Analysis of Mukakuning and Duriangkang Reservoir’s Capacity to Fulfill The Raw Water Demand of Batam City

Batam City is the economic center of Riau Province with a predicted population of 1.8 million people in 2025. To support economic development, Batam City needs a reliable supply of raw water. Mukakuning and Duriangkang reservoirs, which are cascade reservoirs, are the largest contributors to raw water supply in Batam City. This study aims to determine the maximum capacity of the two reservoirs to meet current and future raw water demand. Discharge in the watershed is calculated using daily HEC-HMS model calibrated using Duriangkang Reservoir water level data. The storage of Mukakuning and Duriangkang Reservoir are 6.3 and 106.1 million m3 respectively, equivalent to 39% and 77% of the runoff volume of each watershed, classifying the two reservoirs in the multi-year category. Using current operation, the two reservoirs can supply up to 3.24 m3/s at 100% reliability, compared to existing capacity of 3.1 m3/s. The water loss is dominated by evaporation which reaches 32.6 million m3/year while spilled water is only 8.3 million m3/year. At 95% reliability, the reservoirs are almost at maximum capacity and able to supply 4.03 m3/s of raw water with the spilled water is only 0.4 million m3/year. Efforts to increase capacity by increasing normal water levels are not effective and lead to dam overtopping in PMF condition. More effective way to increase water supply can be obtained by changing operating patterns. If the reservoir is in dry condition, determined by predicted SPI, the water supply is limited so that the discharge can be utilized for a longer period.

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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.

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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.

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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.

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Transfer Entropy as a Tool for Hydrodynamic Model Validation

Entropy ◽

10.3390/e20010058 ◽

2018 ◽

Vol 20 (1) ◽

pp. 58 ◽

Cited By ~ 8

Author(s):

Alicia Sendrowski ◽

Kazi Sadid ◽

Ehab Meselhe ◽

Wayne Wagner ◽

David Mohrig ◽

...

Keyword(s):

Water Level ◽

Numerical Models ◽

Water Levels ◽

Transfer Entropy ◽

Spatial And Temporal Scales ◽

River Deltas ◽

Level Data ◽

Water Level Data ◽

Wax Lake Delta ◽

Validation Tool

The validation of numerical models is an important component of modeling to ensure reliability of model outputs under prescribed conditions. In river deltas, robust validation of models is paramount given that models are used to forecast land change and to track water, solid, and solute transport through the deltaic network. We propose using transfer entropy (TE) to validate model results. TE quantifies the information transferred between variables in terms of strength, timescale, and direction. Using water level data collected in the distributary channels and inter-channel islands of Wax Lake Delta, Louisiana, USA, along with modeled water level data generated for the same locations using Delft3D, we assess how well couplings between external drivers (river discharge, tides, wind) and modeled water levels reproduce the observed data couplings. We perform this operation through time using ten-day windows. Modeled and observed couplings compare well; their differences reflect the spatial parameterization of wind and roughness in the model, which prevents the model from capturing high frequency fluctuations of water level. The model captures couplings better in channels than on islands, suggesting that mechanisms of channel-island connectivity are not fully represented in the model. Overall, TE serves as an additional validation tool to quantify the couplings of the system of interest at multiple spatial and temporal scales.

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Anomaly Detection in Reservoir Water Level Data Using the LSTM Model Based on Deep Learning

Korean Society of Hazard Mitigation ◽

10.9798/kosham.2021.21.1.71 ◽

2021 ◽

Vol 21 (1) ◽

pp. 71-81

Author(s):

Mi-Hye Yang ◽

Won-Ho Nam ◽

Han-Joong Kim ◽

Taegon Kim ◽

An-Kook Shin ◽

...

