• Economic and Environmental Geology
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• v.29 no.1
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• pp.21-24
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• 1996

Inductively coupled plasma atomic emission spectrophotometer (ICP/AES) is a versatile modern instruments for the multi-element analysis, but quantitative analysis using ICP/AES with normal pneumatic nebulizer is not applicable for the measurement of elemental concentrations in water down to the drinkining water standard level except a few elements because of poor detection limits. However, the detection limit can be lowered enough to measure drinking water standard, if ultrasonic nebulizer and/or hydride vapor generator is attached. This method is tested with groundwater samples from Tajeon area. It is confirmed that the elemental concentrations in these samples are within the limit of drinking water standard for the most elements. However, uranium concentration is very high in some samples compared with the concentrations suggested by Environmental Protection Agency of U.S.A. There is no standard concentration level to this element in Korea and it should be prepared immediately.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.188-191
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• 2008

The Tonle Sap, Cambodia, is a huge lake and periodically flooded due to monsoon climate. The incoming water causes intensive flooding that expands the lake over vast floodplain and wetland consisting mainly of forests and shrubs. Monitoring the water-level change over the floodplain is essential for flood prediction and water resource management. A main objective of this study is flood monitoring over Tonle Sap area using ALOS PALSAR. To study double-bounce effects in the lake, backscattering effect using ALOS PALSAR dual-polarization (HH, HV) data was examined. InSAR technique was applied for detection of water-level change. HH-polarization interferometric pairs between wet and dry seasons were best to measure water level change around northwestern parts of Tonle Sap. The seasonal pattern of water-level variations in Tonle Sap studied by InSAR method is similar to the past and altimeter data. However, water level variation measured by SAR was much smaller than that by altimeter because the DInSAR measurement only represents water level change at a given region of floodplain while altimeter provides water level variation at the central parts of the lake.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.1
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• pp.15-26
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• 2023

This study aimed to evaluate the performance of water level classification from CCTV images in agricultural facilities such as reservoirs. Recently, the CCTV system, widely used for facility monitor or disaster detection, can automatically detect and identify people and objects from the images by developing new technologies such as a deep learning system. Accordingly, we applied the ResNet-50 deep learning system based on Convolutional Neural Network and analyzed the water level of the agricultural reservoir from CCTV images obtained from TOMS (Total Operation Management System) of the Korea Rural Community Corporation. As a result, the accuracy of water level detection was improved by excluding night and rainfall CCTV images and applying measures. For example, the error rate significantly decreased from 24.39 % to 1.43 % in the Bakseok reservoir. We believe that the utilization of CCTVs should be further improved when calculating the amount of water supply and establishing a supply plan according to the integrated water management policy.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.191-197
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• 2006

This paper deals with a fault detection system design for nuclear steam generator water level control system. We expressed the nonlinear properties of the steam generator level system as a T-S fuzzy system with time varying uncertain parameters. We design a residual generator using a left coprime factorization of the T-S fuzzy model and a fault detection filter in order to improve the fault detection performance. We demonstrate the efficiency of the suggested design method via many computer simulations.

• Corrosion Science and Technology
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• v.10 no.4
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• pp.151-155
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• 2011

The iron oxide particles could be resulted from the corrosion of the circulating water system of a power plant. Because it may be one of the trouble materials which affect the power generation efficiency due to the deposition on steam generator tube and turbine blade, the continuous observation of its concentration is very important. The laser induced break-down detection (LIBD) technology was applied to monitor continuously the concentration of corrosion products with the detection limit of ppb level. The measurement system consists of a Nd:YAG pulsed laser, a polarizing beam splitter, a flow-type sample cell, an acoustic emission sensor, a high speed data acquisition board, a personal computer, etc.. The performance test results confirmed that this technology can be effective to monitor the corrosion product concentration of the circulating water system of a power plant.

• Proceedings of the KSRS Conference
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• v.1
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• pp.126-129
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• 2006

The marine environment is under considerable threat from intentional or accidental oil spills, ballast water discharged, dredging and infilling for coastal development, and uncontrolled sewage and industrial wastewater discharges. Monitoring spills and illegal oil discharges is an important component in ensuring compliance with marine protection legislation and general protection of the coastal environments. For the monitoring task an image processing system is needed that can efficiently perform the detection and the tracking of oil spills and in this direction a significant amount of research work has taken place mainly with the use of radar (SAR) remote sensing data. In this paper the level set image segmentation technique was tested for the detection of oil spills. Level set allow the evolving curve to change topology (break and merge) and therefore boundaries of particularly intricate shapes can be extracted. Experimental results demonstrated that the level set segmentation can be used for the efficient detection and monitoring of oil spills, since the method coped with abrupt shape’s deformations and splits.

