• Journal of Korea Water Resources Association
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• v.55 no.5
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• pp.345-356
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• 2022

A severe flooding occured at a small urban catchment in Daejeon-si South Korea on July 30, 2020 causing significant loss of property (inundated 78 vehicles and two apartments) and life (one casualty and 56 victims). In this study, a retrospective analysis of the inundation event was implemented using a physically-based urban flood model, H12 with high-resolution data. H12 is an integrated 1-dimensional sewer network and 2-dimensional surface flow model supported by hybrid parallel techniques to efficiently deal with high-resolution data. In addition, we evaluated the impact of the flooding barriers which were installed after the flood disaster. As a result, it was found that the inundation was affected by a combination of multiple components including the shape of the basin, the low terrain of the inundation area located in the downstream part of the basin, and lack of pipe capacity to drain discharge from the upstream during heavy rain. The impact of the flooding barriers was analyzed by modeling with and without barriers on the high-resolution terrain input data. It was evaluated that the flood barriers effectively lower the water depth in the apartment complex. This study demonstrates capability of high-resolution physically-based urban modeling to quantitatively assess the past inundation event and the impact of the reduction measures.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1167-1181
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• 2021

In relation to the algae bloom, four types of blue-green algae that emit toxic substances are designated and managed as harmful Cyanobacteria, and prediction information using a physical model is being also published. However, as algae are living organisms, it is difficult to predict according to physical dynamics, and not easy to consider the effects of numerous factors such as weather, hydraulic, hydrology, and water quality. Therefore, a lot of researches on algal bloom prediction using machine learning have been recently conducted. In this study, the characteristic importance of water quality factors affecting the occurrence of Cyanobacteria harmful algal blooms (CyanoHABs) were analyzed using the random forest (RF) model for Bohyeonsan Dam and Yeongcheon Dam located in Yeongcheon-si, Gyeongsangbuk-do and also predicted the occurrence of harmful blue-green algae using the machine learning and deep learning models and evaluated their accuracy. The water temperature and total nitrogen (T-N) were found to be high in common, and the occurrence prediction of CyanoHABs using artificial neural network (ANN) also predicted the actual values closely, confirming that it can be used for the reservoirs that require the prediction of harmful cyanobacteria for algal management in the future.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.267-278
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• 2022

Recently Flood damage volume has increased as heavy rain has frequently occurred. Especially urban areas are a vulnerability to flooding damage because of densely concentrated population and property. A local government is preparing to mitigate flood damage through the heavy rain warning issued by Korea Meteorological Administration. This warning classification is identical for a national scale. However, Seoul has 25 administrative districts with different regional characteristics such as climate, topography, disaster prevention state, and flood damage severity. This study considered the regional characteristics of 25 administrative districts to analyze the flood vulnerability using entropy weight and Euclidean distance. The rainfall classification was derived based on probability rainfall and flood damage rainfall that occurred in the past. The result shows the step 2 and step 4 of rainfall classification was not significantly different from the heavy rain classification of the Korea Meteorological Administration. The flood vulnerability is high with high climate exposure and low adaptability to climate change, and the rainfall classification is low in the northern region of Seoul. It is possible to preemptively respond to floods in the northern region of Seoul based on relatively low rainfall classification. In the future, we plan to review the applicability of rainfall forecast data using the rainfall classification of results from this study. These results will contribute to research for preemptive flood response measures.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.291-300
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• 2022

Artificial disturbance in mountainous areas increases the sensitivity to erosion by exposure of the subsoil with a low loam ratio to the surface. In this study, rainfall simulations were conducted to evaluate the erodibility of sand and loamy sand in the interrill erosion by the rainfall-induced sheet flow. The mean diameters of sand and loamy sand used in the experiment were 0.936 mm and 0.611 mm, respectively, and the organic matter content was 2.0% and 4.2%, respectively. In the experimental plot, the runoff coefficient of overland flow increased 1.16 times in loamy sand rather than sand. Mean sediment yields of loamy sand and sand by sheet erosion were 3.71kg/m²/hr and 1.13kg/m²/hr respectively. The erodibility, the rate of soil erosion for rainfall erosivity factor, was 3.65 times greater in loamy sand than in sand. As the gradient of the steep slope increased from 24° to 28°, the sediment concentration and the erodibility for two soils increased by about 20%. The erodibility factor K of sandy soils for small plots was overestimated compared to the measured erodibility. This means that RUSLE can overestimate the sediment yields by sheet erosion on sandy soils.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.335-335
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• 2022

