• Title/Summary/Keyword: Antecedent moisture condition

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A Study on the Variation of the Critical Duration According to Hydrologic Characteristics in Urban Area (도시유역에서 수문학적 특성에 따른 임계지속기간의 변화 연구)

  • Lee, Jung-Sik;Shin, Chang-Dong
    • Journal of the Korean Society of Hazard Mitigation
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    • v.5 no.3 s.18
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    • pp.29-39
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    • 2005
  • The objective of this study is to analyze the relation of critical duration according to hydrologic characteristics in urban areas. RRL, ILLUDAS, SWMM, and SMADA urban runoff models were applied to the Seongnae and Banpo watershed and experiment area of the Dong-Eui University. Also, hydrologic characteristics such as temporal pattern of rainfall, rainfall intensity formula, antecedent moisture condition, return period, and urban runoff model were used to simulate the critical duration of the test areas. The results of this study are as follows; (1) The type of temporal pattern of rainfall which causes maximum peak discharge in urban area has resulted in Huff's 4th quartile distribution. (2) The critical duration in urban areas were not influenced by hydrological factors except urban runoff model. (3) Peak discharge and critical duration in urban areas were influenced by the urban runoff model, and the SWMM model using Huff's 4th quartile distribution shows maximum critical duration.

Revised AMC for the Application of SCS Method: 1. Review of SCS Method and Problems in Its Application (SCS 방법 적용을 위한 선행토양함수조건의 재설정: 1. SCS 방법 검토 및 적용상 문제점)

  • Park, Cheong-Hoon;Yoo, Chul-Sang;Kim, Joong-Hoon
    • Journal of Korea Water Resources Association
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    • v.38 no.11
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    • pp.955-962
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    • 2005
  • Even though the runoff volume is very sensitive to the antecedent soil moisture condition (AMC), the general rainfall-runoff analysis in Korea has accepted, without careful consideration of its applicability, the AMC classification of the Soil Conservation Service (SCS, 1972). In this study, by following the development procedure of SCS Curve Number (CN), the rainfall-runoff characteristics of the Jangpyung subbasin of the Pyungchang River Basin were analyzed to estimate the CN and evaluate the AMC classification of currently being used. As results, CN(I), CN(II), and CN(III) were estimated to be 72.1, 79.3, and 76.7, respectively. Among them CN(II) was found to be similar to the other reports but the other two were totally different from those of theoretically estimated. However, it is difficult to evaluate the AMC with CN, rather the frequency of each AMC could be a better indicator for its validity. This study developed the histogram of AMC and compared the frequency of each AMC. hs results we found that the criterion for AMC-III should be increased, Hut that for AMC-I decreased.

Parameter Estimation of Vflo$^{TM}$ Distributed Rainfall-Runoff Model by Areal Average Rainfall Calculation Methods - For Dongchon Watershed of Geumho River - (유역 평균 강우량 산정방법에 따른 Vflo$^{TM}$ 분포형 강우-유출 모형의 매개변수 평가 - 금호강 동촌 유역을 대상으로 -)

  • Kim, Si-Soo;Park, Jong-Yoon;Kim, Seong-Joon;Kim, Chi-Young;Jung, Sung-Won
    • Proceedings of the Korea Water Resources Association Conference
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    • 2012.05a
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    • pp.879-879
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    • 2012
  • 강우현상의 공간적 변동성에 대한 해석은 수자원 계획 및 관리를 위해 중요한 관심사가 되고 있다. 일반적으로 우리가 얻을 수 있는 강우자료는 한 지점에 설치되어 있는 우량계에 의한 관측된 지점강우량자료이다. 기존의 집중형 수문모형이 유출과정의 공간적인 분포 및 변화를 유역단위로 평균화해서 취급하는 개념기반의 모형임에 반해서 분포형 수문모형은 유역을 수문학적으로 균일한 매개변수를 갖는 소유역 또는 격자망으로 구분하여 적용하는 것으로, 도시화 등 토지이용의 변화나 기타 유역내의 물리적인 특성의 변화가 수문과정에 미치는 영향을 잘 모의할 수 있다. 따라서 본 연구에서는 Vflo$^{TM}$ 분포형 강우-유출 모형과 IDW, Ordinary Kriging, Thiessen 등의 강우 분포 기법을 이용하여 낙동강 제 1지류인 금호강의 동촌 수위관측소 유역($1,544km^2$)을 출구로 하여 강우-유출모의를 하였다. 이를 위하여 강우-유출에 영향을 주는 매개변수를 선정하고 동촌 수위관측소의 실측 유량자료를 바탕으로 하여 IDW, Kriging, Thiessen 등의 면적강우량 산정방법별로 모형의 보정(2007, 2009) 및 검증(2010)을 실시하였다. 모의 된 유출량과 실측유량의 상관성은 결정계수 $R^2$에서 IDW 과 Kriging의 경우 0.95 ~ 0.99의 상관성을 나타냈으며 Thiessen 의 경우 0.94 ~ 0.99의 값을 나타냈다. Nash-Sutcliffe 모형효율은 IDW의 경우 0.95 ~ 0.98, Kriging의 경우 0.94 ~ 0.99를 나타냈으며 Thiessen의 경우는 0.90 ~ 0.98의 모형효율을 나타내었다. 이때 포화투수계수와 조도계수가 전체 유량과 첨두시간에 영향을 주었다. 호우사상을 선정하여 검보정을 실시 한 결과, 유역의 유출 모의를 수행하였을 때 선행강우량에 따라서 토양의 침투능에 영향을 많이 주고 있기 때문에, 선행 토양함수조건(Antecedent Moisture Condition: AMC)으로 분류한 뒤에 AMC 조건에 따라서 유출-모의를 수행하는 것이 타당하다고 판단된다.

