• Spatial Information Research
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• v.21 no.6
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• pp.91-98
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• 2013

Government introduces a Total Maximum Daily Loads(TMDL) which can be implemented for total pollutant amounts in 2004. Normally, the local governments have been calculated the amounts of pollutant discharge of each watershed using a water quality model. However, among the input data to use the water quality model, creating a schematic diagram of the stream or the modeling usually requires considerable amount of time and efforts due to the manual work. Therefore, this study tried to develop an algorithm which automates the creation of a schematic diagram for water quality modeling using the Korean Reach File capable of river network analysis. Further, this study creates a schematic diagram with the shape of a stream utilizing GIS capabilities. The diagram can be easily analyzed with overlapping various spatial information such as pollution sources and discharge points. This study mainly has automated element segmentation algorithm to divide streamflows into equal distance using line graphic data of Koran Reach File. Also, automated attribute input algorithm has also been developed to enable to insert element order and type into elements using point graphic data of Korean Reach File. For the verification of the developed algorithm, the algorithm was applied to kyungan stream basin to see the acceptable results. To conclude, it was possible to automate generating of schematic diagram of water quality model and it is expected to be able to save time and cost required for the water modeling. In future study, it is necessary to develop an automatic creation system of various types of input data for water quality modeling and this will lead to relatively easier and simple water quality modeling.

• Journal of Wetlands Research
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• v.14 no.3
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• pp.385-397
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• 2012

A grid based physically distributed model analyzes rainfall-runoff using physical parameters and grid-typed spatial and hydrological data. This study have developed a real time runoff modelling system using GRM RT(Grid based Rainfall-runoff Model Real Time) which is a real time flow analysis module in GRM, a grid based physically distributed rainfall-runoff model. Weather radar data received in real time are calibrated by using real time AWS from Korea Meteorological Administration(KMA), and they are applied to real time runoff modeling. And the runoff model is calibrated by using observed discharges from a water level gauge in real time. This study have designed and implemented the databases necessary to construct the real time runoff modelling system, and established the process of a real time runoff modelling. And the performances of the developed system have been evaluated. The system have been applied to Nerinheon watershed located in the upstream of Soyanggang Dam and the application results are evaluated.

• Journal of the Korean Society of Hazard Mitigation
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• v.6 no.1 s.20
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• pp.69-81
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• 2006

The purpose of this study is to identify the downstream influences due to the dam discharge by using 2-dimensional model, SMS(Surface water Modeling System). RMA-2 and SED-2D in SMS were applied to Yongdam multipurpose dam watershed located in Gum river basin. Through the simulation, erosion and deposit quantitative analysis of sinuous channels and scour pattern analysis of bridges have been done. A differences erosion depths between deposit are simulated as $-102.4 mm{\sim}54.2 mm$ at No.176(1.4 km) and $-104.1 mm{\sim}28.9 mm$ at No.146(7.4 km), sinuous channel. The river bed at Kamdong bridge in straight channal is simulated as uniform erosion. However, the river bed at Dumdul bridge in sinuous channal has been shown as different erosion depths at each sides. Consequently, the parts that could not be simulated on the existing 1-dimensional model, can be improved results by using a 2-dimensional model, about weakness points for hydraulic modeling such as extreme bend, tributary confluence.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.351-351
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• 2021

