• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.578-582
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• 2005

In this study, the conceptual foundation and development process of the Antecedent soil Moisture Condition(AMC) in SCS runoff curve number method are reviewed. Although the runoff volume is very sensitive with AMC condition, the AMC class limits developed in SCS(1972) are used in rainfall-runoff analysis without careful consideration. Tn this study, following the SCS curve number development process, rainfall-runoff characteristics of the Jang-Pyung subbasin subject to the Pyung-Chang River basin are analyzed to evaluate the reasonability of the AMC class limits at present. The New AMC class limits are proposed by the sensitive analysis of the antecedent rainfall - curve number value. As a result, the classification value of AMC-I with II is 22mm of antecedent 5-day rainfall amount, and the classification of AMC-II with III is 117mm in growing season. When the New AMC class limits are applied to Jang-Pyung subbasin, AMC probability distribution shows that the AMC-II has increased remarkably even though the AMC-I has a little higher value. But the AMC-III has the smallest one. According to the conceptual basis of the curve number method, the AMC probability distribution, the New AMC class limits adopted, gives reasonable results.

• Journal of Korea Water Resources Association
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• v.51 no.5
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• pp.417-424
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• 2018

This study analyzed the effect of irrigation reservoirs, antecedent soil moisture conditions (AMC) and Huff time distribution on peak discharge using Monte Carlo simulation. The peak discharge was estimated for four different cases in combination of irrigation reservoir capacity, AMC, and Huff time distribution. Applying 100% reservoir capacity or AMC-III, the peak discharges corresponding return periods of 50~300 years were overestimated by 25~30% compared to those of cases that considered the probability of occurrence for individual condition. Applying the 3rd quantile huff distribution, the peak discharges were overestimated by 5% over the peak discharge that considered the probability of occurrence. The overall results indicated that the effect on the peak flood of Huff distribution was less than AMC and reservoir storage.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.18 no.3
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• pp.13-22
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• 2015

Unpaved forest roads are common accessways in mountain areas being used for forestry purposes. The presence of forest roads produces large volumes of surface runoff and sediment yield due to changes in soil properties and hillslope profile. Rainfall simulation experiments were conducted to estimate the impacts of above-ground vegetation and antecedent soil water condition on hydrology and sediment processes. A total of 9 small plots($1m{\times}0.5m$) were installed to represent different road surface conditions: no-vegetation(3 plots), vegetated surface(3 plots), and cleared vegetation surface(3 plots). Experiments were carried out on dry, wet, and very wet soil moisture conditions for each plot. Above ground parts of vegetation on road surface influenced significantly on surface runoff. Runoff from no-vegetation roads(39.24L) was greater than that from vegetated(25.05L), while cleared-vegetation condition is similar to no-vegetation roads(39.72L). Runoff rate responded in a similar way to runoff volume. Soil erosion was also controlled by land cover, but the magnitude is little than that of surface runoff. Even though slight differences among antecedent soil moisture conditions were found on both runoff and soil erosion, runoff rate and soil losses were increased in very wet condition, followed by wet condition. The experiments suggest that vegetation cover on forest road surface seems most effective way to reduce surface runoff and soil erosion during storm periods.

• Journal of Korean Society on Water Environment
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• v.36 no.3
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• pp.229-244
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• 2020

Hydrologic models, as a useful tool for understanding the hydrologic phenomena in the watershed, have become more complex with the increase of computer performance. The hydrologic model, with complex configurations and powerful performance, facilitates a broader understanding of the effects of climate and soil in hydrologic partitioning. However, the more complex the model is, the more effort and time is required to drive the model, and the more parameters it uses, the less accessible to the user and less applicable to the ungauged watershed. Rather, a parsimonious hydrologic model may be effective in hydrologic modeling of the ungauged watershed. Thus, a semi-distributed hydrologic partitioning model was developed with minimal composition and number of parameters to improve applicability. In this study, the validity and performance of the proposed model were confirmed by applying it to the Namgang Dam, Andong Dam, Hapcheon Dam, and Milyang Dam watersheds among the Nakdong River watersheds. From the results of the application, it was confirmed that despite the simple model structure, the hydrologic partitioning process of the watershed can be modeled relatively well through three vertical layers comprising the surface layer, the soil layer, and the aquifer. Additionally, discussions were conducted on antecedent soil moisture conditions widely applied to stormwater estimation using the soil moisture data simulated by the proposed model.

• Korean Journal of Hydrosciences
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• v.4
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• pp.21-32
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• 1993

The estimates of both runoff depth and peak runoff by the basin runoff curve numbers, which are CN-II for antecedent moisture condition- II and CN -III for antecedent moisture condition-III, obtained from hydrological soil-cover complexes of 26 watersheds are investigated by making use of the observed curve numbers, which are median curve number and optimum curve number, computed from 250 rainfall-runoff records. For gaged basins the median curve numbers are recommended for the estimation of both runoff depth and peak runoff. For ungaged basin, found is that for the estimate of runoff depth CN-II is adequate and for peak runoff CN-II is suitable. Also investigated is the variation of the runoff curves during storms. By the variable runoff curve numbers, the prediction of runoff depth and peak runoff can be improved slightly.

