• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.157-157
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• 2019

This study derived the Flood-Inducing-Rainfall (FIR) and the Flood-Inducing-Runoff (FIRO) from the radar-gage composite data to be used as the basis of the flood warning initiation for the urban area of Seoul. For this, we derived the rainfall depth-duration relationship for the 261 flood events at 239 watersheds during the years 2010 and 2011 based on the 10-minute 1km-1km radar-gauge composite rainfall field. The relationship was further refined by the discrete ranges of the proportion of the flooded area in the watershed (FP) and the coefficient variation of the rainfall time series (CV). Then, the slope of the straight line that contains all data points in the depth-duration relationship plot was determined as the FIR for the specified range of the FP and the CV. Similar methodology was applied to derive the FIRO, which used the runoff depths that were estimated using the NRCS Curve Number method. We found that FIR and FIRO vary at the range of 37mm/hr-63mm/hr and the range of 10mm/hr-42mm/hr, respectively. The large variability was well explained by the FP and the CV: As the FP increases, FIR and FIRO increased too, suggesting that the greater rainfall causes larger flooded area; as the rainfall CV increases, FIR and FIRO decreased, which suggests that the temporally concentrated rainfall requires less total of rainfall to cause the flood in the area. We verified our result against the 21 flood events that occurred for the period of 2012 through 2015 for the same study area. When the 5 percent of the flooded area was tolerated, the ratio of hit-and-miss of the warning system based on the rainfall was 44.2 percent and 9.5 percent, respectively. The ratio of hit-and-miss of the warning system based on the runoff was 67 percent and 4.7 percent, respectively. Lastly, we showed the importance of considering the radar-gauge composite rainfall data as well as rainfall and runoff temporal variability in flood warning system by comparing our results to the ones based on the gauge-only or radar-only rainfall data and to the one that does not account for the temporal variability.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.37-37
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• 2022

유효우량 산정을 위하여 국내에서 주로 사용되는 모형은 NRCS-CN(Natural Resources Conservation Service - curve number) 모형으로, 유역의 유출 능력을 나타내는 유출곡선지수(runoff curve number, CN)와 같은 NRCS-CN 모형의 매개변수들은 관측 강우-유출자료 또는 토양도, 토지피복지도 등을 이용하여 유역마다 결정된 값이 사용되고 있다. 그러나 유역의 CN값은 유역의 토양 상태와 같은 환경적 조건에 따라 달라질 수 있으며, 이를 반영하기 위하여 선행토양함수조건(antecedent moisture condition, AMC)을 이용하여 CN값을 조정하는 방법이 사용되고 있으나, AMC 조건에 따른 CN 값의 갑작스런 변화는 유출량의 극단적인 변화를 가져올 수 있다. NRCS-CN 모형과 더불어 강우 손실량 산정에 많이 사용되는 모형으로 Green-Ampt 모형이 있다. Green-Ampt 모형은 유역에서 발생하는 침투현상의 물리적 과정을 고려하는 모형이라는 장점이 있으나, 모형에 활용되는 다양한 물리적인 매개변수들을 산정하기 위해서는 유역에 대한 많은 조사가 선행되어야 한다. 또한 이렇게 산정된 매개변수들은 유역 내 토양이나 식생 조건 등에 따른 여러 불확실성을 내포하고 있어 실무적용에 어려움이 있다. 따라서 본 연구에서는, 현재 사용되고 있는 강우손실 모형들의 매개변수를 추정하기 위한 방법을 제시하고자 하였다. 본 연구에서 제시하는 방법은 인공지능(AI) 기술 중 하나인 딥러닝(deep-learning) 기법을 기반으로 하고 있으며, 딥러닝 모형으로는 장단기 메모리(Long Short-Term Memory, LSTM) 모형이 활용되었다. 딥러닝 모형의 입력 데이터는 유역에서의 강우특성이나 토양수분, 증발산, 식생 특성들을 나타내는 인자이며, 모의 결과는 유역에서 발생한 총 유출량으로 강우손실 모형들의 매개변수 값들은 이들을 활용하여 도출될 수 있다. 산정된 매개변수 값들을 강우손실 모형에 적용하여 실제 유역들에서의 유효우량 산정에 활용해보았으며, 동역학파 기반의 강우-유출 모형을 사용하여 유출을 예측해보았다. 예측된 유출수문곡선을 관측 자료와 비교 시 NSE=0.5 이상으로 산정되어 유출이 적절히 예측되었음을 확인했다.

