• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.834-840
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• 2021

The management and installation methods of pressure gauges in water supply pipeline are not efficiently regulated and their installations are different in each site. In this paper, various domestic and overseas documents are examined about the pressure gauge. In order to improve the efficiency of operation management such as pipeline network and pump operation, water pressure needs to be measured as accurate as possible, by which decision making for optimal pipe network can be achieved. To get the goal, the installation of pressure gauge should be reviewed about where and how to install. In this study, an optimal horizontal distance test is conducted, in which pressure value variation is monitored and analyzed according to up and down stream distances and valve flow control, and a optimal vertical position test is also analyzed by installing the pressure gauges vertically from the up(180°) to the bottom (0°) of the pipeline.

• Journal of Wetlands Research
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• v.22 no.2
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• pp.106-112
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• 2020

Wetlands play an important function and role in hydrological, environmental, and ecological, aspects of the watershed. Water level in wetlands is essential for various analysis such as for the determination of wetland function and its effects on the environment. Since several wetlands are ungauged, research on wetland water level prediction are uncommon. Therefore, this study developed a water level prediction model using multiple regression analysis, principal component regression analysis, artificial neural network, and DNN to predict wetland water level. Geumjeong-Mountain Wetland located in Yangsan-city, Gyeongsangnam-do province was selected as the target area, and the water level measurement data from April 2017 to July 2018 was used as the dependent variable. On the other hand, hydrological and meteorological data were used as independent variables in the study. As a result of evaluating the predictive power, the water level prediction model using DNN was selected as the final model as it showed an RMSE value of 6.359 and an NRMSE value of 18.91%. This research study is believed to be useful especially as a basic data for the development of wetland maintenance and management techniques using the water level of the existing unmeasured points.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 1995.12a
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• pp.9-21
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• 1995

A planning support system enhances our ability to use water capacity expansion as an urban growth management strategy. This paper reports the development of capacity expansion modeling of water supply as part of the continuing development of such a planning support system (PEGASUS: Planning Environment for Generation and Analysis of Spatial Urban Systems) to incorporate water supply, This system is designed from the understanding that land use and development drive the demand for infrastructure and infrastructure can have a significant influence on the ways in which land is developed and used. Capacity expansion Problems of water supply can be solved in two ways: 1) optimal control theory, and 2) mixed integer nonlinear programming (MINLP). Each method has its strengths and weaknesses. In this study the MINLP approach is used because of its strength of determining expansion sizing and timing simultaneously. A dynamic network optimization model and a water-distribution network analysis model can address the dynamic interdependence between water planning and land use planning. While the water-distribution network analysis model evaluates the performance of generated networks over time, the dynamic optimization model chooses alternatives to meet expanding water needs. In addition, the user and capacity expansion modeling-to-generate-alternatives (MGA) can generate alternatives. A cost benefit analysis module using a normalization technique helps in choosing the most economical among those alternatives. GIS provide a tool for estimating the volume of demanded water and showing results of the capacity expansion model.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1061-1069
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• 2021

Recently, the magnitude and frequency of extreme heavy rains and localized heavy rains have increased due to abnormal climate, which caused increased flood damage in river basin. As a result, the nonlinearity of the hydrological system of rivers or basins is increasing, and there is a limitation in that the lead time is insufficient to predict the water level using the existing physical-based hydrological model. This study predicted the water level at Ulsan (Taehwagyo) with a lead time of 0, 1, 2, 3, 6, 12 hours by applying deep learning techniques based on Deep Neural Network (DNN) and Long Short-Term Memory (LSTM) and evaluated the prediction accuracy. As a result, DNN model using the sliding window concept showed the highest accuracy with a correlation coefficient of 0.97 and RMSE of 0.82 m. If deep learning-based water level prediction using a DNN model is performed in the future, high prediction accuracy and sufficient lead time can be secured than water level prediction using existing physical-based hydrological models.

• Journal of Korea Water Resources Association
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• v.55 no.2
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• pp.121-133
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• 2022

The drought resulting from insufficient rainfall compared to the amount in an ordinary year can significantly impact a broad area at the same time. Another feature of this disaster is hard to recognize its onset and disappearance. Therefore, a reliable and fast way of predicting both the suffering area and the amount of water shortage from the upcoming drought is a key issue to develop a countermeasure of the disaster. However, the available drought scenarios are about 50 events that have been observed in the past. Due to the limited number of events, it is difficult to predict the water shortage in a case where the pattern of a natural disaster is different from the one in the past. To overcome the limitation, in this study, we applied the four RCP climate change scenarios to the water balance model and the annual amount of water shortage from 360 drought events was estimated. In the following chapter, the deep neural network model was trained with the SPEI values from the RCP scenarios and the amount of water shortage as the input and output, respectively. The trained model in each sub-basin enables us to easily and reliably predict the water shortage with the SPEI values in the past and the predicted meteorological conditions in the upcoming season. It can be helpful for decision-makers to respond to future droughts before their onset.

• Korean Journal of Agricultural Science
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• v.37 no.1
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• pp.105-112
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• 2010

The objective of this study is to develop a standardized model for analyzing water balances in large scaled water basin by considering agricultural water districts, and to evaluate the hydrological feasibility of applying this model to several water districts such as Nonbul, Geumbok, Daejeon 1, Daejeon 2, and Cheonggang in Geum river basin. Ten types of stream network were considered in developed model. Using this model, streamflows were simulated by major stations and water balances were analyzed by water districts. Simulated streamflows and measured streamflows were compared at check stations such as Gapcheon and Bugang stations in which Nash and Schcliffe's model efficiencies were 0.633, 0.902, respectively. This results showed its applicabilities to national water resources plan, rural water development plan, and total maximum daily load plan in Korea.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.117-122
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• 2006

Modernized GNSS such as new GPS signals updated GLONASS and coming Galileo promises higher quality and higher reliability for users. Powerful technologies such as Internet, ubiquitous network technology and sensor network has been used to promote a safe and more secure lifestyle. This report describes experimental trials to combine these technologies namely GPS and Sensor Network into a high-performance system. GPS is used to enlarge the communication range, resolving the service area limitations, as a wider service area is required at shore areas compared to urban area. GPS position datum is also used as primary network routing information to get practical Sensor Network. Another application is the under water Sensor Network. Accurate GPS position and time are used to establish stable and high reliability underwater acoustic Sensor Network. This paper describes the background of the project 'Harbor area Marine Ubiquitous Sensor Network', preliminary consideration and testing. Radio and acoustic communication is the main focus of this preliminary experiment.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.3
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• pp.119-124
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• 2012

As an energy network infrastructure, which is capable of integrating energy related services such as AMR/AMI, Smart Grid, and Smart Water Grid, the Smart Utility Network (SUN) enables a paradigm shift from user-oriented networks to device-oriented networks. The SUN has some similarities to sensor networks in application and network requirements. Therefore it is required to investigate and analyze thoroughly existing related work in advance to design new network protocols for SUN. In this paper we analyze service requirements and design considerations for SUN and then present a design guideline of new network protocols for SUN by investigating existing low power protocols, data aggregation methods, and in-network storages.

• Journal of Korea Water Resources Association
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• v.33 no.S1
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• pp.251-256
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• 2000

• Proceedings of the Korea Water Resources Association Conference
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• 1997.05a
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• pp.409-413
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• 1997