저수지에 대한 비상대처계획수립은 최근 기상이변 등에 따른 대규모 호우가 빈번히 발생하고 있을 뿐만 아니라 세계 도처에서 대규모 지진 등으로 많은 인명과 재산 피해가 속출함에 따라 지진 및 이상홍수에 대한 저수지의 안정성 평가를 수행하고 저수지 지점에서 발생할 수 있는 천재지변 또는 예상치 못한 대규모 재해에 효율적으로 대처하기 위한 비상상황의 등급 및 위험수준을 체계적으로 판단하고 비상상황 가상 시나리오별 체계적 행동요령 및 대처계획을 수립하여 저수지 붕괴에 따른 대규모 홍수피해 예상지역 주민들의 신속한 대응으로 생명과 재산피해를 최소화하는데 목적이 있다. 현행 한국농어촌공사 및 지자체에서 수립하고 있는 30만 톤 이상 저수지에 대한 1차원 모형 기반의 EAP수립은 침수구역을 산정할 때 수치지도에 의한 단일 침수심 분석으로 실제 침수구역과는 많은 오류가 나타난다. 이는 침수구역 부정확에 따른 피해복구액 산정이 과다로 책정될 수 있고, 마지막으로 가장 중요한 비상대처계획 수립에 막대한 영향을 미친다. 이에 본 연구는 댐 붕괴에 대응하기 위한 EAP 수립 시 기본이 되는 홍수범람해석을 수행하고 1차원 및 2차원 모형의 결과검토를 통해 보다 효과적인 비상대처계획의 수립을 위한 방안을 제시하고자 하였다. 이를 위해 경천저수지 유역을 대상으로 가능최대강수량 조건 하에서 가능최대홍수량을 산정하고 DAMBRK 모형을 이용하여 댐 붕괴 모의를 위한 시나리오 구성 및 모의를 수행하였다. 이후 댐 붕괴 모의결과를 이용하여 WMS(Watershed Modeling System) 모형을 이용한 1차원 홍수범람해석과 FLUMEN(FLUvial Modeling ENgine) 모형을 이용한 2차원 홍수범람해석에 적용 후 각 결과를 비교·검토하였다.

• Spatial Information Research
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• v.10 no.2
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• pp.289-299
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• 2002

Recently, as the social interest about environmental problems is increased and the importance is highlighted, the related information and the demand of information are increased. and, the Total Pollution System will be executed soon. Therefore, the information management system which can manage and analysis related information efficiently and systematically become required. Especially, the development and application of GIS which can effectively manage and analyze information using spatial data have been processing by government, private institute, and related academic institute of all over the world. also their potentiality of application have been recognizing. The main purpose of this study is to develop the stream water quality management system which can simulate future water quality using water quality model(QUAL2E) and be integrated the whole step from calculating pollutant load divided by administrative district and watershed to displaying the result of modeling visually.

• Journal of the Korean association of regional geographers
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• v.17 no.2
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• pp.245-258
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• 2011

Best management practices (BMPs) are widely accepted and implemented as a mitigation method for soil erosion and non-point source problems. Estimating the amount of soil erosion and the effectiveness of BMPs using hydrological models help to understand the condition, identify the problems, and make plans for conservation practices in an area, typically a watershed. However, the accuracy and reliability of assessment of BMP impacts estimated by hydrological models can be often questionable due to the uncertainties from various sources including GIS(Geographic Information System) data, scale, and model. This study reviewed the development and the background of hydrological models, and the modeling issues such as the selection of models, scale, and uncertainties of data and models. This study also discussed the advantage of a small scale and spatially distributed model to estimate the impacts of BMPs.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.1
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• pp.49-66
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• 2024

Extreme rainfall will become intense due to climate change, increasing inundation risk to agricultural land. Hydrological and hydraulic simulations for the entire watershed were conducted to analyze the impact of climate change. Rainfall data was collected based on past weather observation and SSP (Shared Socio-economic Pathway)5-8.5 climate change scenarios. Simulation for flood volume, reservoir operation, river level, and inundation of agricultural land was conducted through K-HAS (KRC Hydraulics & Hydrology Analysis System) and HEC-RAS (Hydrologic Engineering Center - River Analysis System). Various scenarios were selected, encompassing different periods of rainfall data, including the observed period (1973-2022), near-term future (2021-2050), mid-term future (2051-2080), and long-term future (2081-2100), in addition to probabilistic precipitation events with return periods of 20 years and 100 years. The inundation area of the Aho-Buin district was visualized through GIS (Geographic Information System) based on the results of the flooding analysis. The probabilistic precipitation of climate change scenarios was calculated higher than that of past observations, which affected the increase in reservoir inflow, river level, inundation time, and inundation area. The inundation area and inundation time were higher in the 100-year frequency. Inundation risk was high in the order of long-term future, near-term future, mid-term future, and observed period. It was also shown that the Aho and Buin districts were vulnerable to inundation. These results are expected to be used as fundamental data for assessing the risk of flooding for agricultural land and downstream watersheds under climate change, guiding drainage improvement projects, and making flood risk maps.