• International journal of advanced smart convergence
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• v.9 no.1
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• pp.63-69
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• 2020

The rapid development in modern industrialization pollutant the water and atmospheric air across the globe that have a major impact on the human and livings health. In worldwide, every country government increasing the importance to improve the outdoor air pollution monitoring and control to provide quality of life and prevent the citizens and livings life from hazard disease. We proposed the environmental dust level detection method for outdoor facilities using sensor fusion technology to measure precise micro-dust level and monitor in realtime. In this proposed approach use the camera sensor and commercial dust level sensor data to predict the micro-dust level with data fusion method. The camera sensor based dust level detection uses the optical flow based machine learning method to detect the dust level and then fused with commercial dust level sensor data to predict the precise micro-dust level of the outdoor facilities and send the dust level informations to the outdoor air pollution monitoring system. The proposed method implemented on raspberry pi based open-source hardware with Internet-of-Things (IoT) framework and evaluated the performance of the system in realtime. The experimental results confirm that the proposed micro-dust level detection is precise and reliable in sensing the air dust and pollution, which helps to indicate the change in the air pollution more precisely than the commercial sensor based method in some extent.

• Journal of Korean Society on Water Environment
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• v.18 no.3
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• pp.283-290
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• 2002

In this study, home-made detection system by means of noble FIA is introduced on the measurement of toxic nitrite in the water samples collected from the area of Kwangju. As the standard calibration between 30 to 1000 ppb, the linearity has been shown more than 0.9999 as the correlation coefficient($R^2$) with the detection limit 1.5 ppb(S/N>2). The distribution of sample concentration was monitored as N.D. - 123 ppb which is wide span of concentrations in field water samples. The low level of nitrite is hardly detectable with other expensive sophisticated instruments including ion chromatography. Whereas the result of high concentration brings forth the necessity monitoring constantly our precious water resources. Successfully, the FIA system has played a very important role detecting wide span of nitrite in water sample. This technique can be adopted for controlling our environment in the near future.

• Journal of Korean Society on Water Environment
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• v.26 no.6
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• pp.954-962
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• 2010

The objective of this study was to develop automatic event detection algorithm for groundwater level rise. The groundwater level data and rainfall data in July and August at 37 locations nationwide were analyzed to develop the algorithm for groundwater level rise due to rainfall. In addition, the algorithm for groundwater level rise by ice melting and ground freezing was developed through the analysis of groundwater level data in January. The algorithm for groundwater level rise by rainfall was composed of three parts, including correlation between previous rainfall and groundwater level, simple linear regression analysis between previous rainfall and groundwater level, and diagnosis of groundwater level rise due to new rainfall. About 49% of the analyzed data was successfully simulated for groundwater level rise by rainfall. The algorithm for groundwater level rise due to ice melting and ground freezing included graphic analysis for groundwater level versus time (day), simple linear regression analysis for groundwater level versus time, and diagnosis of groundwater level rise by new ice melting and ground freezing. Around 37% of the analyzed data was successfully simulated for groundwater level rise due to ice melting and ground freezing. The algorithms from this study would help develop strategies for sustainable development and conservation of groundwater resources.

• The Korean Journal of Pesticide Science
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• v.12 no.4
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• pp.315-322
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• 2008

In this study, a simple, effective, and sensitive method has been developed for the quantitative residue analysis of cyhalofop-butyl and its metabolite cyhalofop acid in water and soil when kept under laboratory conditions. The content of cyholofop-butyl and cyhalofop acid in water and soil was analyzed by first purifying the compounds through liquid-liquid extraction and partitioning followed by Silica gel (adsorption) chromatography. Upon the completion of the purification step the residual levels were monitored through high-performance liquid chromatography (HPLC) using a UV absorbance detector. The recoveries of cyhalofop-butyl from three replicates spiked at two different concentrations ranged from 82.5 to 100.0% and from 66.7 to 97.9% in water and soil, respectively. The limit of detection and minimum detection level of cyhalofop-butyl in water and soil was 0.02 ppm and 10 ng, respectively. The recoveries of cyhalofop acid ranged from 80.7 to 104.8% in water and from 76.9 to 98.1 % in soil. The limit of detection of cyhalofop acid was 0.005 ppm in water and 0.01 ppm in soil, while the minimum detection level was 2 ng both in water and soil. The half-live of cyhalofop-butyl was 4.14 and 6.6 days in water and soil, respectively. The method was successfully applied to evaluate cyhalofop-butyl residues in water and soil applied aj. 30% emulsion, oil in water (EW) product.