only 44.53% of the total volume of the simple surge tank, and it serves as an effective limiter of maximum amplitudes of oscillations. This study substantiates how an optimized double chamber surge tank can be used in high head plants with appreciable variations in reservoir water levels.

Download Full-text

Real-Time Reservoir Operation by Tree-Based Model Predictive Control Including Forecast Uncertainty

10.5194/egusphere-egu2020-896 ◽

2020 ◽

Author(s):

Gokcen Uysal ◽

Rodolfo-Alvarado Montero ◽

Dirk Schwanenberg ◽

Aynur Sensoy

Keyword(s):

Water Supply ◽

Real Time ◽

Predictive Control ◽

Reservoir Operation ◽

Lead Time ◽

Flood Control ◽

Closed Loop ◽

Multi Stage ◽

Streamflow Forecasts ◽

Related Technique

<p>Streamflow forecasts include uncertainties related with initial conditions, model forcings, hydrological model structure and parameters. Ensemble streamflow forecasts can capture forecast uncertainties by having spread forecast members. Integration of these forecast members into real-time operational decision models which deals with different objectives such as flood control, water supply or energy production are still rare. This study aims to use ensemble streamflows as input of the recurrent reservoir operation problem which can incorporate (i) forecast uncertainty, (ii) forecasts with a higher lead-time and (iii) a higher stability. A related technique for decision making is multi-stage stochastic optimization using scenario trees, referred to as Tree-based Model Predictive Control (TB-MPC). This approach reduces the number of ensemble members by its tree generation algorithms using all trajectories and then proper problem formulation is set by Multi-Stage Stochastic Programming. The method is relatively new in reservoir operation, especially closed-loop hindcasting experiments and its assessment is quite rare in the literature. The aim of this study is to set a TB-MPC based real-time reservoir operation with hindcasting experiments. To that end, first hourly deterministic streamflows having one single member are produced using an observed flood hydrograph. Deterministic forecasts are tested with conventional deterministic optimization setup. Secondly, hourly ensemble streamflow forecasts having a lead-time up to 48 hours are produced by a novel approach which explicitly presents dynamic uncertainty evolution. Produced ensemble members are directly provided to input to related technique. Uncertainty becomes much larger when managing small basins and small rivers. Thus, the methodology is applied to the Yuvacik dam reservoir, fed by a catchment area of 258 km<sup>2</sup> and located in Turkey, owing to its challenging flood control and water supply operation due to downstream flow constraints. According to the results, stochastic optimization outperforms conventional counterpart by considering uncertainty in terms of flood metrics without discarding water supply purposes. The closed-loop hindcasting experiment scenarios demonstrate the robustness of the system developed against biased information. In conclusion, ensemble streamflows produced from single member can be employed to TB-MPC for better real-time management of a reservoir control system.</p>

Download Full-text

Multiyear rainfall variability in the Mono river basin and its impacts on Nangbeto hydropower scheme

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-384-343-2021 ◽

2021 ◽

Vol 384 ◽

pp. 343-347

Author(s):

Salomon Obahoundje ◽

Ernest Amoussou ◽

Marc Youan Ta ◽

Lazare Kouakou Kouassi ◽

Arona Diedhiou

Keyword(s):

Water Level ◽

Water Availability ◽

Rainfall Variability ◽

Energy Generation ◽

Hydropower Plant ◽

Hydropower Generation ◽

Reservoir Water ◽

Reservoir Water Level ◽

Hydropower Plants ◽

Change Context

Abstract. Hydropower energy, the main renewable energy source in West Africa, contributes to more than half of the Togo and Benin National electrification. This resource highly depends on water availability in rivers or reservoirs. The water availability heavily relies on climate patterns of the area. In the climate change context, the sustainability of hydropower plants is at risk. This work aims to assess the sensitivity of the Nangbeto hydropower plant to multiyear climate variability using statistical analysis. The results show that energy generation at Nangbeto hydropower is more modulated by four main variables namely inflow to reservoir, water level, rainfall of the actual and the previous year. The energy generation is found to be strongly and significantly correlated to inflow to reservoir, water level, and rainfall. Overall, the Nangbeto hydropower generation is more sensitive to inflow which is controlled by climate variables (rainfall, temperature) and land use/cover change. Therefore, the probable future change in these variables is suggested to be deeply investigated.