남한상세 기후변화 전망보고서(2021)는 2100년대 강원도 강수량이 현재보다 19% 증가하고, 평균기온이 현재보다 6.5℃ 상승할 것으로 공표했다. 강원도는 영동지역과 영서지역으로 분리돼 기후 차이가 분명하다. 기상청 ASOS 데이터(1986~2020)를 이용해 기후 특성을 확인한 결과 영동지역 강수량은 1,463mm, 평균기온은 10.5℃, 상대습도는 66%로 분석됐고, 영서지역 강수량은 1,307mm, 평균기온은 11℃, 상대습도는 68%로 분석됐다. 영동지역 강수량이 영서지역 강수량보다 약 156mm 더 많으며, 이는 영동지역에서 큰 규모의 우심 피해가 발생할 가능성이 존재함을 의미한다. 강원도 평년 우심 피해 현황을 살펴본 결과 영동지역은 5회(피해액: 62억 원), 영서지역은 24회(피해액: 62억원)가 발생했다. 이는 미래로 갈수록 더 심해질 것으로 판단되며, 이런 기상 재난을 객관적으로 판단할 수 있는 기준이 필요하다. 이에 본 연구에서는 기후변화에 따른 강원도 기후 재난취약성을 평가했다. 이를 위해 기후변화 위험성, 기후변화 민감도, 기후변화 적응능력 지표를 활용해 기후변화 취약성 지표를 선정했다. 기후변화 위험성 지표는 홍수(CWD, Rx5day, R30mm), 가뭄(CDD, SU, TX90p), 폭염(SU, TR, TN90p), 한파(ID, TX10p, FD)로 RCP 8.5 기후변화시나리오를 ETCCDI 지수에 적용했다. 기후변화 민감도와 기후변화 적응능력 지표는 국가통계포털, 강원통계정보, WAMIS에서 자료를 수집해 선정했다. 또한 재난취약성 지표를 4단계(Very Low, Low, High, Very High)로 구분했다. 홍수 취약성 평가 결과 2090년대 원주시, 춘천시, 횡성군이 Low에서 Very High로 단계가 격상됐다. 가뭄 취약성 평가 결과 2090년대 양양군, 영월군, 정선군이 Very Low에서 Very High로 단계가 격상됐다. 폭염 취약성 평가 결과 2090년대 삼척시, 태백시, 영월군이 Very Low에서 Very High로 단계가 격상됐다. 한파 취약성 평가 결과 삼척시, 태백시, 영월군이 High에서 Very Low로 단계가 격하됐다. 고로 강원도는 기후 재난취약성 평가 결과에 따른 미래 기후변화를 대비하고, 각 지역 특성에 맞는 복원력 관점 기후 재난 관리가 필요하다고 사료된다.

• Journal of Korea Water Resources Association
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• v.56 no.8
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• pp.509-520
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• 2023

Various drought indices are widely used for assessing drought conditions which are affected by many factors such as precipitation, soil moisture, and runoff. The values of drought indices varies depending on hydro-meteorological data and calculation formulas, and the judgment of the drought condition may also vary. This study selected four calculation components such as precipitation data length, accumulation period, probability distribution function, and parameter estimation method as the sources of uncertainty in the calculation of standardized precipitation index (SPI), and evaluated their contributions to the uncertainty using root mean square error (RMSE) and linear mixed model (LMM). The RMSE estimated the overall errors in the SPI calculation, and the LMM was used to quantify the uncertainty contribution of each factor. The results showed that as the accumulation period increased and the data period extended, the RMSEs decreased. The comparison of relative uncertainty using LMM indicated that the sample size had the greatest impact on the SPI calculation. In addition, as sample size increased, the relative uncertainty related to the sample size used for SPI calculation decreased and the relative uncertainty associated with accumulation period and parameter estimation increased. In conclusion, to reduce the uncertainty in the SPI calculation, it is essential to collect long-term data first, followed by the appropriate selection of probability distribution models and parameter estimation methods that represent well the data characteristics.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.871-881
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• 2023