Keyword(s):

Anomaly Detection ◽

Water Supply ◽

Water Level ◽

Detection Algorithm ◽

Agricultural Water ◽

Level Measurement ◽

Level Data ◽

Water Level Data ◽

Agricultural Water Supply ◽

Agricultural Reservoir

Weather and hydrological phenomena have been changing due to climate change as evidenced by localized torrential rainfall and precipitation falling by more than 30% compared to the annual average. From 2013 to 2017 the ninety-nine reservoirs reached a water storage rate of 0%, making a secure stable water supply for agriculture uncertain. There is an increased need for information regarding agricultural water management to respond to the changes in the agricultural environment and climate. Therefore, automatic water level measurement facilities have been introduced to determine the real-time reservoir storage capacity and agricultural water supply. According to the Ministry of Agriculture, Food and Rural Affairs' guidelines for the installation and operation of water level measurement instruments, automatic water level facilities are currently installed at 1,734 reservoirs and 1,880 irrigation canals, with water level data generated at 10-minute intervals. The official recognition of hydrological water level data for agricultural reservoirs increased from six in 2016 to forty-nine in 2019. Anomaly detection algorithm methods for data regarding the agricultural reservoir level as well as quality control measures based on agricultural reservoir characteristics are required to minimize data quality degradation and generate reliable hydrological data over time. Though it was practically impossible to analyze the correlation between the water level or run-off and influential factors such as weather and terrain, recently a non-linear hydrological analysis has been possible using models such as Artificial Neural Networks (ANNs). This study aims to present an anomaly detection algorithm for reservoir level data using deep learning based LSTM (Long Short-Term Memory) models, in combination with other neural networks for managing quantitative information of agricultural water supply.

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Multi-objective optimization of typhoon inundation forecast models for water-level gauging network by integration of ARMAX with a Genetic Algorithm

10.5194/nhess-2016-1 ◽

2016 ◽

Cited By ~ 1

Author(s):

Huei-Tau Ouyang

Keyword(s):

Genetic Algorithm ◽

Water Level ◽

Water Levels ◽

Time Shift ◽

Multi Objective ◽

Cumulative Rainfall ◽

Level Data ◽

Water Level Data ◽

Forecast Models ◽

Gauging Station

Abstract. The forecasting of inundation levels during typhoons requires that multiple objectives be taken into account, including the forecasting capacity with regard to variations in water level throughout the entire weather event, the accuracy that can be attained in forecasting peak water levels and the time at which peak water levels are likely to occur. This paper proposed a means of forecasting inundation levels in real-time using monitoring data from a water-level gauging network. ARMAX was used to construct water-level forecast models for each gauging station using input variables including cumulative rainfall and water level data from other gauging stations in the network. Analysis of the correlation between cumulative rainfall and water level data makes it possible to obtain an approximation as to the cumulative duration of rainfall and time lags associated with each gauging station. Analyses on water levels as well as on cumulative rainfall enable the identification of associate sites pertained to each gauging station that share high correlations with regard to water level and low mutual information with regard to cumulative rainfall. Water level data from associate sites is used as a second input variable for the water-level forecast model of the target site. Three indices were considered in the selection of an optimal model: the coefficient of efficiency (CE), error in the stage of peak water level (ESP), and relative time shift (RTS). We used a multi-objective genetic algorithm to derive an optimal Pareto set of models capable of performing well in the three objectives. A case study was conducted on the Xinnan area of Yilan County, Taiwan in which optimal water-level forecast models were established for each of the four water-level gauging stations in the area. Test results demonstrate that the model best able to satisfy PE exhibited significant time shift, whereas the models best able to satisfy CE and RTS provide accurate forecasts of inundations when variations in water level are less extreme.

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DEVELOPMENT OF RESERVOIR OPERATION FOR BATANG AI HYDROELECTRIC PROJECT

Journal of Civil Engineering Science and Technology ◽

10.33736/jcest.303.2016 ◽

2016 ◽

Vol 7 (2) ◽

pp. 45-49

Author(s):

Kiu Kwong Kiat ◽

Frederik Josep Putuhena

Keyword(s):

Power Generation ◽

Water Supply ◽

Power Supply ◽

Water Demand ◽

Reservoir Operation ◽

Maximum Capacity ◽

Hydroelectric Project ◽

Continuous Power

Batang Ai Hydroelectric Project is meant to generate electricity. The Batang Ai Dam has a maximum capacity to generate around 108MW when it is fully operational. Efficient reservoir operation should be carried out very carefully in order to provide reliable water supply for power generation and water demand. The research of this project is to review the Batang Ai Dam storage conservation for the reservoir operation by using storage conservation simulation. The simulations are carried out with various outflow conditions using the principle of the storage equation. Lastly, the results from the simulation show that with proper regulation of the reservoir outflow, the Batang Ai Hydroelectric Project reliability to provide continuous power supply without shortage in water supply is assured.

