• Journal of Korea Water Resources Association
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• v.31 no.2
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• pp.167-176
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• 1998

On steep hillslopes, saturation zone formations and subsurface flows were monitored through the observation systems of observation wells, tensiometers and trenches. By the 103 mm rain which had fallen on the hillslope with dry soil moisture, the saturation zone began to be formed at the top of hillslope during the rain and developed to be formed within a few hours after the end of rain on all hillslope. Subsurface water outflowed mainly from the soil profile of 0-40 cm depth, but did not outflow from the one of 40-80 cm depth. This saturation zone seemed to be formed by partially saturation of soil. This resulted for two reasons. Firstly, the saturation zone was formed by a smaller amount of rain than that required. Secondly the soil at a certain depth below the water table was unsaturated. Saturation zones formed by pre-rains responded rapidly to rains and subsurface water outflowed mainly from the soil profile of 40-80 cm depth simultaneously with the rising of the water level. The rates of subsurface discharge from the soil profile of 40-80 cm depth to the precipitation were related to the antecedent precipitation although the maximum water levels of saturation zone formed by four rains were similar.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.749-754
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• 2005

본 연구에서는 한 개의 침투 조절 요소, 두 개의 직렬탱크 및 한 개의 병렬 탱크로 구성된 개선된 형태의 TANK 모형을 제시하였다. 침투는 강우의 형태로 유역에 공급되는 물의 분배를 결정하는 과정으로서, 이를 적절히 고려할 수 있는지의 여부가 강우-유출 모형의 유효성을 판단하는 기준이 된다고 해도 과언이 아니다. 따라서 본 연구에서는 구조가 비교적 단순하고 사용이 간편하여 기존에 널리 사용되어 오던 개념적 모형인 TANK 모형에 침투 조절 요소를 도입하여 보다 합리적으로 강우-침투-유출 과정을 모의하고 해석하고자 노력하였다. 이를 통해 단순히 시간의 함수가 아닌 토양 함수량의 함수로서 침투능의 변화를 고려할 수 있으며, 유역 유출의 각 성분(지표면 유출, 중간 유출, 지하수 유출)에 영향을 미치는 모형의 매개변수에 물리적 의미를 더욱 부여할 수 있다. 또한 침투 조절 요소의 매개변수 산정을 위해 선행 강우 지수(Antecedent Precipitation Index)를 이용하였으며, 이를 통해 토양 선행 함수 상태의 고려가 가능하다. 또한 본 연구에서는 모형의 매개변수 최적화를 위해 실수 코딩 유전 알고리즘(Real Coded Genetic Algorithm)을 사용하였으며, 모형의 적용성과 유효성 검증을 위해 IHP 연구 유역인 평창강 방림 유역을 대상유역으로 하여 이 유역의 실측 호우 사상을 사용하였다. 결과적으로 계산된 수문곡선은 관측치에 비교적 잘 일치하며, 단일 호우와 복합 호우 사상 모두에 대해 비교적 양호한 결과를 나타내었다.

• The Journal of Engineering Geology
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• v.24 no.4
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• pp.463-471
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• 2014

This paper considers the effect of rainfall on non-point source (NPS) pollutant loads. The impact of runoff on the occurrence of NPS pollutants was found to be influenced by rainfall amount, rainfall intensity, and the number of antecedent dry days (ADD), both independently and in combination. The close correlation ($R^2$ = 0.9920) between rainfall and runoff amounts was demonstrated at the study site (a flower farm) over the period between January 2011 and December 2013. The relationships among pollutant levels, runoff, and rainfall was not satisfactory results except for the Biochemical Oxygen Demand ($BOD_5$). The correlation coefficients between $BOD_5$, and both runoff and rainfall, were greater than 0.92. However, the relationships of other pollutants, such as Suspended Solid (SS), Chemical Oxygen Demand ($COD_{Mn}$), Total Nitrogen (TN), and Total Phosphorus (TP), with runoff and rainfall had correlation coefficients of less than 0.70. The roles of rainfall was different from rainfall categories on the occurrence of runoff. Instantaneous rainfall intensity was a principle factor on the occurrence of runoff following light rainfall events (total ${\leq}30mm$). For rainfall of intermediate intensity (total precipitation 31-50 mm), the combined effect of both average rainfall intensity and ADD was found to influence runoff generation. We conclude that the control of NPS pollutants with the reflection of the climate change that makes the remarkable effect of amounts and forms on the rainfall and runoff.

