• Journal of Korea Water Resources Association
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• v.50 no.3
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• pp.139-153
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• 2017

The variation in runoff due to global climate change and urbanization should be identified quantitatively because these two factors have been significantly accelerated during the last three decades in South Korea. However, only a few research to analyze the impacts due to two factors over different time scales can be found. Therefore, in this study, the hydrological model based approach and the hydrological sensitivity approach were used to separate relative impacts by two factors on monthly, seasonal, and annual time scales at the Soyang River upper basin and the Seom River basin in South Korea. The 3 techniques such as the double mass curve method, the Pettitt's test, and the BCP analysis were performed to detect change point occurred by abrupt change in the collected observed runoff. After detection of change ponts, SWAT models calibrated on the natural periods were used to calculate the changes due to human activities. Also, 6 Budyko based methods were auxiliary to verify the results from hydrological based approach.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.4
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• pp.81-94
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• 2006

The water quality impacts of forest fragmentation at the Doam-dam watershed were evaluated in this study. For this ends, the watershed scale model, Soil and Water Assessment Tool (SWAT) model was utilized. To exclude the effects of different magnitude and patterns in weather, the same weather data of 1985 was used because of significant differences in precipitation in year 1985 and 2000. The water quality impacts of forest fragmentation were analyzed temporarily and spatially because of its nature. The flow rates for Winter and Spring has increased with forest fragmentations by $8,366m^3/month$ and $72,763m^3/month$ in the S1 subwatershed, experiencing the most forest fragmentation within the Doam-dam watershed. For Summer and Fall, the flow rate has increased by $149,901m^3/month$ and $107,109m^3/month$, respectively. It is believed that increased flow rates contributed significant amounts of soil erosion and diffused nonpoint source pollutants into the receiving water bodies. With the forest fragmentation in the S1 watershed, the average sediment concentration values for Winter and Spring increased by 5.448mg/L and 13.354mg/L, respectively. It is believed that the agricultural area, which were forest before the forest fragmentation, are responsible for increased soil erosion and sediment yield during the spring thaw and snow melts. For Spring and Fall, the sediment concentration values increased by 20.680mg/L and 24.680mg/L, respectively. Compared with Winter and Spring, the increased precipitation during Summer and Fall contributed more soil erosion and increased sediment concentration value in the stream. Based on the results obtained from the analysis performed in this study, the stream flow and sediment concentration values has increased with forest fragmentation within the S1 subwatershed. These increased flow and soil erosion could contribute the eutrophication in the receiving water bodies. This results show that natural functionalities of the forest, such as flood control, soil erosion protection, and water quality improvement, can be easily lost with on-going forest fragmentation within the watershed. Thus, the minimize the negative impacts of forest fragmentation, comprehensive land use planning at watershed scale needs to be developed and implemented based on the results obtained in this research.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.212-212
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• 2023

비점오염원관리와 같이 장기적인 유역 관리 계획에서 유역 내 오염원 평가는 정말 중요하다. 유역 내 오염원 평가는 강우 유출에 의한 비점오염 발생원이 어디서 얼마나 발생시키는지에 대한 정량적인 조사가 필요하다. 유역 내의 오염원에 대한 정량적인 조사는 많은 비용과 시간이 필요하다. 이러한 비용과 시간을 줄이기 위해 유역단위 수리 수문 모델을 사용하고 있다. 유역단위 수리수문 모델은 HSPF (Hydrological Simulation Program in Fortran), SWAT (Soil and Water Assessment Tool), L-THIA ACN-WQ(The Long-term Hydrologic Impact Assessment Model with Asymptotic Curve Number Regression Equation and Water Quality model)등 다양한 모델이 사용되고 있다. 하지만 유역 모델을 통한 모의는 다양한 연산 과정을 진행하여 모의까지 많은 시간이 필요하다는 단점이 있다. 이에 따라 데이터 기반 모델링 기법(머신러닝/딥러닝)을 이용한 유출 및 수질 예측 연구가 많이 이루어지고 있다. 단순 머신러닝/딥러닝 기반 모델링 기법은 점(최종유출구)에서의 예측만 가능하여 최적관리 기법 적용 등과 같은 유역관리 방안을 적용하기 힘들다는 문제점이 있다. 따라서 본 연구에서 머신러닝/딥러닝을 통해 일부 수문 프로세스를 대체하고 소유역별 하도추적 기법을 연계하여 유량 및 수질 항목들의 모의가 가능한 하이브리드 모델을 개발하였다. 이는 머신러닝/딥러닝이 유역 모델의 일부 연산 과정을 대체하여 모의시간이 빠르며, 기존 머신러닝/딥러닝 예측 모델에서 평가가 어려웠던 유역 관리 방안 및 최적관리기법 적용 평가에도 활용이 가능할 것으로 판단이 된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.314-318
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• 2009