Download Full-text

ICESat-2 Reservoir Applications: A case study from the largest man-made reservoir in India

10.31223/x5dk9d ◽

2021 ◽

Author(s):

Surajit Ghosh ◽

Atul Kaushik

Keyword(s):

Water Level ◽

Water Levels ◽

Water Bodies ◽

Reservoir Water ◽

Reservoir Water Level ◽

Reservoir Storage ◽

Inland Water ◽

Change Impact ◽

And Performance ◽

Inland Water Bodies

Monitoring inland water levels is crucial for understanding hydrological processes to climate change impact leading to policy implementation. Satellite altimetry has proved to be an excellent technique to precisely measure water levels of rivers, lakes, and other inland water bodies. The ATL13 product of ICESat-2 space-borne LiDAR is solely dedicated to inland water bodies. The water surface heights were derived from ICESat-2's strong beams, and performance was assessed with respect to reservoir gauge observations. Statistical measurements were used to understand the agreement (R2= 0.99, %RMSE=0.08) among the datasets. An R2 value of 0.99 was observed between ICESat-2 derived water level anomaly and the reservoir storage anomaly. This study provides a unique opportunity to utilize the ATL13 data product to study reservoir water level variation and estimate the reservoir's storage. The methodology can also be helpful to understand the reservoir storage variation in a data-sparse region.

Download Full-text

Keakuratan Prediksi Inflow Waduk Dengan Neraca Air Waduk

Teknik ◽

10.14710/teknik.v37i2.12613 ◽

2016 ◽

Vol 37 (2) ◽

pp. 94

Author(s):

Dyah Ari Wulandari ◽

Hary Budieny ◽

Dwi Kurniani

Keyword(s):

Water Balance ◽

Reservoir Operation ◽

Human Error ◽

Series Data ◽

Data Series ◽

Reservoir Water ◽

Balance Accuracy ◽

Error Factor ◽

Reservoir Inflow ◽

Inflow Prediction

Dalam perhitungan inflow waduk sering digunakan persamaan neraca air waduk yang menggunakan data seri laporan harian operasi waduk, evaporasi dan curah hujan diwaduk, dan lengkung H-V-A waduk. Pada pengamatan data series laporan harian operasi waduk dan pengukuran kapasitas tampungan waduk, dapat terjadi kesalahan yang disebabkan karena kesalahan faktor manusia maupun faktor alat, hal ini akan menyebabkan kesalahan pula pada besarnya inflow waduk yang dihasilkan. Lebih lanjut di dalam perencanaan, data series inflow waduk ini diperlukan sebagai input pada pemodelan optimasi operasi waduk dan sedimentasi waduk, sehingga keakuratan datanya sangat diperlukan. Tujuan penelitian ini adalah untuk mengevaluasi tingkat akurasi penggunaan neraca air waduk dalam memprediksi inflow waduk. Untuk mengetahui tingkat akurasi dilakukan dengan membandingkan antara inflow waduk dari anak sungai hasil pengukuran dan hasil hitungan dengan persamaan neraca air waduk. Kemudian dilakukan variasi periode pengukuran dan kurva H- V-A yang digunakan. Berdasarkan penelitian yang dilakukan maka pada periode perhitungan yang lebih lama menghasilkan tingkat error yang lebih kecil. Pemakaian kurva waduk yang berbeda menghasilkan inflow yang berbeda. Tingkat error yang didapat masih cukup besar, diatas 30 %, sehingga perhitungan inflow waduk dari anak sungai dengan menggunakan metode neraca air waduk kurang akurat. [Title: Accuracy of Reservoir Inflow Prediction Using Reservoir Water Balance] In the calculation of reservoir inflow often used reservoir water balance equation using the data series of daily reports reservoir operation, evaporation and precipitation, and H-V-A curve. In observation of the data series of daily reports of reservoir operation and measurement of reservoir storage capacity, the errors may occur due to human error factor and factor appliance. This will cause an error on the reservoir inflow generated. Further, in the planning, this series data of reservoir inflow is required as input to the modeling of reservoir operation optimization and reservoir sedimentation, so the accuracy of the data are required. The purpose of this study was to evaluate the use of the reservoir water balance accuracy rate in predicting inflow. To determine the level of accuracy, the effort is done by comparing the inflow tributary reservoirs of measurement and the count with the reservoir water balance. Then perform variations of the measurement period and curves H-V-A is used. Based on the research conducted in the period longer calculation produces a smaller error. The different H-V-A curve results in the different inflow. Error rate obtained is still quite large, above 30%, so the calculation of tributary inflow reservoirs using reservoir water balance method is less accurate.

Download Full-text