• Journal of Korean Society on Water Environment
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• v.30 no.1
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• pp.8-15
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• 2014

In this study, regression equation was analyzed to estimate non-point source (NPS) pollutant loads in orchard area. Many factors affecting the runoff of NPS pollutant as precipitation, storm duration time, antecedent dry weather period, total runoff density, average storm intensity and average runoff intensity were used as independent variables, NPS pollutant was used as a dependent variable to estimate multiple regression equation. Based on the real measurement data from 2008 to 2012, we performed correlation analysis among the environmental variables related to the rainfall NPS pollutant runoff. Significance test was confirmed that T-P ($R^2=0.89$) and BOD ($R^2=0.79$) showed the highest similarity with the estimated regression equations according to the NPS pollutant followed by SS and T-N with good similarity ($R^2$ >0.5). In the case of regression equation to estimate the NPS pollutant loads, regression equations of multiplied independent variables by exponential function and the logarithmic function model represented optimum with the experimented value.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.6
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• pp.177-186
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• 2013

The purpose of this study was to analyze the temporal and spatial characteristics of the stream flow of small rural streams for investigating the status of stream depletion located downstream of irrigation reservoir. Bonghyun and Hai reservoirs and each downstream were selected for this study. Streamflow was measured for 8 stations downstream from two reservoirs from 2010 to 2012. The water quality samples were collected monthly from the 8 stream stations and 2 reservoir stations from 2011 to 2012. The stream depletion was found in most of the downstream of reservoirs for the non-irrigation period and even in the irrigation period when there were a lot of antecedent precipitation. We found that the stream segments where there were few streamflow, vegetation covers the stream and block the streamflow which makes the stream lost its original function as a stream. Water quality monitoring results of Bonghyun stream indicated that the concentration of SS, Turbidity, TOC, COD were decreased as the stream flows from the reservoir to downstream while the TN and TP were increased. The correlation analysis for water quality data indicated that the correlation between T-N and T-P was high for Bonghyeon and Sukji streams, respectively. Continuous monitoring for rural streams located in downstream of reservoirs are required to quantify the status of stream flow depletion and determine the amount of environmental flows.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1289-1292
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• 2010

용수부족 현상을 극복하기 위하여 댐건설 등의 생태계의 교란을 일으키는 방안을 배제하고 친생태적인 우수이용 등의 대체수자원을 개발하여 수자원 이용효율을 높이는 방안이 중요시 되고 있다. 이에 본 연구에서는 초기우수의 수질특성과 대기의 상태에 크게 영향을 미치는 수문학적 요인인 선행강우에 따른 수질변화에 대하여 분석하였다. 시료채취기간은 2001년 11월 22일에서 2003월 7월 06일까지 발생한 5mm 이상 호우사상을 대상으로 26회 에 걸쳐 초기 우수를 채집하여 분석을 실시하였으며, 이 중 봄 12회, 여름 7회, 가을 2회, 겨울 5회였다. 강우량 규모는 5~10mm인 호우가 5회, 10~20mm인 호우가 9회, 20mm~30mm인 호우가 5회, 30mm~50mm 인 호우가 2회, 50mm~100mm인 호우가 3회, 100mm~200mm인 호우가 2회였으며, 이를 채취하여 탁도, 증발잔유물, BOD, NH3-N, ${SO_4}^{-2}$, 전기 전도도 등의 항목을 측정하였다. 우수수질은 강우가 지속됨에 따라 급격히 개선되었으며, 이에 대한 상관관계도 높게 분석되었다.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.117-117
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• 2021

본 연구에서는 Sentinel-1A/B C-band SAR(Synthetic Aperture Radar) 위성영상을 기반으로 인공신경망(Artificial Neural Network, ANN) 모형을 활용해 금강 유역 상류 40×50 km² 면적에 대한 토양수분을 산정하였다. 10 m 공간 해상도의 Sentinel-1A/B SAR 영상은 8일 간격으로 2015년부터 2019년까지 5년 동안 구축하였고, SNAP(SentiNel Application Platform)을 통해 기하 보정, 방사 보정 및 잡음(Noise) 보정을 수행하고 VV 및 VH 편파 후방산란계수로 변환하였다. ANN 모형 검증자료로 TDR(Time Domain Reflectometry)로 측정된 9개 지점의 실측 토양수분 자료를 구축하였으며, 수문학적 개념인 선행강우를 고려하기 위해 동지점에 대한 강수량 자료를 구축하였다. ANN은 각 지점에 해당하는 토양 속성별로 모델링하고, 전체 기간 및 계절별로 나누어 모의하였으며, 전체 자료의 60%와 40%를 각각 훈련 및 테스트 데이터로 사용하였다. 산정된 토양수분은 상관계수(Correlation Coefficient, R)와 평균제곱근오차(Root Mean Square Error, RMSE)를 활용하여 검증을 수행할 예정이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.147-147
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• 2022

