• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.3
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• pp.109-121
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• 2020

Converting the agricultural land-use of rice field to upland has been increasingly conducted as farmers encourages themselves to grow higher value-added crops on rice fields under the policy support. Comparing to rice field, Upland shows different characteristic of discharge due to the slope, scale, and shape of field and characteristics of rainfall event. In this study, we designed the experiment fields reflecting flat-upland characteristics with different land scale, and tried to collect the discharge and load data. Soybeans and corn were selected as target crops considering the possibility of large-scale cultivation and crop demand. The cultivation was conducted during the growth period in 2019 with 3 different field scales. Hence, we have collected the discharge data from 17 rainfall events and the load data for 8 rainfall events. As a result, the magnitude of rainfall events and the discharge duration were found to have a strong positive correlation and field discharge occurred during the period by 55% to 83% of rainfall duration. Besides we found other relationships and characteristics of rainfall event, discharge, and pollutant load and also pointed out that continuous monitoring and more data are required to derive statistically significant results. Compared with slope-field monitoring data obtained from the precedent research, the runoff ratio of the flat-fields was significantly lower than slope-fields. Overall the discharge in the slop and flat-fields shows appreciably different characteristics so that the related researches need to be further conducted to reasonably assess environmental impact of agricultural activities at flat-field.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.1
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• pp.39-51
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• 2016

Extreme floods occur more often recently as the frequency of extreme storm events increase due to the climate change. Because the extreme flood exceeding the design flood can cause large-scale disasters, it is important to predict and prepare for the future extreme flood. Flood flow is affected by two main factors; rainfall and land use. To predict the future extreme flood, both changes in rainfall due to the climate change and land use should be considered. The objective of this study was to simulate the future design flood in the Hwangguji river watershed, South Korea. The climate and land use change scenarios were derived from the representative concentration pathways (RCP) 4.5 and 8.5 scenarios. Conversion of land use and its effects (CLUE) and hydrologic modelling system (HEC-HMS) models were used to simulate the land use change and design flood, respectively. Design floods of 100-year and 200-year for 2040, 2070, and 2100 under the RCP4.5 and 8.5 scenarios were calculated and analyzed. The land use change simulation described that the urban area would increase, while forest would decrease from 2010 to 2100 for both the RCP4.5 and 8.5 scenarios. The overall changes in design floods from 2010 to 2100 were similar to those of probable rainfalls. However, the impact of land use change on design flood was negligible because the increase rate of probable rainfall was much larger than that of curve number (CN) and impervious area.

• Journal of Wetlands Research
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• v.18 no.1
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• pp.10-15
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• 2016

In this research, the environmental effects of rain garden when applied to a stormwater runoff originated from a rooftop were evaluated. The rain garden that was utilized as LID represents less than 1% of the catchment area that it drains. Storm event monitoring was conducted from March 2012 to August 2014 on a total of 19 storm events. In the 19 storm events that was monitored only 32% produced an outflow which has a mean rainfall characteristic of approximately 25 mm. With the application of rain garden, hydrologic improvement was observed as the facility exhibit a delay and reduction in the production of runoff and peak flows as the rainfall progresses. Furthermore, in terms of pollutant reduction, it was observe that the rain garden showed a generally satisfactory performance in reducing pollutants. In addition to this, the rain garden also has additional attributes that adds to the aesthetic appeal of the surrounding environment as well as in the lives of the people. The findings of this research will help in the further improvement and reinforcement of LID designs.

• Journal of Korea Water Resources Association
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• v.44 no.3
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• pp.209-220
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• 2011

Input uncertainty is one of the major sources of uncertainty in hydrologic modeling. In this paper, first, three alternate rainfall inputs generated by different interpolation schemes were used to see the impact on a distributed watershed model. Later, the residuals of precipitation interpolations were tested as a source of ensemble streamflow generation in two river basins in the U.S. Using the Monte Carlo parameter search, the relationship between input and parameter uncertainty was also categorized to see sensitivity of the parameters to input differences. This analysis is useful not only to find the parameters that need more attention but also to transfer parameters calibrated for station measurement to the simulation using different inputs such as downscaled data from weather generator outputs. Input ensembles that preserves local statistical characteristics are used to generate streamflow ensembles hindcast, and showed that the ensemble sets are capturing the observed steamflow properly. This procedure is especially important to consider input uncertainties in the simulation of streamflow forecast.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.1
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• pp.39-50
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• 2020

