• 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.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 1999.04a
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• pp.149-156
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• 1999

In the United States (U.S.), the monitored natural attenuation (MNA) approach has been used as an alternative remedial option for organic and inorganic compounds retained in soil and dissolved in groundwater. The U.S. Environmental Protection Agency (EPA) defines the MNA as“in-situ naturally-occurring processes include biodegradation, diffusion, dilution, sorption, volatilization, and/or chemical and biochemical stabilization of contaminants and reduce contaminant toxicity, mobility or volume to the levels that are protective of human health and the environment”. The Department of Soil Environment. National Institute Environmental Research (NIER) is in the process for demonstrating the MNA approach as a potential remedial option for the BTEX contaminated site in Uiwang City. The project is charactering the research site in terms of the nature and extend of contamination, biological degradation rate, and geochemical and hydrological properties. The microbial-degradation rate and effectiveness of nutrient and redox supplements will be determined through laboratory batch and column tests. The geochemical process will be monitored for determining the concentration changes of chemical species involved in the electron transfer processes that include methanogenesis, sulfate and iron reduction, denitrification, and aerobic respiration. Through field works, critical soil and hydrogeologic parameters will be acquired to simulate the effects of dispersion, advection, sorption, and biodegradation on the fate and transport of the dissolved-phase BTEX plume using Bioplume III model. The objectives of this multi-years research project are (1) to evaluate the MNA approach using the BTEX contaminated site in Uiwang City, (2) to establish a standard protocol for future application of the approach, (3) to investigate applicability of the passive approach as a secondary treatment remedy after active treatments. In this presentation, the overall picture and philosophy behind the MNA approach will be reviewed. Detailed discussions of the site characterization/monitoring plans and risk-based decision-making processes for the demonstration site will be included.

• Journal of Korea Water Resources Association
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• v.41 no.10
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• pp.1035-1044
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• 2008

It is critical to study on data charateristics analysis and prediction for the flood disaster prevention and water quality monitoring because discharge and TOC data in a river channel are strongly nonlinear. Therefore, in the present study, prediction models for discharge, TOC, and TOC load data were developed using approximation component in the last level and detail components segregated by wavelet transform. The results show that the developed model overcame the persistence phenomenon which could be seen from previous models and improved the prediciton accuracy comparing with the previous models. It might be expected that the results from the present study can mitigate flood disaster damage and construct active alternatives to various water quality problems in the future.

• Journal of Korea Water Resources Association
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• v.54 no.6
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• pp.381-393
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• 2021

As part of the National Disaster Management Research Institute's Official Development Assistance (ODA) projects for transferring new technologies in the field of disaster-safety management, a flood forecasting and warning system was established in 2019 targeting the Borikhan in the Namxan River Basin in Bolikhamxai Province, Laos. In the target area, which is an ungauged small and medium river basin, observation stations for real-time monitoring of rainfall and runoff and alarm stations were installed, and a software that performs real-time data management and flood forecasting and warning functions was also developed. In order to establish a flood warning standard and develop a nomograph for flood prediction, hydraulic and hydrological analysis was performed based on the 30-year annual maximum daily rainfall data and river morphology survey results in the target area. This paper introduces the process and methodology used in this study, and presents the results of the system's applicability review based on the data observed and collected in 2020 after system installation.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.2
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• pp.55-67
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• 2022

Land use is a critical factor that affects the hydrological characteristics of watersheds, thereby determining the biological condition of streams. This study analyzes the effects of land uses in the watersheds on biological indicators of streams across the Han River basin using a linear model (LM) and generalized additive model (GAM). LULC and biological monitoring data of streams were obtained from the Korean Ministry of Environment. The proportions of urban, agricultural, and forest areas in the watersheds were regressed to the three biological indicators, including diatom, benthic macroinvertebrate, and fish of streams. The estimated LM and GAM models for the biological indicators were then compared, using regression determination R² and AIC values. The results revealed that GAM models performed better than the LM models in explaining the variances of biological indicators of streams, indicating the non-linear relationships between biological indicators and land uses in watersheds. Also, the results suggested that the indicator of macroinvertebrates was the most sensitive indicator to land uses in watersheds. Although non-linear relationships between watershed land uses and biological indicators of streams could vary among biological indicators, it was consistent that streams' biological integrity significantly deteriorated by a relatively low percentage of urban areas. Meanwhile, biological indicators of streams were negatively affected by the relatively high percentage of agricultural areas. The results of this study can be integrated into effective quantitative criteria for the watershed management and land use plans to enhance the biological integrity of streams. In specific, land uses management plans in watersheds may need more close attention to urban land use changes than agricultural land uses to sustain the biological integrity of streams.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.140-140
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• 2021

Urban flood management is a crucial and challenging task, particularly in developed cities. Therefore, accurate prediction of urban flooding under heavy precipitation is critically important to address such a challenge. In recent years, machine learning techniques have received considerable attention for their strong learning ability and suitability for modeling complex and nonlinear hydrological processes. Moreover, a survey of the published literature finds that hybrid computational intelligent methods using nature-inspired algorithms have been increasingly employed to predict or simulate the streamflow with high reliability. The present study is aimed to propose a novel approach, an ensemble tree, Bayesian Additive Regression Trees (BART) model incorporating a nature-inspired algorithm to predict hourly multi-step ahead streamflow. For this reason, a hybrid intelligent model was developed, namely GA-BART, containing BART model integrating with Genetic algorithm (GA). The Jungrang urban basin located in Seoul, South Korea, was selected as a case study for the purpose. A database was established based on 39 heavy rainfall events during 2003 and 2020 that collected from the rain gauges and monitoring stations system in the basin. For the goal of this study, the different step ahead models will be developed based in the methods, including 1-hour, 2-hour, 3-hour, 4-hour, 5-hour, and 6-hour step ahead streamflow predictions. In addition, the comparison of the hybrid BART model with a baseline model such as super vector regression models is examined in this study. It is expected that the hybrid BART model has a robust performance and can be an optional choice in streamflow forecasting for urban basins.

• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1047-1060
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• 2017

In recent years, global warming has been continuing and abnormal weather phenomena are occurring frequently. Especially in the 21st century, the intensity and frequency of hydrological disasters are increasing due to the regional trend of water. Since the damage caused by disasters in urban areas is likely to be extreme, it is necessary to prepare a landslide susceptibility maps to predict and prepare the future damage. Therefore, in this study, we analyzed the landslide vulnerability using the logistic model and assessed the management plan after the landslide through the field survey. The landslide area was extracted from aerial photographs and interpretation of the field survey data at the time of the landslides by local government. Landslide-related factors were extracted topographical maps generated from aerial photographs and forest map. Logistic regression (LR) model has been used to identify areas where landslides are likely to occur in geographic information systems (GIS). A landslide susceptibility map was constructed by applying a LR model to a spatial database constructed through a total of 13 factors affecting landslides. The validation accuracy of 77.79% was derived by using the receiver operating characteristic (ROC) curve for the logistic model. In addition, a field investigation was performed to validate how landslides were managed after the landslide. The results of this study can provide a scientific basis for urban governments for policy recommendations on urban landslide management.

• Journal of Korea Water Resources Association
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• v.46 no.11
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• pp.1129-1140
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• 2013

Precipitation is one of the important factors in the hydrological cycle. It needs to understand accurate of spatial precipitation field because it has large spatio-temporal variability. Precipitation data obtained through the Tropical Rainfall Monitoring Mission (TRMM) 3B43 product is inaccurate because it has 25 km space scale. Downscaling of TRMM 3B43 product can increase the accuracy of spatial precipitation field from 25 km to 1 km scale. The relationship between precipitation and the normalized difference vegetation index(NDVI) (1 km space scale) which is obtained from the Moderate Resolution Imaging Spectroradiometers (MODIS) sensor loaded in Terra satellite is variable at different scales. Therefore regression equations were established and these equations apply to downscaling. Two renormalization strategies, Geographical Difference Analysis (GDA) and Geographical Ratio Analysis (GRA) are implemented for correcting the differences between remote sensing-derived and rain gauge data. As for considering the GDA method results, biases, the root mean-squared error (RMSE), MAE and Index of agreement (IOA) is equal to 4.26 mm, 172.16 mm, 141.95 mm, 0.64 in 2009 and 17.21 mm, 253.43 mm, 310.56 mm, 0.62 in 2011. In this study, we can see the 1km spatial precipitation field map over Korea. It will be possible to get more accurate spatial analysis of the precipitation field through using the additional rain gauges or radar data.

• Journal of Soil and Groundwater Environment
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• v.26 no.6
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• pp.144-156
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• 2021

This study examined hydrogeological characteristics of groundwater and surface water interaction in the fresh-saline water mixed zone of East Coast lagoon area, Korea, using several technical approaches including hydrological, lithological, and isotopic methods. In addition, the fresh-saline water interface was evaluated using vertical electrical conductivity (EC) data. For this purpose, three monitoring wells (SJ-P1, SJ-P2, and SJ-P3) were installed across the Songji lagoon at depths of 7.4 to 9.0 m, and water level, EC, and temperature at the wells and in the lagoon (SJ-L1) were monitored using automatic transducers from August 1 to October 21, 2021. Isotopic composition of the groundwater, lagoon water, and sea water were also monitored in the mid-September, 2013. The mixing ratios calculated from oxygen and hydrogen isotopic composition decreased with increasing depth in the monitoring wells, indicating saline water intrusion. In the study area, the interaction of groundwater-surface water-sea water was evident, and residual salinity in the sedimentary layers created in the past marine environment showed disorderly characteristics. Moreover, the horizontal flow at the lagoon's edge was more dominant than the vertical flow.

• Journal of Soil and Groundwater Environment
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• v.26 no.6
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• pp.130-143
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• 2021

Wetlands are one of the most representative groundwater dependent ecosystems(GDEs) that require access to groundwater on a permanent or intermittent basis to maintain their biological communities and ecological processes. In this study, the seasonal characteristics of the GDEs in Baekseok Reservoir Wetland were evaluated through the monitoring of the temporal and spatial community of benthic macroinvertebrates in the wetland. The appearance of benthic macroinvertebrates appearance was changed seasonally depending on environmental factors such temperature, precipitation and water level for their habitat and it also showed the clear spatial difference in the wetland. The scores of Diversity index(H'), Richness Index (R1) and the Ecological score of benthic macroinvertebrates (TESB/AESB) were relatively high at St.3 and 4(i.e., north area) where groundwater inflows into wetland(i.e., high ²²²Rn conc.). The statistical analysis (ANOVA test and PCA) investigated the correlation among the benthic macroinvertebrates' community, groundwater level, wetland water level and water quality. The results showed that the community of benthic macroinvertebrates at St. 3 and 4 in Baekseok Reservoir Wetlands was spatially dependent on groundwater level and groundwater inflow. The characterization and assessment of GDEs requires understanding the hydrological, biogeochemical and biological process and this study will provide information for characterization and assessment of GDEs.