• Economic and Environmental Geology
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• v.48 no.6
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• pp.477-490
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• 2015

In this study, we investigated the restoration possibility of the old streams by enhancing the rainwater infiltration in the watershed of Deokjin Park, Jeonju City. This study was performed by modeling groundwater discharge to the streams under various conditions. We assessed the amount and location of groundwater recharge enhancement to restore the streams and evaluated whether the baseflows of the restored streams are sufficient to keep the water ecosystem of the Deokjin Pond. The results show that the baseflow of the streams can persist for a longer time even during the dry season when the rainwater drainage system is recovered similarly to the those before development using low impact development (LID) techniques. The enhancements of recharge in the headwater area, which is the area around the zoo and Daeji Village in the Deokjin Park watershed, is useful to increase the baseflows of the downstream reaches. Furthermore, spreaded recharge over a widespread area is better to prevent the streams from drying than the intensive recharge at a few sites.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1317-1328
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• 2021

This study aims to provide a predictive model based on climate models for simulating continuous daily rainfall sequences by combining bias-correction and spatio-temporal downscaling approaches. For these purposes, this study proposes a combined modeling system by applying conditional Copula and Multisite Non-stationary Hidden Markov Model (MNHMM). The GloSea5 system releases the monthly rainfall prediction on the same day every week, however, there are noticeable differences in the updated prediction. It was confirmed that the monthly rainfall forecasts are effectively updated with the use of the Copula-based bias-correction approach. More specifically, the proposed bias-correction approach was validated for the period from 1991 to 2010 under the LOOCV scheme. Several rainfall statistics, such as rainfall amounts, consecutive rainfall frequency, consecutive zero rainfall frequency, and wet days, are well reproduced, which is expected to be highly effective as input data of the hydrological model. The difference in spatial coherence between the observed and simulated rainfall sequences over the entire weather stations was estimated in the range of -0.02~0.10, and the interdependence between rainfall stations in the watershed was effectively reproduced. Therefore, it is expected that the hydrological response of the watershed will be more realistically simulated when used as input data for the hydrological model.

• Journal of Korean Society on Water Environment
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• v.33 no.2
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• pp.219-229
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• 2017

A watershed-river linked modeling system was developed to forecast the water quality, particularly weekly changes in chlorophyll-a concentration, of the Yeongsan River, Korea. Hydrological Simulation Program-Fortran (HSPF) and Environmental Fluid Dynamics Code (EFDC) were adopted as the basic model framework. In this study, the EFDC model was modified to effectively simulate the operational condition and flow of multi-functional weirs constructed in the main channel of rivers. The model was tested against hydrologic, water quality and algal data collected at the right upstream sites of two weirs in 2014. The mean absolute errors (MAEs) of the model calibration on the annual variations of river stage, TN, TP, and algal concentration are 0.03 ~ 0.10 m, 0.65 ~ 0.67 mg/L, 0.03 ~ 0.04 mg/L, and $9.7{\sim}10.8mg/m^3$, respectively. On the other hand, the MAE values of forecasting results for chlorophyll-a level at the same sites in 2015 range from 18.7 to $22.4mg/m^3$, which are higher than those of model calibration. The increased errors in forecasting are mainly attributed to the higher uncertainties of weather forecasting data compared to the observed data used in model calibration.