• Proceedings of the Korean Society of Environment and Ecology Conference
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• 2003.10a
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• pp.105-126
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• 2003

In Korea most of annual rainfall is concentrated in several episodic heavy rains during the season of summer monsoon and typhoon. Because of uneven rainfall distribution many dams have been constructed in order to secure water supply in dry seasons. The Han River system has the most dams among Korean rivers, and the river is a series of dams now. Reservoirs need different strategy of water quality control from river water. Autochthonous organic matter and phosphorus should be the major target to be controlled in lakes. In this Paper some problems are discussed that makes efforts of water quality improvement ineffective in lakes of Korea, even after the substantial investment to wastewater treatment facilities.1) Phosphorus is the key factor controlling eutrophication of lakes and the reduction ofphosphors should be the major target of water treatment. However, water quality management strategy in Korea is still stream-oriented, and focused on BOD removal from sewage. Phosphorus removal efficiency remains as low as 10-30%, because biological treatment is adopted for both secondary treatment and advanced treatment. The standard for TP concentration of the sewage treatment plant effluent is 6 mgP/l in most of regions, and 2 mg/l in enforced region near metropolitan water intake point. TP in the effluents of sewage treatment plants are usually 1-2 mg/1, and most of plants meet the effluent regulation without a further phosphorus removal process. The generous TP standard for effluents discourages further efforts to improve phosphorus removal efficiency of sewage treatment. Considering that TP standard for the effluent is below 0.1 mg/l in some countries, it should be amended to below 0.1 mg/l in Korea, especially in the watershed of large lakes.2) Urban runoff and combined sewer overflow are not treated, even though their total loading into lakes can be comparable to municipal sewage discharges on dry days. Chemical coagulation and rapid settling might be the solution to urban runoff in regard of intermittent operation on only rainy days.3) Aggregated precipitation in Korea that is concentrated on several episodic heavyrains per year causes a large amount of nonpoint source pollution loading into lakes. It makes the treatment of nonpoint source discharge by methods of other countries of even rain pattern, such as retention pond or artificial wetland, impractical in Korea.4) The application rate of fertilizers in Korea is ten times as high as the average ofOECD countries. The total manure discharge from animal farming is thought to be over the capacity of soil treatment in Korea. Even though large portion of manure is composted for organic fertilizer, a lot of nutrients and organic matter emanates from organic compost. The reduction of application rate and discharge rate of phosphorus from agricultural fields should be encouraged by incentives and regulations.5) There is a lot of vegetable fields with high slopes in the upstream region of the HanRiver. Soil erosion is severe due to high slopes, and fertilizer is discharged in the form of adsorbed phosphorus on clay surface. The reduction of soil erosion in the upland area should be the major preventive policy for eutrophication. Uplands of high slope must be recovered to forest, and eroded gullies should be reformed into grass-buffered natural streams which are wider and resistant to bank erosion.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.7 no.4
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• pp.98-109
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• 2004

This study was conducted to develop revegetation methods for the restoration of the steep slopes by recycling of bark compost and mushroom media. In general, bark compost and mushroom media can be used as soil media for the restoration works, because they can increase infiltration of rainfall and give enough porous to breathe and elongate for the root growth as well as environmental value. This experiment was carried out to know the effect of soil media composed by different ratio of mushroom media for the restoration of steep rock-exposed slopes, and to certificate how soil media(PEC) will be effective to germinate and grow for native plants. The main results of the study are summarized as follows; 1. In percent coverage, the soil media PEC1 is more valuable than PEC2. The seed mixtures recommended by Government of Transportation and Construction can be used at PEC1 and PEC2, but it will be more useful if the total amount of seed are reduced and seed mixtures are altered in a direction of native plants. 2. The soil media is under 20 mm tested by Yamanaka Hardiness Tester which is available for the seed germination and growth. 3. The surface cracks are not occurred in PEC1 and PEC2, but more than 30 cracks per 1 square meter are occurred at soil media which is constructed by normal soil-seed-fertilizer hydro-seeding methods. 4. The soil moisture contents are over 20 percent level during 15 day. Such moisture content in soil media will be effective for the plant growth. By using Terra-Control, PEC can maintain enough soil moisture. 5. The eroded soils from $60^{\circ}$ slopes by artificial rainfall with the intensity of 20 mm/hr in one day after seeding are estimated under 1%. By the results of erosion test, it comes to the conclusion that soil media of PEC can be adapted at steep rock exposed slopes.

• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.97-105
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• 2020

Recently, Artificial Neural Network receives attention as a data prediction method. Among these, a Long Shot-term Memory (LSTM) model specialized for time-series data prediction was utilized as a prediction method of hydrological time series data. In this study, the LSTM model was constructed utilizing deep running open source library TensorFlow which provided by Google, to predict inflows of multipurpose dams. We predicted the inflow of the Yongdam Multipurpose Dam which is located in the upper stream of the Geumgang. The hourly flow data of Yongdam Dam from 2006 to 2018 provided by WAMIS was used as the analysis data. Predictive analysis was performed under various of variable condition in order to compare and analyze the prediction accuracy according to four learning parameters of the LSTM model. Root mean square error (RMSE), Mean absolute error (MAE) and Volume error (VE) were calculated and evaluated its accuracy through comparing the predicted and observed inflows. We found that all the models had lower accuracy at high inflow rate and hourly precipitation data (2006~2018) of Yongdam Dam utilized as additional input variables to solve this problem. When the data of rainfall and inflow were utilized together, it was found that the accuracy of the prediction for the high flow rate is improved.

• Journal of Korea Water Resources Association
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• v.51 no.11
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• pp.1021-1029
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• 2018

A primary objective of this study is to develop a drought forecasting technique based on groundwater which can be exploit for water supply under drought stress. For this purpose, we explored the lagged relationships between regionalized SGI (standardized groundwater level index) and SPI (standardized precipitation index) in view of the drought propagation. A regional prediction model was constructed using a NARX (nonlinear autoregressive exogenous) artificial neural network model which can effectively capture nonlinear relationships with the lagged independent variable. During the training phase, model performance in terms of correlation coefficient was found to be satisfactory with the correlation coefficient over 0.7. Moreover, the model performance was described by root mean squared error (RMSE). It can be concluded that the proposed approach is able to provide a reliable SGI forecasts along with rainfall forecasts provided by the Korea Meteorological Administration.

• Journal of the Korean Geosynthetics Society
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• v.12 no.1
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• pp.39-50
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• 2013

This study aims at investigating the behavior of the ground water level when installing upward soil nails that drain water as well. To do this, a series of down-scaled model tests were conducted. A model slope with weathered soils was prepared and then an artificial rain was scattered on the slope. The relative densities of soil specimen were 60%, 75%, and 90%, and the rainfall intensities 50mm/hr, 75mm/hr, 100mm/hr, and 125mm/hr, respectively. The experimental parameters, such as the ground water level, ratio of soil runoff, and failure mode of the slope were measured and analyzed. As the results, It may be concluded that the ground water level in the slope supported by drainable upward soil nails increases very gradually while the unsupported soil changes dramatically. In addition, the ground water level becomes constant and no failure occurs as time goes by. In case of the relative density of 75%, the runoff ratio seemed to increase up to about 8~15% after reinforcement.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.5
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• pp.671-683
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• 2018

The flood damage caused by heavy rains in urban watershed is increasing, and, as evidenced by many previous studies, urban flooding usually exceeds the water capacity of drainage networks. The flood on the area which considerably urbanized and densely populated cause serious social and economic damage. To solve this problem, deterministic and probabilistic studies have been conducted for the prediction flooding in urban areas. However, it is insufficient to obtain lead times and to derive the prediction results for the flood volume in a short period of time. In this study, IDNN, TDNN and NARX were compared for real-time flood prediction based on urban runoff analysis to present the optimal real-time urban flood prediction technique. As a result of the flood prediction with rainfall event of 2010 and 2011 in Gangnam area, the Nash efficiency coefficient of the input delay artificial neural network, the time delay neural network and nonlinear autoregressive network with exogenous inputs are 0.86, 0.92, 0.99 and 0.53, 0.41, 0.98 respectively. Comparing with the result of the error analysis on the predicted result, it is revealed that the use of nonlinear autoregressive network with exogenous inputs must be appropriate for the establishment of urban flood response system in the future.

• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1217-1227
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• 2018

This paper aims to evaluate the applicability of dam inflow prediction model using recurrent neural network theory. To achieve this goal, the Artificial Neural Network (ANN) model and the Elman Recurrent Neural Network(RNN) model were applied to hydro-meteorological data sets for the Soyanggang dam and the Chungju dam basin during dam operation period. For the model training, inflow, rainfall, temperature, sunshine duration, wind speed were used as input data and daily inflow of dam for 10 days were used for output data. The verification was carried out through dam inflow prediction between July, 2016 and June, 2018. The results showed that there was no significant difference in prediction performance between ANN model and the Elman RNN model in the Soyanggang dam basin but the prediction results of the Elman RNN model are comparatively superior to those of the ANN model in the Chungju dam basin. Consequently, the Elman RNN prediction performance is expected to be similar to or better than the ANN model. The prediction performance of Elman RNN was notable during the low dam inflow period. The performance of the multiple hidden layer structure of Elman RNN looks more effective in prediction than that of a single hidden layer structure.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.35-43
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• 2021

