• Journal of Environmental Science International
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• v.18 no.3
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• pp.309-314
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• 2009

A accurate reservoir inflow is very important as providing information for decision making about the water balance and the flood control, as well as for dam safety. The methods to calculate the inflow were divided by the directed method to measure streamflow from upstream reservoirs and the indirected method to estimate using the correlation of reservoir water level and release. Currently, the inflow of multi-purpose dam is being calculated by the indirect method and the reservoir water level to calculate the storage capacity is being used by centimeters(cm) units. Corresponding to the storage volume of 1cm according to scale and water level of multi-purpose dam comes up to from several 10 thousand tons to several million tons. If it converts to inflow during 1 hour, and it comes to several hundred $m^3/sec$(CMS). Therefore, the inflow calculated on the hourly is largely deviated along the water level changes and is occurred minus value as the case. In this research, the water level gage has been developed so that it can measure a accurate water level for the improvement for the error and derivation of inflow, even though there might be various hydrology and meteorologic considerations to analyse the water balance of reservoir. Also, it is confirmed that the error and the standard derivation of data observed by the new gage is decreased by 89,6% and 1/3 & 87% and 2/3 compared to that observed by the existing gage of Daecheong and Juam multi-purpose dam.

• Journal of Korea Water Resources Association
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• v.45 no.5
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• pp.465-472
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• 2012

Recently, as the development of water front and natural type river is gradually increasing, it is mostly the case in that the flow analysis is implemented by only the flood level of the starting point without the tidal effect when the flood water level of the starting point is highly estimated than the high tidal water level in the design of river adjacent to an estuary. This research has analyzed the variation of tidal current for Oncheon river in Busan using Delft-3D program, considering that the tidal effect can cause the change of the flood water level of the starting point although the flood water level is higher than the flood tide level. As a result, considering the tidal effect at downstream boundary condition, water level indicates a periodicity of tide in particular region and the fluctuation range of water level is extended to upstream.

• Journal of Korean Society of Rural Planning
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• v.21 no.4
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• pp.177-186
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• 2015

The main objective of this study was to assess the applicability of IoT (Internet of Things)-based flood management under climate change by developing intelligent water level monitoring platform based on IoT. In this study, Arduino Uno was selected as the development board, which is an open-source electronic platform. Arduino Uno was designed to connect the ultrasonic sensor, temperature sensor, and data logger shield for implementing IoT. Arduino IDE (Integrated Development Environment) was selected as the Arduino software and used to develop the intelligent algorithm to measure and calibrate the real-time water level automatically. The intelligent water level monitoring platform consists of water level measurement, temperature calibration, data calibration, stage-discharge relationship, and data logger algorithms. Water level measurement and temperature calibration algorithm corrected the bias inherent in the ultrasonic sensor. Data calibration algorithm analyzed and corrected the outliers during the measurement process. The verification of the intelligent water level measurement algorithm was performed by comparing water levels using the tape and ultrasonic sensor, which was generated by measuring water levels at regular intervals up to the maximum level. The statistics of the slope of the regression line and $R^2$ were 1.00 and 0.99, respectively which were considered acceptable. The error was 0.0575 cm. The verification of data calibration algorithm was performed by analyzing water levels containing all error codes in a time series graph. The intelligent platform developed in this study may contribute to the public IoT service, which is applicable to intelligent flood management under climate change.

• The Journal of Engineering Geology
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• v.22 no.2
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• pp.207-221
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• 2012

A statistical analysis of time series of water level at 27 groundwater monitoring wells was conducted to analyze the surface water-groundwater connectivity in the wide alluvial plains surrounding the Nakdong River, Korea. Change in groundwater level is strongly related to river water level, yielding an average cross-correlation coefficient of 0.601, which is much higher than that between rainfall and groundwater level (0.125). Principal component analysis of groundwater level indicates that wells in the study area can be classified into two groups: wells in Group A are located close to a river, have water levels closely related to river level, and generally show a large increase in groundwater level during heavy rainfall. On the other hand, wells in Group B located far from a river are relatively less related to river level. Including hydrologic and statistical analyses, geochemical analysis and temperature monitoring are additionally required to reveal the relationship between surface water level and groundwater level, and to assess the possibility of groundwater flooding.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.2
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• pp.87-95
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• 2013

The aim of this study is to examine the behavior of reservoir fill dam with the water level raising by use of the centrifugal model test and the numerical simulation. In this study, LIQCA2D-SF based on the cyclic elasto-plastic constitutive model proposed by Oka et al. (1999) is applied for numerical simulation. In order to investigate the displacements and the pore water pressures in the fill dam due to the water level raising velocity, three model tests in centrifugal field of 50g for fill dams were conducted. A comparison between the test result and the simulation result has provided the influence on the displacement and the pore water pressure of the fill dam with increasing up of the water level.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.835-841
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• 2022