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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.

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A comparative assessment of selected raw water intake systems in Rwanda

Water Practice & Technology ◽

10.2166/wpt.2012.045 ◽

2012 ◽

Vol 7 (2) ◽

Author(s):

I. Nhapi ◽

A. J. Nshimiyimana ◽

U. G. Wali ◽

F. O. K. Anyemedu ◽

J. J. Kashaigili

Keyword(s):

Water Supply ◽

Water Intake ◽

Rural Areas ◽

Urban Areas ◽

Water Levels ◽

Bank Filtration ◽

Raw Water ◽

Groundwater Abstraction ◽

Water Turbidity ◽

Physical Measurements

After the genocide of 1994, Rwanda has been struggling to contain urban migration and its pressures on existing facilities. Water supply coverage is low at 76% in urban areas and 68% in rural areas. This implies that huge investments are required to meet the Millennium Development Goals on water supply and sanitation. This study was conducted to assess the existing problems of raw water intake systems at Yanze and Nyabarongo intakes in Kigali; Shyogwe intake in Ruhango District; and Kadahokwa intake in Huye District. The study was in response to high amounts of sediments in raw water which literally clogged the intake systems for a number of days, resulting in erratic water supplies to the residents in the rainy season. The study focused on performance problems of the intake systems, raw water turbidity variations and the assessment of how environmental concerns could be addressed in the design of intake systems in areas of high soil erosion activities. Data was collected through interviews and physical measurements. The study revealed that flooding, intake site selection, erosion, screen clogging, intake protection, high raw water turbidity, inadequacy of raw water supplied to the water treatment plants, and low downstream environmental flows were the main intake problems. The Yanze intake had worst problems with high levels of flooding, erosion, sedimentation, and high raw water turbidity levels. The bank filtration system at Nyabarongo gave the least problems of raw water turbidity. Yanze and Nyabugogo river intakes systems were found to be threatened by decreasing water levels attributed to surrounding upstream landuse activities. It was recommended that proper maintenance of existing structures, landuse management around river intakes, use of well-designed reservoir abstraction systems, increased groundwater abstraction systems (including bank filtration), would greatly improve the performance of intake systems in Rwanda.

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Deformation and stability analyses of a near-dam rocky slope and its potential landslide-generated wave threats

Quarterly Journal of Engineering Geology and Hydrogeology ◽

10.1144/qjegh2021-018 ◽

2021 ◽

pp. qjegh2021-018

Author(s):

Ming-liang Chen ◽

Xing-guo Yang ◽

Shun-chao Qi ◽

Hai-bo Li ◽

Jia-wen Zhou

Keyword(s):

Water Level ◽

Rock Slope ◽

Limit Equilibrium ◽

Water Levels ◽

Reservoir Rock ◽

Water Diversion ◽

Reservoir Water ◽

Reservoir Water Level ◽

The Impact

Occurrence of a reservoir landslide and its potential secondary hazards near a dam can result in significant losses and casualties, such as those that resulted from the Vajont landslide. In this study, a cataclinal rock slope in the Maoergai reservoir was taken as a case to study the characteristics of the gravitational deformation process and to analyze the potential threat. The stability of rock slope is analyzed by the limit equilibrium method, and the potential landslide movement and subsequent waves are also simulated. Results indicate that lithology, geological structure, reservoir water level changes and artificial activities all play an important role for the large deformation of rock slope deformation, which is characterized by a combination of bending-toppling and principally shear-slip. Pre-calculations of potential threats indicated that the impact of a landslide wave would be greater at dead water levels than at the normal water level and could result in blockage of the inlet to the water diversion structure on the opposite right bank. These findings provide implication for the control of reservoir rock slopes: (i) serious attention should be paid to the influence of water on rock strength in early and (ii) infiltration must be prevented during water level rise.Thematic collection: This article is part of the Role of water in destabilizing slopes collection available at: https://www.lyellcollection.org/cc/Role-of-water-in-destabilizing-slopes

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