본 연구의 목적은 강우-유출자료 및 댐 방류량 자료의 비선형적인 특정을 가장 잘 반영할 수 있는 신경망모형을 적용하여 수질정책의 기초자료를 제공하기 위하여 신뢰성 있는 유량자료를 산정하는 모형을 개발하였고 이를 낙동강 유역에 적용하는 것이다. 이를 위해서 낙동강물환경연구소의 8일 측정 유량이 가지는 정확성을 이용하면서 상류 댐의 일 방류량자료와 유역별 강우자료 및 국토해양부 수위관측소의 수위자료를 연계하여 유량을 보간할 수 있는 유량 보간 신경망 모형을 개발하였다. 신경망 모형의 출력값은 낙동강물환경 연구소에서 측정하지 않은 기간에 대하여 유량을 보간할 수 있도록 구성하였으며 신경망 모형의 구조는 입력층과 출력층 사이에 하나의 은닉층이 존재하는 다층 신경망으로 구성하였으며, 학습단계에서는 오류 역전파 알고리듬 학습방법 중 모멘텀법을 사용하였다. 본 연구를 통하여 낙동강 전 유역에 대하여 유량 보간 모형을 적용한 결과 댐 방류량과 강우자료 및 상류 수위 관측소의 유량 자료를 이용한 유량 보간 신경망모형의 일 유량결과의 적용가능성을 검증할 수 있으며, 제시된 모형은 지속적인 수문자료의 질적 향상과 유출패턴의 축적으로 그 성능을 향상시킬 수 있을 것이며 또한 홍수기의 더 정확한 유량예측을 위한 적용사례의 확장 및 SWAT을 이용한 모형의 적용에 대한 연구가 병행되어야 할 것이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.652-656
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• 2007

The major streams in South Korea have established the TMDL(Total Maximum Daily Loads) regulation for just 4 years. Traditional concepts in water quality management in South Korea are based upon the selection of a design streram flow which is 10-year averged flow exeedance probability 75%(Q275). That is, a single flow value based upon average long term flow conditions is chosen for application in dilution calculations, permit design, water quality modeling, etc. While these TMDLs seems to satisfy the requirement of the target water quality regulations, they have contributed little to any watershed/waterbody assessment and restoration plans. These types of TMDLs do little to characterize the problems the TMDLs are intended to address. For TMDLs to be more beneficial in the assessment and implementation process, TMDLs should reflect adequate water quality across flow conditions rather than at a single flow value such as average daily flow. In this paper, we developed LDC (load duration curve) methodology for theevaluation of Korean TMDL evaluation based on watershed scaled, physically based on SWAT(Soil and Water Assessment Tool) model.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.38-38
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• 2023