• Journal of Korea Water Resources Association
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• v.52 no.9
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• pp.615-626
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• 2019

Soil moisture and runoff have very close relationship. Especially the water retention capacity and drainage characteristics of the soil are determined by various factors of the soil. In this study, a total of 40 rainfall events were identified from the entire rainfall events of Sulma basin in 2016 and 2017. For each selected events, the constant-K method was used to separate direct runoff and baseflow from total flow and calculate the runoff coefficient which shows positive exponential curve with Antecedent Soil Moisture (ASM). In addition to that, the threshold of soil moisture was determined at the point where the runoff coefficient starts increasing dramatically. The threshold of soil moisture shows great correlation with runoff and depth to water table. It was founded that not only ASM but also various factors, such as Initial Soil Moisture (ISM), storage capacity of soil and precipitation, affect the results of runoff response. Furthermore, wet condition and dry condition are separated by ASM threshold and the start and peak response are analyzed. And the results show that the response under wet condition occurred more quickly than that of dry condition. In most events occurred in dry condition, factors reached peak in order of soil moisture, depth to water table and runoff. However, in wet condition, they reached peak in order of depth to water table, runoff and soil moisture. These results will help identify the interaction among factors which affect the runoff, and it will help establish the relationship between various soil conditions and runoff.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.288-288
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• 2011

최근 들어 관측된 강우-유출 사상으로부터 유출곡선지수(Runoff curve number, CN)를 계산하는 연구가 수행되어왔으며, 이것은 기존 선행토양함수조건(Antecedent Moisture Condition; AMC) 을 이용한 유출곡선지수 적용에 대한 여러 문제점(AMC 기준의 타당성, 초기손실우량과 최대잠재보유수량의 비($I_a$ S=0.20의 적정성))이 부각되면서 선행유출조건을 이용한 유출곡선지수가 제안되었다. 본 연구에서는 선행유출조건(Antecedent Runoff Condition, ARC) 방법을 적용하여 IHP유역인 방림과 상안미 유역의 강우-유출자료로부터 CN을 직접 산정하였다. 먼저 방림과 상안미 유역에서 각각 12개, 10개의 관측된 강우-유출 사상을 통해 초기손실우량과 최대잠재보유수량의 비($I_a$/S)가 기존 가정의 0.20보다 작은 것을 확인하고 수정된 $I_a$/S비를 고려하여 대상 유역에서의 적정 CN을 산정하였다. 실제 강우-유출 사상에서 산정한 각 사상별 CN의 대표값을 찾기 위해 ARC-II의 평균유출조건으로 가정하여 각 사상별 단순평균과 4개의 지속기간(4시간, 3시간, 2시간, 1시간)별로 구분하여 평균한 CN을 구분하였다. 이를 통해 계산된 유효우량과 관측 유효우량과 비교를 실시하였으며 각 사상을 단순 평균한 ARC-II 조건으로 가정하여 계산된 CN의 오차가 가장 작은 것으로 나타났다. 따라서 기존의 선행토양함수조건(Antecedent soil moisture condition, AMC)의 CN으로 산정된 유효우량과 ARC조건으로 산정된 유효우량을 비교한 결과 방림유역에서 는 오차가 ARC 방법의 경우 37.76%, AMC 방법의 경우 51.27%로 평가되었고 상안미 유역에서는 오차가 ARC의 경우 31.97%, AMC 방법의 경우43.08%로 두 유역에서 모두 ARC 방법으로 산정된 CN이 더 적은 오차값을 주었다. 따라서 방림과 상안미 유역에서의 ARC로 산정된 CN값은 유효우량 산정의 정확성을 향상시킬 수 있으리라 판단된다.

• Journal of The Korean Society of Agricultural Engineers
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• v.50 no.6
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• pp.3-12
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• 2008

It is important to estimate accurate effective rainfall to analyse flood flow and long-term runoff for the rational planning, design, and management of water resource. The initial abstraction is also important to estimate effective rainfall. The Soil Conservation Service (SCS) has developed a procedure and it has been most commonly applied to estimate effective rainfall. But the SCS method still has weak points, because of unnatural assumptions such as antecedent moisture conditions and initial abstraction. The coefficient of initial abstraction(K) is depending on the soil moisture condition and antecedent rainfall. The maximum storage capacity of Umax which is calibrated by stream flow data in the proposed watershed was derived from the DAWAST(DAily WAtershed STreamflow) model. The values of K obtained from 69 storm events at the five watersheds are ranging from 0.133 to 0.365 and its mean value is 0.207. Effective rainfall could be estimated more reasonably by introducing new concept of initial abstraction. The equation of $K=0.076Sa^{0.255}$ was recommended instead of 0.2 and it could be applicable to the small-medium rural watersheds.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.3
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• pp.849-858
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• 2014

The mount of antecedent 5-day rainfall (P5) is usually used to determine the antecedent soil moisture condition for estimating effective rainfall using the NRCS-CN method. In order to re-establish the threshold of P5 considering basin characteristics, this study investigated the sensitivity of the threshold of P5 to effective rainfall by comparing the corresponding observed direct runoff. The overall results indicate that the direct runoff estimated using the re-establihed threshold of P5 has smaller mean error (RMSE of 27.3 mm) than those using the conventional threshold (RMSE of 35.2 mm). In addition, after evaluating the effectiveness of threshold of P5 using the improvement index, the threshold re-established in this study improved the ability to estimate the direct runoff by 30% on average. This study also suggested to employ regression models using topographic indices to re-establish the threshold for ungauged basins. When using the re-established threshold from the regression model, the RMSE decreased ranging from 0.4 mm to 15.1 mm and the efficiency index of Nash and Sutcliffe increased up to 0.33.