Citrus quality is generally determined by its sugar content and acidity. In particular, sugar content is a very important factor because it determines the taste of citrus. Currently, the most commonly used method of measuring citrus sugar content in farms is a portable juiced sugar meter and a non-destructive sugar meter. This method can be easily measured by individuals, but the accuracy of the sugar content is inferior to that of the citrus NongHyup official machine. In particular, there is an error difference of 0.5 Brix or more, which is still insufficient for use in the field. Therefore, in this paper, we propose an AI model that predicts the citrus sugar content of unmeasured days within the error range of 0.5 Brix or less based on the previously collected citrus sugar content and meteorological data (average temperature, humidity, rainfall, solar radiation, and average wind speed). In addition, it was confirmed that the prediction model proposed through performance evaluation had an mean absolute error of 0.1154 for Seongsan area and 0.1983 for the Hawon area in Jeju Island. Lastly, the proposed model supports an error difference of less than 0.5 Brix and is a technology that supports predictive measurement, so it is expected that its usability will be highly progressive.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.30-30
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• 2023

This study aims to establish the multi-reservoir operation system model in the Upper Mun River Basin which includes 5 main dams namely, Mun Bon (MB), Lamchae (LC), Lam Takhong (LTK), Lam Phraphoeng (LPP), and Lower Lam Chiengkrai (LLCK) Dams. The knowledge and AI technology were applied aiming to develop innovative prototype for SMART dam-reservoir operation in future. Two different sorts of reservoir operation system model namely, Fuzzy Logic (FL) and Constraint Programming (CP) as well as the development of rainfall and reservoir inflow prediction models using Machine Learning (ML) technique were made to help specify the right amount of daily reservoir releases for the Royal Irrigation Department (RID). The model could also provide the essential information particularly for the Office of National Water Resource of Thailand (ONWR) to determine the short-term and long-term water resource management plan and strengthen water security against flood and drought in this region. The simulated results of base case scenario for reservoir operation in the Upper Mun from 2008 to 2021 indicated that in the same circumstances, FL and CP models could specify the new release schemes to increase the reservoir water storages at the beginning of dry season of approximately 125.25 and 142.20 MCM per year. This means that supplying the agricultural water to farmers in dry season could be well managed. In other words, water scarcity problem could substantially be moderated at some extent in case of incapability to control the expansion of cultivated area size properly. Moreover, using AI technology to determine the new reservoir release schemes plays important role in reducing the actual volume of water shortfall in the basin although the drought situation at LTK and LLCK Dams were still existed in some periods of time. Meanwhile, considering the predicted inflow and hydrologic factors downstream of 5 main dams by FL model and minimizing the flood volume by CP model could ensure that flood risk was considerably minimized as a result of new release schemes.

• Korean Journal of Ecology and Environment
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• v.56 no.2
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• pp.127-139
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• 2023

Daechung Reservoir has been suffering from severe cyanobacterial blooming periodically due to the water pollutants from the watershed, especially nutrients from nonpoint sources. As a countermeasure, an artificial wetland was constructed to mitigate the pollutant load from the watershed by utilizing the vegetation. We investigated the water quality of the influent and outflow of the wetland during years 2014~2020 to evaluate the performance of pollutant removal through the wetland. Major pollutants (e.g. BOD, COD, SS, T-N, and T-P) were largely reduced during the retention in the wetland while nutrients removal was more efficient than that of organic matters. Pollutant removal efficiency for different inflow concentrations was also investigated to estimate the wetland's capability as a way of managing nonpoint sources. The efficiency of water treatment was significantly higher when inflow concentrations were above 75^th percentile for all pollutant, implying the wetland can be applied to the pre-treatment of high pollution load including initial rainfall runoff. Furthermore, the yearly variation of removal efficiency for seven years was analyzed to better understand long-term trends in water treatment of the wetland. The annual treatment efficiency of T-P was very high in the early stages of vegetation growth with high concentration of inflow water. However, it was confirmed that the concentration of inflow water decreased, vegetation stabilized, and the treatment efficiency gradually decreased as the soil was saturated. The findings of the study suggest that artificial wetlands can be an effective method for controlling harmful algal blooms by alleviating pollutant load from the tributaries of Daechung Reservoir.