The water level of the dam reservoir is an important data in the operation of the dam. reservoir storage can be calculated by using water levels or prepared for disasters such as drought and floods. However, the water level is measured near the dam, making it difficult to represent a reservoir with a large area, and there is a high possibility that the water surface will be distorted due to discharge. Furthermore, the results of the survey showed that the water level of the reservoir is irregular rather than constant, and the water level of the reservoir is repeatedly falling and rising by section. In order to calculate such a complex and irregular representative water level, the water level observation density of the reservoir must be increased. In this study, we tried to derive the optimum water level observation density for Hwacheon Dam. A reasonable water level measurement density was derived by investigating the water level elevation of the reservoir and statistically analyzing it. The observation density may vary depending on the size of the reservoir, so the same analysis was conducted on the Goesan Dam and Boseonggang Dam. According to the results, four Hwacheon dams, three Goesan dams, and seven Boseong River dams are needed for observation density.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.6
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• pp.77-85
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• 2013

The efficient operation and management strategies of reservoirs in irrigation periods of drought events are an essential element for drought planning and countermeasure. Korea Rural Community Corporation has developed the real-time water level observation system of agricultural reservoirs to efficiently operate reservoirs, however, it is not possible to predict drought conditions, and only provides information of current situation. Hence, it is necessary to evaluate accurate irrigation vulnerability and efficiently reservoir operation rules using current water level. In this paper, the improvement methods of reservoir operation planning were developed with water supply vulnerability characteristic curves comparing to automatic water gauge at agricultural reservoirs. The 11 reservoirs were simulated applying the reservoir operation rules which was determined by irrigation vulnerability characteristic curves criteria and real time water level, and evaluated water supply situation in 2012 year. The analysis of results can be identified probabilistic possibility of water supply failures compared with the existing reservoir operation criteria. These results of efficient reservoir operation rules can be achieved enable irrigation planners to optimally manage available water resources for decision making, and contributed to maintain the water supply according to demand strategy for agricultural reservoirs management.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.118-123
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• 2015

There have been various studies on measurements of flood risk and forecasting models. For river and dam region, PDF and FVI has been proposed for measurement of flood risk and regression models have been applied for forecasting model. For Bo region unlikely river or dam region, flood risk would unexpectedly increase due to outgoing water to keep water amount under the designated risk level even the drain system could hardly manage the water amount. GFI and general linear model was proposed for flood risk measurement and forecasting model. In this paper, FVI with the consideration of duration on GFI was proposed for flood risk measurement at Bo region. General linear model was applied to the empirical data from Bo region of Nadong river to derive the forecasting model of FVI at three different values of Base High Level, 2m, 2.5m and 3m. The significant predictor variables on the target variable, FVI were as follows: ground water level based on sea level with negative effect, difference between ground altitude of ground water and river level with negative effect, and difference between ground water level and river level after Bo water being filled with positive sign for quantitative variables. And for qualitative variable, effective soil depth and ground soil type were significant for FVI.

• Journal of the Korean Geosynthetics Society
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• v.9 no.3
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• pp.87-93
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• 2010

The change of water level in reservoirs is an important factor causing failure of bank slopes, i.e. landslide. The water level of Three Gorges reservoir in China fluctuate between 145 m and 175 m, as a matter of flood control. During its normal operational state, the rate of water level fluctuation is supposed to range from 0.67 m/d to 3.0 m/d. Majiagou slope is located on the left bank of Zhaxi River, 2.1 km up from the outlet. Zhaxi River is a tributary of the Yangtze River within the Three Gorges area, of which the water level changes with the reservoir. At the back of Majiagou slope, a 20 m long and 3~10 cm wide fissure developed just after the reservoir water level rose from 95 m to 135 m in 2003. This big fissure was a full suggestion of potential failure of this slope. In this study, the pore water pressure files obtained from seepage analysis were used to evaluate the change in factor of safety (FS) with reservoir water level. Slope stability analyses then were carried out, with fully specified slip surface and limit equilibrium method. In the limit equilibrium analysis, the contribution of negative pore water pressure to shear strength was considered by the use of Fredlund's shear strength equation for unsaturated soils. On the base of the analyses, the change of FS with reservoir water level was interpreted in detail. It was found that FS against bank slopes decreases with the rise of the reservoir water level and increases with the drawdown of the reservoir water level. The most dangerous state was when the reservoir water level stays at the highest for a long time.

• Ecology and Resilient Infrastructure
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• v.7 no.4
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• pp.345-352
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• 2020

Securing the lead time for evacuation is crucial to minimize flood damage. In this study, downstream water levels for heavy rainfall were predicted using measured water level observation data. Multiple regression analysis and artificial neural networks were applied to the Seom River experimental watershed to predict the water level. Water level observation data for the Seom River experimental watershed from 2002 to 2010 were used to perform the multiple regression analysis and to train the artificial neural networks. The water level was predicted using the trained model. The simulation results for the coefficients of determination of the artificial neural network level prediction ranged from 0.991 to 0.999, while those of the multiple regression analysis ranged from 0.945 to 0.990. The water level prediction model developed using an artificial neural network was better than the multiple-regression analysis model. This technique for forecasting downstream water levels is expected to contribute toward flooding warning systems that secure the lead time for streams.