• Journal of Wetlands Research
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• v.26 no.1
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• pp.1-9
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• 2024

In this study, a HSPF model was developed to simulate runoff and water quality in the Haebancheon watershed, which has a high land area ratio and population density among the West Nakdong River watersheds. Various non-point source pollution control strategies were applied, and the reduction in pollutant loads and the exceedance rate of water quality standards were analyzed. The scenarios included basic road cleaning for reducing pollutant loads, runoff reduction measures considering extensive low-impact development techniques, and inflow reduction measures to mitigate non-point source pollution entering the river. In the first step, practical conditions such as the number of vehicles for road cleaning in Kimhae City were considered, while for the second and third steps, it was assumed that 50% of the applicable land use area was used to be applicable for the LID techniques. As a result of applying all three measures, it was analyzed that the BOD pollutant load could be reduced by 58.28%, T-N by 58.49%, and T-P by 51.56%. Furthermore, the 60th percentile of water quality measurements accumulated over 5 years was set as the target water quality, and a flow-duration curve was constructed. The exceedance rate of the flow-duration curve before and after applying non-point source pollution reduction measures was analyzed. As a result, for BOD, the exceedance rate decreased from 41.57% before applying the measures to 16.32% after, showing a 25.25% reduction in the exceedance rate. For T-N, the exceedance rate decreased significantly from 40.31% before the measures to 22.84% after, and for T-P, it decreased significantly from 62.43% to 27.22%.

• Journal of Soil and Groundwater Environment
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• v.11 no.1
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• pp.65-76
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• 2006

This paper outlines the methodology of grid-based water balance for estimating the spatial distribution of recharge, which is applied to Woedo catchment in the northern area of the Jeju Island. The catchment is divided into grids and a daily water balance in each grid is computed for the period of 5 years. Daily rainfall data in each grid is interpolated from the data of 10 rainfall gauging stations. The spatial distributions of parameters such as SCS curve number, soil water retention capacity and crop coefficients are derived from GIS analyses of soil and land use characteristics. The SCS curve number is obtained by calibrating simulated runoffs with respect to the observed runoffs. The results show that the average annual rainfall increases from 1,665 mm/year to 3,382 mm/year in accordance with the topographic elevation, and the average annual recharge varies from 372 mm/year to 2,576 mm/year according to the average annual rainfall increases. Spatial variability of recharge is the highest among the water balance components such as rainfall, direct runoff, evaprotranspiration and recharge because the rate of runoff and evapotranspiration in the area with relatively low rainfall is higher than the other area.

• Korean Journal of Environmental Agriculture
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• v.20 no.3
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• pp.192-200
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• 2001

The event-based agricultural non-point source(AGNPS) pollution model was applied to estimate the loads of nitrogen and phosphorus in a stream draining small agricultural watersheds. Calibration and verification of the model were performed using observed data collected from rainfall events in the Imgo watersheds during 1997-1998. Parameter calibrations were made for the runoff curve number. The peak flow volumes in the watersheds were well reproduced by the modified model. Average deviation between observed and simulated values was 10%, and this match was confirmed by the coefficient of efficiency value of 0.97. The deviations tended to increase as the peak flows increased. The simulated total N concentrations in the stream water were fairly close to the measured values, and the coefficient of efficiency in the estimation was 0.93. However, there were relatively large variations between calculated and observed values of total P concentration, and the coefficient of efficiency in the estimation was 0.74. Any inaccuracies that arise in estimating runoff flow and nutrient loading can not be explained exactly and further adjustment and refinements may be needed for application of AGNPS in agricultural watersheds. With this restrictions in mind, it can be concluded that AGNPS can provide realistic estimates of nonpoint source nutrient yields.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.587-596
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• 2014