This study investigates the geomorphic changes and Bed Relief Index of the river downstream of the Yeongju Dam by Nays2DH, a two-dimensional numerical model, in order to grasp the dynamics of the downstream river while applying various flow patterns such as pulse discharge. It shows that the geomorphic and the bed elevations changes are the largest under the condition of the normalized pulse discharge. The total change in the riverbed is 29.88 m for uniform flow, 27.46 m for normalized hydrograph, 29.63 m for pulse flow and 31.87 m for pulse flow with normalized hydrograph which result in the largest variation in scour and deposition. The Bed Relief Index (BRI) increases with time under conditions of uniform flow, pulse flow and pulse flow with normalized hydrograph. However, BRI increased rapidly until 30 hrs after the peak flow (14 hrs), but decreased from 56 hrs under the condition of normalized hydrograph. Therefore, the condition of normalized hydrograph gives greater dynamics than the condition of a single flood or constant flow, and the dynamics increase downstream than upstream, resulting in an effect on improving the environment of the river downstream of the dam.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.845-853
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• 2023

Recently, along with the increase in chemical accidents, the number of accidents-related disasters has been increasing continuously since 2012, and when looking at the hydrogen fluoride incident which is a representative example of domestic chemical incidents, there is insufficient technology applicable to the incident site. The result was that the damage spread. Therefore, in this paper, we will adapt the water pollution accident response system to a location-based approach, and introduce a measurement method for alternative index tracking using a GPS electronic floater of a location-based index measurement method for real-time response in the water environment when a chemical incident occurs. The research target area is Gumi City, which is the area where the hydrogen fluoride incident occurred, and Gamcheon is selected, and alternative tracking using GPS electronic floater is conducted in the corresponding target area through water quality and flow measurement. As a result, it is possible to measure water quality and flow at the same time in tracker experiments using GPS electronic floater based on the research results, it is believed that using GPS electronic floater will be of great help in disaster response systems for spill incidents in the river.

• Journal of the Korean Recycled Construction Resources Institute
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• v.12 no.2
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• pp.229-238
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• 2024

This study evaluated the odor removal performance of a bacteria-based odor reduction kit. The bacteria used were Rhodobacter capsulatus, Paracoccus limosus, and Brevibacterium hankyongi, which can remove ammonia (NH₃), hydrogen sulfide (H₂S), total nitrogen (T-P), and total phosphorus (T-N), which are odor pollutants. The materials used were bacteria and porous aggregates (expanded vermiculite, zeolite beads, activated carbon), and the combination of the materials varied depending on the removal mechanism. Materials with a physical adsorption mechanism (zeolite beads and activated carbon) gradually slowed down the concentration reduction rate of odor pollutants (NH₃, H₂S, T-P, and T-N), and had no further effect on reducing the concentration of odor pollutants after 60 hours. Expanded vermiculite, in which bacteria that remove odors through a bio-adsorption mechanism were immobilized, had a continuous decrease in concentration, and the concentration of odor pollutants reached 0 ppm after 108 hours. As a result, the odor removal performance of materials with physical adsorption mechanisms in actual river water did not meet the odor emission standard required by the Ministry of Environment, while the expanded vermiculite immobilized with bacteria satisfied the odor emission permissible standard and achieved water quality grade 1.

• Journal of Korea Water Resources Association
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• v.57 no.5
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• pp.321-332
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• 2024

Understanding the status of surface cover in riparian zones is essential for river management and flood disaster prevention. Traditional survey methods rely on expert interpretation of vegetation through vegetation mapping or indices. However, these methods are limited by their ability to accurately reflect dynamically changing river environments. Against this backdrop, this study utilized satellite imagery to apply the Random Forest method to assess the distribution of vegetation in rivers over multiple years, focusing on the Naeseong Stream as a case study. Remote sensing data from Sentinel-2 imagery were combined with ground truth data from the Naeseong Stream surface cover in 2016. The Random Forest machine learning algorithm was used to extract and train 1,000 samples per surface cover from ten predetermined sampling areas, followed by validation. A sensitivity analysis, annual surface cover analysis, and accuracy assessment were conducted to evaluate their applicability. The results showed an accuracy of 85.1% based on the validation data. Sensitivity analysis indicated the highest efficiency in 30 trees, 800 samples, and the downstream river section. Surface cover analysis accurately reflects the actual river environment. The accuracy analysis identified 14.9% boundary and internal errors, with high accuracy observed in six categories, excluding scattered and herbaceous vegetation. Although this study focused on a single river, applying the surface cover classification method to multiple rivers is necessary to obtain more accurate and comprehensive data.