In January 2021 heavy flood affected South Kalimantan with causing many casualties. The heavy rainfall is predicted to be generated due to the ENSO (El Nino-Southern Oscillation). The weak La-Nina mode appeared to generate more convective cloud above the warmed ocean and result in extreme rainfall with high anomaly compared to past historical rainfall event. Subsequently, the antecedent soil moisture distribution showed to have an important role in generating the flood response. Saturated flow and infiltration excess mainly contributed to the runoff generation due to the high moisture capacity. The hydro-meteorological processes in this event were deeply analyzed using the coupled atmospheric model of Weather Research and Forecasting (WRF) and the hydrological model extension (WRF-Hydro). The sensitivity analysis of the flood response to the SST anomaly and the soil moisture capacity also compared. Result showed that although SST and soil moisture are the main contributors, soil moisture have more significant contribution to the runoff generation despite of anomaly rainfall occurred. Model performance was validated using the Global Precipitation Measurement (GPM) and Soil Moisture Operational Products System (SMOPS) and performed reasonably well. The model was able to capture the hydro-meteorological process of atmosphere and hydrological feedbacks in the extreme weather event.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.515-530
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• 2021

This study is to estimate soil moisture (SM) using Sentinel-1A/B C-band SAR (synthetic aperture radar) images and Multiple Linear Regression Model(MLRM) in the Yongdam-Dam watershed of South Korea. Both the Sentinel-1A and -1B images (6 days interval and 10 m resolution) were collected for 5 years from 2015 to 2019. The geometric, radiometric, and noise corrections were performed using the SNAP (SentiNel Application Platform) software and converted to backscattering coefficient of VV and VH polarization. The in-situ SM data measured at 6 locations using TDR were used to validate the estimated SM results. The 5 days antecedent precipitation data were also collected to overcome the estimation difficulty for the vegetated area not reaching the ground. The MLRM modeling was performed using yearly data and seasonal data set, and correlation analysis was performed according to the number of the independent variable. The estimated SM was verified with observed SM using the coefficient of determination (R²) and the root mean square error (RMSE). As a result of SM modeling using only BSC in the grass area, R² was 0.13 and RMSE was 4.83%. When 5 days of antecedent precipitation data was used, R² was 0.37 and RMSE was 4.11%. With the use of dry days and seasonal regression equation to reflect the decrease pattern and seasonal variability of SM, the correlation increased significantly with R² of 0.69 and RMSE of 2.88%.

• Journal of the Korean Society of Industry Convergence
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• v.11 no.1
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• pp.11-18
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• 2008

After execute quantitative analysis that choose station and compose floodgate quality of water net and use floodgate data and quality of water data analysis target Sign of the cock as 1 dimension access for Non-point pollution source pollution and estimate of Gaeuncheon's at Kyongsangbukdo report to the Throne in this research, presented parameter conclusion notation model (AGNPS) in real condition of our agricultural area through comparison with spot value and result is as following in reply. With result observation and analysis result of the AGNPS model the comparison which it will pay from the hazard which it analyzes 2005, the rainfall thought which is used in the analysis to select 8 heavy rain thoughts 2005 July - is data until of September. Actual amount of rainfall 6.0~195.0 mm one time the antecedent precipitation showed API5 case 0.0~507.0mm and were observed peak flows (Qpeak) each from the P-1 $0.026m^3/sec{\sim}9.265m^3/sec$, from the P-2 $0.010m^3/sec-2.747m^3/sec$ and from the P-3c $0.064m^3/sec-13.482m^3/sec$ to show. Also amendment AMC condition it will be cool and it uses and the AGNPS model conference the result which it occurs, analysis and regression analysis of actual flow for as 0.992 very the possibility of getting the result which is good there was a decisive coefficient which is cool. But the gun is (T-P) with the total nitrogen (T-N) decisive coefficient each as 0.794 and 0.849 the presumption which is reliability generally will pay and with the fact that it will be the possibility of getting it is judged.