Pleikrong reservoir with a concrete gravity dam that impound more than 1 billion cubic meter storage volume is one of the largest reservoir in Central Highland of Vietnam. Sedimentation is a major problem in this area and it becomes more severe due to the effect of climate change. Over time, it gradually reduces the reservoir storage capacity affecting to the reliability of water and power supply. This study aims to integrate the soil and water assessment tool (SWAT) model with 14 bias-corrected GCM/RCM models under two emissions scenarios, representative concentration pathway (RCP) 4.5 and 8.5 to estimate sediment inflow to Pleikrong reservoir in the long term period. The result indicated that the simulated total amount of sediment deposited in the reservoir from 2010 to 2018 was approximately 39 mil m³ which is a 17% underestimate compared with the observed value of 47 mil m³. The results also show the reduction in reservoir storage capacity due to sedimentation ranges from 25% to 62% by 2050, depending on the different climate change models. The reservoir reduced storage volume's rate in considering the impact of climate change is much faster than in the case of no climate change. The outcomes of this study will be helpful for a sustainable and climate-resilient plan of sediment management for the Pleikrongreservoir.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.6
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• pp.965-972
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• 2017

Assessment of vulnerability of water use to climate change include a variety of climate change scenarios. However, in most future vulnerability studies, only the climate change scenarios are used and not the future scenarios of social and economic indicators. Therefore, in this study, we applied the Representative Concentration Pathway (RCP) climate change scenario and Shared Socioeconomic reference Pathway (SSP) developed by IPCC to reflect the future. We selected indicators for estimating the vulnerability of water use, and indices were integrated with a multi-criteria decision making approach - Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The indicator data utilized national statistics and reports, social and economic scenarios, and simulated results from the Soil and Water Assessment Tool (SWAT) model which reflects climate change scenario. Finally, we derived the rankings of water use vulnerability for the short-term future (2020) and mid-term future (2050) within the Han River watershed. Generally, considering climate change alone and considering climate change plus social and economic changes showed a similar spatial distribution. In the future scenarios, the watershed rankings were similar, but showed differences with SSP scenario in some watersheds. Therefore, considering social and economic changes is expected to contribute to more effective responses to climate change.

• The Journal of Engineering Geology
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• v.23 no.4
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• pp.375-380
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• 2013

The concept of safe yield places an emphasis on balancing groundwater withdrawal with groundwater recharge but ignores naturally occurring groundwater discharge. Because streams and their alluvial aquifers are closely linked in terms of water supply and water quality, to be properly understood and managed they must be considered together. Therefore, some districts in Kansas have reevaluated their safe-yield policies to account for natural groundwater discharge and stream-aquifer interactions by amending their safe-yield regulations to include a portion of baseflow as the minimum desirable streamflow (MDS). This study proposes a modified safe-yield policy in which the drought flow is chosen as the MDS. Baseflow separation was conducted from streamflow hydrograph and the results are presented as a flow-duration curve. The exploitable groundwater can be determined by subtracting MDS from the cumulative baseflow. This method was tested in the Musimcheon watershed, which was validated for streamflow using the SWAT-K model. The annually averaged exploitable groundwater in the whole watershed was estimated to be 86 mm. The exploitable groundwater amounts were also estimated for each subwatershed in the Musimcheon watershed.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1727-1731
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• 2008