Soil moisture is one of the most important interests in hydrological response and the interaction between the land surface and atmosphere. Estimation of Antecedent Wetness Conditions (AWC) which is soil moisture condition prior to a rainfall in the basin should be considered for rainfall-runoff prediction. In this study, Soil Wetness Index (SWI), Antecedent Precipitation Index ($API_5$), remotely sensed Soil Moisture ($SM_{rs}$), and 5 days ground Soil Moisture ($SM_{g5}$) were selected to estimate the AWC at four study area in the Korean Peninsula. The remotely sensed soil moisture data were taken from the AMSR-E soil moisture archive. The maximum potential retention ($S_{obs}$) was obtained from direct runoff and rainfall using Soil Conservation Service-Curve Number (SCS-CN) method by rainfall data of 2011 for each study area. Results showed the great correlations between the maximum potential retention and SWI with a mean correlation coefficient which is equal to -0.73. The results of time length representing the time scale of soil moisture showed a gap from region to region. It was due to the differences of soil types and the characteristics of study area. Since the remotely sensed soil moisture has been proved as reasonable hydrological variables to predict a wetness in the basin, it should be continuously monitored.

• Journal of Environmental Impact Assessment
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• v.19 no.1
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• pp.49-57
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• 2010

The objective of the research is to analyze changing trend of water discharge in precipitation, according to changing land use, through an environment-friendly urban development method called LID. The study chose S1 basin (Separated Sewer districts) in Cheongju region for survey. Among LID methods, relatively more applicable methods of green rooftop space and parking lot with permeable material were selected to construct plausible scenarios. Curve Number (CN) value was calculated due to land use patterns in each scenario, and SWMM model simulation were conducted during 2008 for comparative analysis. For Case 1, only parking lot with permeable material was applied to the scenario. Green rooftop space I and II were applied to Case 2 and 3 respectively. For Case 4 and 5, green rooftop space I and II were applied, in addition to parking lot with permeable material, Calculation of CN value showed that for S1 basin, the value was 88.1 (prior to scenario application), 86.5 (Case 1), 81.9 (Case 2), 68.5 (Case 3), 80.4 (Case 4) and 67.2 (Case 5). Changing pattern of rain water discharge was analyzed for each scenario. For Case 1, the change was not remarkable before and after application of scenario. In Case 2 and 4, the impact of rain water discharge as source of pollutant fell to 20~30%. The rate dropped to 30~50% in Case 3 and 5 respectively. The result demonstrates that the amount of rain water discharge, amount and frequency of sewer overflow, frequency of rain water discharge, and pollution load decreased in accordance with declining CN value in each scenario. In installing green rooftop space, the effect was twice greater when rain water discharge was directly infiltrated into soil.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.1-12
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• 2012

The agricultural area was classified into dry and paddy fields in this study using the near-infrared band of Landsat TM to extract land cover classes that need to the application of Expected Mean Concentration (EMC) in nonpoint source works. The accuracy of image classification of the land cover map from Landsat TM image showed 83.61% and 78.41% respectively by comparing with the large and middle scale land cover map of Ministry of Environment. As the result of Soil Conservation Service (SCS) Curve Number (CN) using the land cover map from image classification, Dongbok dam and Dongbok stream basin were analyzed high. Also Geymbaek water-gage and Bosunggang upstream basin showed high in the analysis of EMC of BOD, TN, TP by basin. And also Geymbaek water-gage and Bosunggang upstream basin showed high in the analysis of non-point source through coupling with direct runoff. Therefore these basins were selected with the main area for the management of nonpoint source.

• 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.

• Journal of Korea Water Resources Association
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• v.50 no.10
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• pp.653-660
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• 2017

The SCS-CN (Soil Conservation Service-Curve Number) method has been practically applied for estimating the effective precipitation. The CN is used to be determined according to the land use condition based on the US standard. However, there are two distinctive differences between U.S. and Korean land use conditions: mountainous (forest) and rice paddy area that cover more than 70% of the Korean territory. The previous work proposed to use 79 for rice paddy area, regardless of the soil type. Because US SCS's goal was originally to increase crops, the SCS classification standard provides only for woods and there are no criteria to distinguish the wood and forest. To determine the CN for forest, alternatively the U.S. Forest Service criteria have been employed in practice considering hydrologic condition class. In this study, we investigated the change of the forest CN using the observed rainfall - runoff data within the target area. The results indicated that the CN for forest was suitable for HC=1, and the corresponding CNs were redetermined between 54 and 55.