• Journal of Korea Water Resources Association
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• v.33 no.5
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• pp.635-645
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• 2000

In tidal rivers, the river level, discharge and tide are interrelated. Therefore, the stage-discharge relation that takes no account of tidal effects is inaccurate. For the calculation of river discharge in low water level, this paper attempts to formulate a multiple regression equation of stage-discharge curve to calculate the river discharge in low water level with variables as river level and differences between sea level and river level. Numerical application were perfonned on Ulsan gaging station in Taehwa river, and the comparison with existing rating curve equation showed good applicability of this multiple regression equation.uation.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.839-844
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• 2003

The effect of water level on the free vibration of a partially water-filled two rectangular plates structure was investigated by experimental modal analysis and finite element analysis using ANSYS computer program. Modal parameters of two rectangular plates coupled with water were obtained by means of experiment and the FEM solutions were compared with the experimental solutions to verify the finite element model. As a result, the comparison between the experiment and FEM results showed excellent agreement. The transverse vibration modes, in-phase and out-of-phase, were observed alternately in the fluid-coupled system. The effect of water level and water gap size on the fluid-coupled natural frequency were investigated. It was found that the natural frequency of the partially water-filled two rectangular plates are not proportional to the water level, but depend on mode number of plates.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.6
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• pp.1-9
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• 2020

Reservoir storage and water level information is essential for accurate drought monitoring and prediction. In particular, the agricultural drought has increased the risk of agricultural water shortages due to regional bias in reservoirs and water supply facilities, which are major water supply facilities for agricultural water. Therefore, it is important to evaluate the available water capacity of the reservoir, and it is necessary to determine the water surface area and water capacity. Remote sensing provides images of temporal water storage and level variations, and a combination of both measurement techniques can indicate a change in water volume. In areas of ungauged water volume, satellite remote sensing image acts as a powerful tool to measure changes in surface water level. The purpose of this study is to estimate of reservoir storage and level variations using satellite remote sensing image combined with hydrological statistical data and the Normalized Difference Water Index (NDWI). Water surface areas were estimated using the Sentinel-2 satellite images in Seosan, Chungcheongnam-do from 2016 to 2018. The remote sensing-based reservoir storage estimation algorithm from this study is general and transferable to applications for lakes and reservoirs. The data set can be used for improving the representation of water resources management for incorporating lakes into weather forecasting models and climate models, and hydrologic processes.

• International Journal of Contents
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• v.14 no.4
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• pp.57-64
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• 2018

Among many UNESCO world heritage sites in Korea, "Historic Village: Hahoe" is adjacent to Nakdong River and it is imperative to monitor the water level near the village in a bid to forecast floods and prevent disasters resulting from floods.. In this paper, we propose a recurrent neural network with multiple hidden layers to predict the water level near the village. For training purposes on the proposed model, we adopt the sixth-order error function to improve learning for rare events as well as to prevent overspecialization to abundant events. Multiple hidden layers with recurrent and crosstalk links are helpful in acquiring the time dynamics of the relationship between rainfalls and water levels. In addition, we chose hidden nodes with linear rectifier activation functions for training on multiple hidden layers. Through simulations, we verified that the proposed model precisely predicts the water level with high peaks during the rainy season and attains better performance than the conventional multi-layer perceptron.

• Journal of Korean Society of Water and Wastewater
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• v.26 no.4
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• pp.547-554
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• 2012

As a national river remediation project has been completed, this study has a special interest on the capabilities to predict water levels at various points of the Geum River. To be endowed with intelligent forecasting capabilities, the author formulate the neuro-genetic algorithm associated with the short-term water level prediction model. The results show that neuro-genetic algorithm has considerable potentials to be practically used for water level forecasting, revealing that (1) model optimization can be obtained easily and systematically, and (2) validity in predicting one- or two-day ahead water levels can be fully proved at various points.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.6
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• pp.51-58
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• 2011

The objective of this study is to identify whether or not the ground water level is decreasing. We suggest a method of estimating the change in groundwater level using newly developed groundwater pumping station data. The Goseong area located in Gyeongnam province was selected considering three factors. First, this area demands relatively large amount of irrigation water because most of the land is used as a paddy field and the proportion of the paddy field within total arable land is increasing. Second, groundwater level data in nearby area are available since these are monitored by Water Management Information System (WAMIS). Third, many groundwater pumping stations have been developed in this area in order to overcome droughts thus detail information for pumping stations are available. Regression results indicate groundwater level has been decreased for over 20 years. This decreasing trend is due to the shortage of surface irrigation water which was caused by the decrease in rainfall.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.601-604
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• 1996

It is well known that steam generator water level control at low power operation has many difficulties in a PWR (pressurized water reactor) nuclear power plant. The reverse process responses known as shrink and swell effects make it difficult to control the steam generator water level at low power. A new automatic control logic to remove the reverse process responses is proposed in this paper. It is implemented in PLC (programmable logic controller) and evaluated by using test equipment in Korea Atomic Energy Research Institute. The simulation test shows that the performance requirements is met at low power (below 15%). The water level control by new control logic is stabilized within 1% fluctuation from setpoint, while the water level by YGN 3 and 4 control logic is unstable with the periodic fluctuation of 25% magnitude at 5% power.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.491-494
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• 2003

An Automatic Water Level Measurement System has been developed in this study. It has the characteristics that it use lower power and solar power and it has the ability of sending data and remote-controlled by wireless MODEM this system was set up in the experimental site and was tested. Also, the management system for the water level data has been developed and will be used by instruments administrating reservoirs.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1235-1240
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• 2019

It is well known that the ground water level changes rapidly before and after the earthquake, and the variation of ground water level prediction is used to predict the earthquake. In this paper, we predict the ground water level in Miryang City using ANFIS algorithm for earthquake prediction. For this purpose, this paper used precipitation and temperature acquired from National Weather Service and data of underground water level from Rural Groundwater Observation Network of Korea Rural Community Corporation which is installed in Miryang city, Gyeongsangnam-do. We measure the prediction accuracy using RMSE and MAPE calculation methods. As a result of the prediction, the periodic pattern was predicted by natural factors, but the change value of ground water level was changed by other variables such as artificial factors that was not detected. To solve this problem, it is necessary to digitize the ground water level by numerically quantifying artificial variables, and to measure the precipitation and pressure according to the exact location of the observation ball measuring the ground water level.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.198-203
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• 2020

In this paper, we propose an artificial water level prediction system for small river flood prediction. River level prediction can be a measure to reduce flood damage. However, it is difficult to build a flood model in river because of the inherent nature of the river or rainfall that affects river flooding. In general, the downstream water level is affected by the water level at adjacent upstream. Therefore, in this study, we constructed an artificial intelligence model using Recurrent Neural Network(LSTM) that predicts the water level of downstream with the water level of two upstream points. The proposed artificial intelligence system designed a water level meter and built a server using Nodejs. The proposed neural network hardware system can predict the water level every 6 hours in the real river.