• Journal of Korea Water Resources Association
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• v.37 no.5
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• pp.397-406
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• 2004

It is necessary to estimate the groundwater recharge rate properly to evaluate the reasonable development amount of groundwater in a specific site. A small basin in Wicheon River Basin located in the Province of Kyungsangbuk-Do is selected to calculate the groundwater recharge rate. Average annual groundwater recharge rates are calculated from 1992 to 1997 because wet and draught year are contained during this period. In the calculation, baseflow separation method and SCS-CN method are applied to this area. As a result of estimation by baseflow separation method, the value of groundwater recharge ratio is varied between 11.9% and 18.7%. The average annual recharge rate is 14.5%. The average annual recharge rate calculated by SCS-CN method is varied between 7.9% and 20.9%. The average annual recharge rate in the calculation period is 15.1%. The results show that the average annual recharge amount from infiltration in the study basin is 141.6mm and 147.4mm in each estimation method. It appears that the average annual recharge amount calculated for the long period containing wet and draught year by the two methods is useful for groundwater development.

• 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 the Korean Association of Geographic Information Studies
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• v.8 no.2
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• pp.125-135
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• 2005

Generation and transport of nonpoint source pollution, especially sediment-associated pollutants, are profoundly influenced by hydrologic features of runoff. In order to identify pollutant export rates, hence, clear knowledge of rainfall-runoff relationship is a pre-requisition. In this study, performance of AnnAGNPS model was assessed based on the ability of the model to predict rainfall-runoff relationship. Three catchments, each under different nearly single land use, were simulated. From the results, it was found that the model was likely to produce better predictions for larger catchments than smaller catchments. Because of using the daily time scale, the model could not account for short durations less than 24 hours, especially high intensity events with multiple peak flow that significantly contribute to the generation and transport of pollutants. Since CN information for regional areas has not been built up, a careful selection of CN is needed to achieve accurate prediction of runoff volume. Storm distribution also found to be considered as an important calibration parameter for the hydrologic simulation.

• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1261-1271
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• 2018

This study evaluates the applicability of the classification rule of hydrological soil group proposed by Lee et al. (2018) with its application to three river basins (Jungmuncheon, Cheonmicheon, and Hancheon) in Jeju Island. The CN values are estimated as results of this application to these three basins, which is then compared with those estimated by applying the conventional three methods. Additionally, previous studies related with the classification of soil groups of Jesu Island, such as the infiltration and rainfall-runoff analysis, are reviewed to evaluate how the resulting hydrological soil groups vary depending on the adopted classification method.. Summarizing the results is as follows. (1) Comparison result of the hydrological soil groups of Jeju Island with respect to the classification method shows that the soil group B is dominant in the application of Lee et al. (2018). However, it is hydrological soil groups C and D in the application of Hu and Jung (1987), hydrological soil groups A and C in the application of Jung et al. (1995), and hydrological soil group D in the application of RDA (2007). (2) In all the applications of Lee et al. (2018) to three selected river basins in Jeju Island, the CN valuse are found to be smaller than those by other conventional three methods.. Lastly, (3) The evaluation results of previous studies related with the classification of hydrological soil groups analysis in Jeju Island shows that the CN value in the Jeju Island may be smaller than those estimated by conventional three methods, also the initial loss higher than 0.2S.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1909-1913
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• 2008

수자원의 공급적인 측면에서 내륙지역에 비하여 불리한 도서지역은 단기간의 가뭄에도 생활용수가 고갈되어 매년 상습적인 식수난을 겪고 있는 상태이다. 전국 3,170개 섬 중 491개 유인도에 831,295명(2003년)이 거주하고 있으나 상수도 보급률은 28.7%에 불과하다(환경부, 2005). 나머지 71.3%의 도서지역 주민들은 간이 급수시설, 우물, 지붕수 등을 생활용수로 이용하고 있다. 이와같이 도서지역은 상수도 보급율이 열악하여 지하수자원에 대한 의존도가 내륙지역에 비하여 높아 지하수자원을 통해 부족한 용수를 공급받아야 할 실정이다. 용수공급을 위한 지하수의 개발을 위해서 무엇보다 선행되어야 할 것은 도서지역의 지하수개발가능량 평가이며 이의 평가를 위해서는 지하수함양량의 파악이 이루어져야 한다. 지하수함양량 산정 기법 중 하나인 NRCS-CN방법은 선행강우조건, 토지피복상태, 수문학적 토양군 등의 인자들에 의해 산정되어진다. 수문학적 토양군의 경우 대부분의 연구에서 정정화 등 (1995)에 의해 분류된 자료가 이용되고 있었으나 최근 정광호 등(2007)에 의하여 수문학적 토양군이 재분류 되었다. 본 연구에서는 NRCS-CN방법을 이용하여 식수난에 어려움을 겪고 있는 우리나라 서남해안의 14개 도서지역에 대하여 수문학적 토양군의 1995년 분류와 2007년 분류를 적용하여 지하수함양량을 산정하고 비교하였다. 1995년 분류와 2007년 분류에서 지하수함양량과 함양률은 개도, 생일도, 보길도를 제외한 도서지역은 1%미만의 차이로 변화가 거의 없는 것으로 나타났다. 개도, 생일도, 보길도는 1995년 분류에 비하여 2007년 분류에서 $2.2%{\sim}2.8%$ 감소하였다. 따라서 대상지역의 수문학적토양군의 재분류에 의한 지하수함양량 및 함양률의 차이가 미미함을 알 수 있었다. 연평균 함양량은 1995년 분류와 2007년 분류에서 수도가 590.8mm, 583.5mm로 최대값을 가지며 가파도가 270.2mm, 270.5mm로 최소값을 가지는 것으로 나타났다. 함양률의 경우 1995년 분류에서는 개도가 29.8%의 최대값을 나타내었고 가파도가 23.3%의 최소값을 가지는 것으로 나타났으며 2007년 분류에서는 사량도 상도가 28.5%의 최대값을 나타내었고 가파도가 23.3%의 최소값으로나타났다.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.2
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• pp.1-15
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• 2004