수자원의 효율적인 관리를 위해서는 신뢰성 있는 유량자료의 획득이 대단히 중요하다. 우리나라는 양질의 유량자료를 획득하기 위해 매년 많은 시간과 돈을 투자하고 있으나 자료의 질적인 면에서 만족할 만한 성과를 얻지 못하고 있다. 현재까지 우리나라의 유량자료는 댐의 수문자료와 수량관리 부처인 건교부에서 운영하는 수위표 지점의 수위-유량곡선에서 산출된 자료에 의존하고 있다. 그러나 수위-유량 관계식을 보정하기 위한 유량측정사업이 지속적이지 못하며, 이 관계식은 유량이 적은 저수기 및 갈수기에는 부정확하다는 한계가 있다. 또한, 국립환경과학원 낙동강물환경연구소에서 오염총량관리를 위한 낙동강수계 유량측정사업을 실시하고 있지만, 목적은 낙동강수계의 오염총량관리 단위유역 말단 47개 지점에서 유량측정을 효율적으로 실시하여 수질정책의 기초자료를 제공하는데 있다. 이 자료 역시 오염총량관리를 위하여 유량측정을 실시하여 수자원의 효율적인 관리를 위한 일 유량을 알 수가 없는 한계점을 가지고 있다. 따라서 저수기 및 갈수기에 수질정책의 기초자료를 제공하기 위해서 하천을 포함한 유역의 정확한 강우-유출특성의 파악이 필요하다. 그러나 강우-유출특성 또한 유역 내 강우의 시 공간적 분포가 다르며 그 자가 비선형성이 강하고 여러 변동성을 포함하므로, 강우로부터 하천의 유출량의 정확한 해석이 불가능하다. 그러나 최근 인공지능 분야에서 신호처리, 지능제어 및 패턴인식 등의 수단으로 사용되고 있는 신경망은 학습이라는 최적화 과정을 통해 입력과 출력으로 구성되는 하나의 시스템을 비선형적으로 구축할 수 있으며 이러한 이점을 활용하여 수자원 분야에서 다양하게 적용되고 있다. 본 연구의 목적은 강우-유출자료 및 댐 방류량 자료의 비선형적인 특정을 가장 잘 반영할 수 있는 신경망모형을 적용하여 수질정책의 기초자료를 제공하기 위하여 신뢰성 있는 유량자료를 산정하는 모형을 개발하는 것이다. 이를 위해서 낙동강물환경연구소에서 오염총량관리를 위한 낙동강수계 유량측정 지점 상류의 댐 방류량의 일 방류량자료와 강우자료를 입력 자료로 하여 유량을 예측할 수 있는 유량예측 신경망 모형 FFBN(Flow Forecasting By Neural)을 개발하였다. 그리고 입력 자료로서 장기유출모형인 SWAT의 모의결과를 입력 자료로 추가한 FFBNS(Flow Forecasting By Neural and SWAT)을 개발하였다. 신경망 모형의 구조는 입력층과 출력층 사이에 하나의 은닉층이 존재하는 다층 신경망으로 구성하였으며, 학습단계에서는 오류 역전파 알고리듬 학습방법 중 모멘텀법을 사용하였다. 예측된 유출량을 실측치와의 비교를 위하여 낙본D지점과 낙본 E지점에 대하여 $2005{\sim}2006$년까지의 모의 결과를 낙동 수위측정지점과 구미 수위측정지점의 실측치 통하여 복잡한 비선형성을 가지는 유출 시계열 자료에 대한 효과적인 최적의 신경망모델을 개발하여 유량을 예측하고 적용 가능성을 검토하고자 한다. 모의 결과는 수질정책의 기초자료 제공에 기여할 수 있을 것으로 판단된다.

• Journal of Korean Society on Water Environment
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• v.30 no.6
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• pp.638-646
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• 2014

Soil erosion from agricultural fields leads to various environmental problems weakening the capabilities of flood control and ecosystem in water bodies. Regarding these problems, Ministry of Environment of South-Korea prepared various structural and non-structural best management practices (BMPs) to control soil erosion. However, a lot of efforts are required to monitor and develop BMPs. Thus, modeling techniques have been developed and utilized for these issues. This study estimated the effectiveness of BMPs which are a vegetation mat with infiltration roll and Roll type vegetation channel using Soil and Water Assessment Tool (SWAT) model through the adjustment of the conservation practice factors, P factors, for Universal Soil Loss Equation which were calculated by monitoring data collected at the segment plots. Each BMP was applied to the areas with slopes ranged from 7% to 13% in the Haeanmyeon watershed. As a result of simulation, the vegetation mat with infiltration roll and Roll type vegetation channel showed 55% and 59% efficiency of soil erosion reduction, respectively. Also, Vegetation mat with infiltration roll and Roll type vegetation channel showed each 11.2% and 11.8% efficiency in reduction of sediment discharge. These roll type vegetation channel showed greater efficiency of soil erosion reduction and sediment discharge. Based on these results, if roll type vegetation channel is widely used in agricultural fields, reduction of soil erosion and sediment discharge of greater efficiency would be expected.