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Estimation of CN-based Infiltration and Baseflow for Effective Watershed Management (효과적인 유역관리를 위한 CN기법 기반의 침투량 산정 및 기저유출량 분석)

  • Kim, Heewon;Sin, Yeonju;Choi, Jungheon;Kang, Hyunwoo;Ryu, Jichul;Lim, Kyoungjae
    • 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.

Change of AMC due to Climatic Change (기후변화에 따른 선행토양함수조건(AMC)의 변화)

  • Yoo, Chulsang;Park, Cheong Hoon;Kim, Joong Hoon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.3B
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    • pp.233-240
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    • 2006
  • One of the main factor that effects on the CN's value in SCS Curve Number method for the estimation of direct runoff is the antecedent soil moisture condition (AMC). It is also common to use the AMC-III in hydrologic practice, which provides the largest runoff as possible. In this paper, AMC defending on the rainfall characteristics is analyzed using daily rainfall data at rainy season (June~September) of the Seoul station from 1961 to 2002. The probability mass function of AMC is also investigated to analyze the variation of AMC based on climate change, scenarios from several General Circulation Model (GCM) predictions. As a results we can find that the occurrence of AMC-I is reduced, and AMC-III is increased, whereas AMC-II does not change.

Prediction of rainfall abstraction based on deep learning considering watershed and rainfall characteristic factors (유역 및 강우 특성인자를 고려한 딥러닝 기반의 강우손실 예측)

  • Jeong, Minyeob;Kim, Dae-Hong;Kim, Seokgyun
    • 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.

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A Study on the Selection of AMC of Curve Number (유출곡선지수의 선행토양함수조건 선정 기준 연구)

  • Kim, Jee-Sang;Ahn, Jaehyun
    • Journal of Wetlands Research
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    • v.14 no.4
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    • pp.519-535
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    • 2012
  • In order to establish a rainfall-runoff model, calibration of hydrological parameters for the model is very important. Especially, Curve Number(CN), estimated by NRCS method, is a main factor to apply unit hydrograph theory to calculation of peak discharge. For using NRCS method, it is needed selecting AMC because CN is strongly connected with that. In this study, we focus our concern on finding a applicable standard for selecting AMC for CN. For this, three dams which are Boryeong, Habchon, Namgang are selected as target basins to use observed data including rainfall and dam inflow. As a result of this research, it is found that CN must be included as a calibrated parameter to calculate effective rainfall for the rainfall-runoff model. Also, it is preferred to use PWRMSE of HEC-HMS program as a objective function for optimizing hydrological parameters. From the analyzing result of variation of AMC for peak discharge, it is recommended to apply AMC-III to estimation of CN for calculating effective rainfall of design hydrograph.

The Effect of Slope-based Curve Number Adjustment on Direct Runoff Estimation by L-THIA (경사도에 따른 CN보정에 의한 L-THIA 직접유출 모의 영향 평가)

  • Kim, Jonggun;Lim, Kyoung Jae;Park, Younshik;Heo, Sunggu;Park, Joonho;Ahn, Jaehun;Kim, Ki-sung;Choi, Joongdae
    • Journal of Korean Society on Water Environment
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    • v.23 no.6
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    • pp.897-905
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    • 2007
  • Approximately 70% of Korea is composed of forest areas. Especially 48% of agricultural field is practiced at highland areas over 400 m in elevation in Kangwon province. Over 90% of highland agricultural farming is located at Kangwon province. Runoff characteristics at the mountainous area such as Kangwon province are largely affected by steep slopes, thus runoff estimation considering field slopes needs to be utilized for accurate estimation of direct runoff. Although many methods for runoff estimation are available, the Soil Conservation Service (SCS), now Natural Resource Conservation Service (NRCS), Curve Number (CN)-based method is used in this study. The CN values were obtained from many plot-years dataset obtained from mid-west areas of the United States, where most of the areas have less than 5% in slopes. Thus, the CN method is not suitable for accurate runoff estimation where significant areas are over 5% in slopes. Therefore, the CN values were adjusted based on the average slopes (25.8% at Doam-dam watershed) depending on the 5-day Antecedent Moisture Condition (AMC). In this study, the CN-based Long-Term Hydrologic Impact Assessment (L-THIA) direct runoff estimation model used and the Web-based Hydrograph Analysis Tool (WHAT) was used for direct runoff separation from the stream flow data. The $R^2$ value was 0.65 and the Nash-Sutcliffe coefficient value was 0.60 when no slope adjustment was made in CN method. However, the $R^2$ value was 0.69 and the Nash-Sutcliffe value was 0.69 with slope adjustment. As shown in this study, it is strongly recommended the slope adjustment in the CN direct runoff estimation should be made for accurate direct runoff prediction using the CN-based L-THIA model when applied to steep mountainous areas.