For the simulation of flow phenomenon that calculate basin outflow, it is required to estimate effective precipitation which contributes to direct runoff. This paper is focused on using detailed soil map which is one of the data required to estimate effective precipitation by SCS CN method. Korean detailed soil map must be reclassified as SCS hydrologic soil group when it is applied to SCS CN method. In this study, Korean detailed soil maps which are reclassified as SCS hydrologic soil group by the methods of Her and Jung (1987) and Jung et al. (1995) are applied to flow simulation and the results are analyzed. The study sites are Wichon watershed and Pyungchang river basin which are studied by International Hydrological Program(IHP). HEC-1 and WMS v6.1 are used to simulate flow phenomenon and calculate geographic parameters. The difference of flow analysis results from each soil reclassification method is different from each sites. But the results of flow analysis approximate observed data by using Jung et al. (1995) method more than Her and Jung (1987) method.

• Journal of Environmental Science International
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• v.15 no.3
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• pp.253-260
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• 2006

Groundwater recharge from precipitation is affected by the infiltration from ground surface and the movement of soil water. Groundwater recharge is directly related to the groundwater amount and flow in aquifers, and baseflow to rivers. Determining groundwater recharge rate for a given watershed is a prerequisite to estimate sustainable groundwater resources. The estimation of groundwater recharge rate were carried out for three subwatersheds in the Wicheon watershed and two subwatersheds in the Pyungchang River basin and for the period 1990-2000, using the NRCS-CN method and the baseflow separation method. The recharge rate estimates were compared to each other. The result of estimation by the NRCS-CN method shows the average annual recharge rate 15.4-17.0% in the Wicheon watershed and 26.4-26.8% in the Pyungchang River basin. The average annual recharge rates calculated by the baseflow separation method ranged 15.1-21.1% in the W icheon watershed, and 25.2-33.4% in the Pyungchang River basin. The average annual recharge rates calculated by the NRCS-CN method is less variable than the baseflow separation method. However, the average annual recharge rates obtained from the two methods are not very different, except NO. 6 subwatershed in Pyungchang River basin.

• Journal of Environmental Science International
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• v.13 no.12
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• pp.1033-1039
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• 2004

The methodology developed by Soil Conservation Service for determination of runoff value from precipitation is applied to estimate the precipitation recharge in the Pyungchang river basin. Two small areas of the basin are selected for this study. The CN values are determined by considering the type of soil, soil cover and land use with the digital map of 1:25,000. Forest covers more than $94{\%}$ of the study area.. The CN values for the study area vary between 47 in the forest area and 94 in the bare soil under AMC 2 condition. The precipitation recharge rate is calculated for the year when the precipitation data is available since 1990. To obtain the infiltration rate, the index of CN and five day antecedent moisture conditions are applied to each precipitation event during the study period. As a result of estimation, the value of precipitation recharge ratio in the study area vary between $15.2{\%}\;and\;35.7{\%}$ for the total precipitation of the year. The average annual precipitation recharge rate is $26.4{\%}\;and\;26.8{\%}$, meaning 377.9mm/year and 397.5mm/year in each basin.

• 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.

• Journal of Korea Water Resources Association
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• v.49 no.5
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• pp.373-380
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• 2016

The NRCS-CN (Natural Resources Conservation Service-Curve Number) method has been practically applied for estimating the effective precipitation. However, there are no criteria which reflect the geographic characteristics of Korea having more than 70% of mountainous and rice paddy areas, leading to significant errors in runoff calculation. Thus, it is required to estimate the runoff curve number considered Korea land use classification, however there are practical difficulties to conduct the accurate research and experimentation. In this study, after selecting target areas (urban, agriculture, forest), we performed the runoff analysis to redetermine CN values for the selected basins. To do this, curve numbers for soil type A were estimated using genetic algorithm, and then curve numbers for soil type (B, C, D) were estimated using CN aligner equation. Comparing the initial curve numbers with the estimated curve numbers, it was observed that the slightly differences at Chunwang(0), Choonyang(-1), Janggi(-3). Through the above process, this study proposed new curve numbers to reflect observed rainfall-runoff.