The objective of this study was to assess the livestock nonpoint source pollutant impact on water quality in Namgang dam watershed using the HSPF (Hydrological Simulation Program-Fortran) model. The input data for the HSPF model was established using the landcover, digital elevation, and watershed and river maps. In order to apply the pollutant load to the HSPF model, the delivery load of the livestock nonpoint source in the Namgang dam watershed was calculated and used as a point pollutant input data for the HSPF model. The hydrologic and water quality parameters of HSPF model were calibrated and validated using the observed runoff data from 2007 to 2015 at Sancheong station. The R² (Determination Coefficient), RMSE (Root Mean Square Error), NSE (Nash-Sutcliffe efficiency coefficient), and RMAE (Relative Mean Absolute Error) were used to evaluate the model performance. The simulation results for annual mean runoff showed that R² ranged 0.79~0.81, RMSE 1.91~2.73 mm/day, NSE 0.7~0.71 and RMAE 0.37~0.49 mm/day for daily runoff. The simulation results for annual mean BOD for RMSE ranged 0.99~1.13 mg/L and RMAE 0.49~0.55 mg/L, annual mean TN for RMSE ranged 1.65~1.72 mg/L and RMAE 0.55 mg/L, and annual mean TP for RMSE ranged 0.043~0.055 mg/L and RMAE 0.552~0.570 mg/L. As a result of livestock nonpoint pollutant loading simulation for each sub-watersehd using the HSPF model, the BOD ranged 16.6~163 kg/day, TN ranged 27.5~337 kg/day, TP ranged 1.22~14.1 kg/day.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.3
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• pp.105-115
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• 2008

Urbanization results in increased runoff volume and peak flowrate and shortening in time of concentration, which may cause frequent flooding downstream. There are various types of flow retardation methods including detention ponds, retention ponds, and infiltration ponds. In general, hydrologic models to design the detention pond are classified into planning model and design model. This study is comparing and analyzing of planning model to design the detention pond in urban area. Detention ponds data of Disaster Impact Assessment Report on 22 sites were analyzed to investigate proper planning models in this study. From this research, following conclusions are derived, 1) In case of on-line detention pond, Lee model(1991) is the best planning model and similar to real storage volume. 2) In case of off-line detention pond, Abt and Grigg model is much more proper model compared to other models.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.102-102
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• 2015

최근 중소규모 하천은 하천수 및 하천변 지하수 이용의 증가와 토지이용변화 등 유역 내 수문인자의 특성 변화로 인해 하천의 건천화가 점증하고 있어 하천 환경이 악화되고 있는 실정이다. 본 연구에서는 격자기반의 분포형 장기수문 모델(PGA-CC)을 이용하여 과거 수십년동안 토지이용변화에 따른 하천 건천화 영향을 평가하였다. 실제 건천화가 진행되고 있는 삽교천 상류유역($358.8km^2$)을 선정하였고 토지이용변화분석을 위해 과거 1975년 토지이용도(Past), 현재 2008년 토지이용도(Present)를 구축하였다. 각각의 토지이용 항목 중 변화율이 가장 높은 도시비율은 과거 토지이용도에서는 2.6 %였으며 현재 토지이용도에서는 11.3 %로 8.7 %가 증가하였다. 모델 검보정은 최근 7년(2005-2011)동안 최종유역출구지점에서 유출 검보정을 실시하였다. 그 결과 NSE (Nash-Sutcliffe model efficiency)은 평균 0.71로 유출량의 모의값과 실측값이 유효한 것으로 나타났다. 건천화를 평가하기 위해 시험유역에서의 5 WPs (Watching Points)를 선정하여 과거 및 현재 토지이용조건을 모의하고 유황분석을 통한 갈수 변화량 분석을 실시하였다. 건천화 빈도분석을 위해 GEV (Generalized Extreme Value) 갈수빈도분석을 실시하여 과거 토지이용 모의결과 산정된 평균 갈수량($m^3/s$) 이하로 낮아지는 유출량 일수를 계산하였다. 최종유역출구에서 과거 및 현재 토지이용도에서 모의된 평균갈수량은 각각 $3.27m^3/s$ 및 $3.11m^3/s$로 나타났다. GEV 갈수빈도분석결과 과거 토지이용조건에서의 평균갈수량은 $3.20m^3/s$(재현기간 2.33년)으로 나타났다. 도시증가에 따른 인구증가는 지하수 사용량에 증가를 가져온다. 이는, 건천화에 영향을 미치며 본 연구에서는 지하수이용량 자료(1998-2011)를 이용하여 도시면적과 지하수이용량의 선형회귀분석을 실시하여 과거 22년 지하수 사용량을 예측하였다. 그 결과 지하수사용량 증가는 토지이용변화와 복합적으로 상류유역에 하천의 변화를 가속시키는 것으로 나타냈다.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.114-114
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• 2019

최근 들어 집중호우 및 토지이용 변화로 인한 고탁수 문제가 빈번히 발생하고 있다. 이러한 탁수 및 수질오염 문제를 해결하기 위해 환경부는 비점오염원 관리지역을 선정하였으며, Best Management Pratices(BMPs), Low Impact Development(LID) 등 다양한 저감 대책을 시행하고 있다. 비점오염원의 발생원인과 발생위치를 정확하게 증명할 수 없으므로 유역 내 수문 및 수질을 모의할 수 있는 Soil and Water Assessment Tool(SWAT) 모델이 다양한 비점오염원 연구에 널리 활용되고 있다. 그러나 SWAT 모델은 Hydrologic Response Unit(HRU)의 경사도와 경사장을 산정할 때 소유역 내 평균 경사도를 이용하여 토양유실량 및 유출특성을 모의에 필요한 매개변수들을 산정한다는 한계점이 있다. 본 연구에서는 이러한 SWAT 모형의 단점을 보완하기 위하여 실제 경작지를 기준으로 HRU를 생성하고, 실측 경사도와 경사장을 적용하기 위한 기술을 개발하였다. 본 연구에서 개발한 기술을 고탁수로 인해 비점오염원 관리지역으로 지정된 도암호 유역에 적용하여 실측 경사도와 경사장을 적용하여 모의한 유출량과 기존의 SWAT 모델을 통해 모의한 유출량을 비교 분석하였다. 기존 모델의 결과와 본 연구에서 개발한 기술을 적용하여 모의한 결과를 비교하였을 때 수문 컴포넌트 중 중간유출과 기저유출에 있어서 차이가 발생한 것을 알 수 있었다. 또한 본 연구에서 개발된 기술을 적용함으로써 도암호 유역에서 비교적 정확한 토양유실과 Suspended Solids(SS) 모의 결과를 나타냈다. 하지만 본 연구는 도암호 유역만을 대상으로 수행되었기 때문에 다른 비점오염 관리지역에 확대 적용하여 본 연구의 결과를 재검토할 필요가 있다.

• Journal of Korean Society on Water Environment
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• v.27 no.4
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• pp.405-412
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• 2011

Increased Non-permeable areas which have resulted from civilization reduce the volume of groundwater infiltration that is one of the important factors causing water shortage during a dry season. Thus, seeking the efficient method to analyze the volume of groundwater in accurate should be needed to solve water shortage problems. In this study, two different watersheds were selected and precipitation, soil group, and land use were surveyed in a particular year in order to figure out the accuracy of estimated infiltration recharge ratio compared to Web-based Hydrograph Analysis Tool (WHAT). The volume of groundwater was estimated considering Antecedent soil Moisture Condition (AMC) and Curve Number (CN) using Long Term Hydrologic Impact Assessment (L-THIA) model. The results of this study showed that in the case of Kyoung-an watershed, the volume of both infiltration and baseflow seperated from WHAT was 46.99% in 2006 and 33.68% in 2007 each and in Do-am watershed the volume of both infiltration and baseflow was 33.48% in 2004 and 23.65% in 2005 respectively. L-THIA requires only simple data (i.e., land uses, soils, and precipitation) to simulate the accurate volume of groundwater. Therefore, with convenient way of L-THIA, researchers can manage watershed more effectively than doing it with other models. L-THIA has limitations that it neglects the contributions of snowfall to precipitation. So, to estimate more accurate assessment of the long term hydrological impacts including groundwater with L-THIA, further researches about snowfall data in winter should be considered.

• 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.