• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1094-1098
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• 2010

미계측 유역에서의 홍수량을 추정할 수 있는 방법은 다양하게 제시되고 있으나, 이에 대한 평가나 조사는 사실상 전무하여 수자원 설계실무에 이용할 수 있는 절차나 방법은 극히 제한되어있다. 현재 주로 이용하고 있는 홍수량 추정절차는 강우를 근거로 한 확률강우량법, SCS방법, 단위도법이 국내의 표준방법으로 이용되고 있다. 또한 수치지도 및 위성영상분석 등과 같은 GIS 자료의 구축이 가능해짐에 따라서, 국내에서는 토양의 종류와 피복 형태 그리고 선행강우조건까지 종합적으로 고려하여 해석하는 유출곡선번호(SCS Runoff Curve Number; CN) 방법이 많이 사용되고 있다. 유출량 해석 시 이용되는 CN은 토지이용도 및 토양도와 같은 지형학적 인자에 지배받게 된다. 그러나 현재 우리나라에서 제공하는 토지이용도 및 토양도는 그 종류가 다양하고, 분류방식이 상이하여 활용 자료에 따라 CN이 달라지므로 유출율의 차이가 발생하게 된다. 국내에서 제공되는 다양한 자료를 이용하여 최적의 CN값을 산정하기 위한 연구가 선행된 바있다. 허기술(1987) 등은 우리나라의 정밀토양도에 의한 토양군 분류에 관한 연구를 진행하였으며 조홍제(1997, 2001)는 LANDSAT 위성영상을 이용하여 유역의 토지피복상태를 분류하고 식생지수를 고려하여 CN을 추정하였고, 김경탁(1998, 2003, 2004)은 개략토양도와 정밀토양도를 이용하여 유출모의 실행한 결과를 비교하여 신뢰도가 높다고 판단되는 정밀토양도를 사용한 CN 추정기법의 사용을 제안한 바 있다. 본 연구에서는 GIS를 이용하여 국내에서 활용 가능한 토양도 및 토지이용도의 종류에 따라 총 9개 Case로 안동댐 유역의 CN을 산정하였다.

• Water Engineering Research
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• v.4 no.1
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• pp.19-30
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• 2003

TMDL development and implementation have great potential fur use in efforts to improve water quality management, but the TMDL approach still has several difficulties to overcome in terms of cost, time requirements, and suitable methodologies. A well-defined prioritization approach for identifying watersheds of concern among several tar-get locations that would benefit from TMDL development and implementation, based on a simple screening approach, could be a major step in solving some of these difficulties. Therefore, a web-based decision support system (DSS) was developed to help identify areas within watersheds that might be priority areas for TMDL development. The DSS includes a graphical user interface based on the HTML protocol, hydrological models, databases, and geographic information system (GIS) capabilities. The DSS has a hydrological model that can estimate non-point source pollution loading based on over 30 years of daily direct runoff using the curve number method and pollutant event mean concentration data. The DSS provides comprehensive output analysis tools using charts and tables, and also provides probability analysis and best management practice cost estimation. In conclusion, the DSS is a simple, affordable tool for the preliminary study of TMDL development via the Internet, and the DSS web site can also be used as an information web server for education related to TMDL.

• Water for future
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• v.27 no.4
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• pp.85-94
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• 1994

A Sensitivity analysis on the model parameters involved in the Clark watershed routing method is made to demonstrate the effect of each parameter on the magnitude of 50-year design flood for small urban streams. As for the rainfall parameter the time distribution pattern of design storm was selected. For short duration storms Huff, Yen & Chow and Japanese Central type distributions were selected and the Mononobe distribution of 24-hour design storm was also selected and tested for Clark method application. The effect of SCS runoff curve number for effective rainfall and the methods of subbasin division for time-area curve were also tested. The routing parameter, i.e. the storage constant(K), was found to be the dominating parameter once design storm is selected. A multiple regression formula for K correlated with the drainage area and main channel slope of the basin is proposed for the use in urban stream practice for the determination of design flood by Clark method.

• Magazine of the Korean Society of Agricultural Engineers
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• v.18 no.2
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• pp.4116-4120
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• 1976

With the use of many rivers increased nearly to the capacity, the need for information concerning daily quantities of water and the total annual or seasonal runoff has became increased. A systematic record of the flow of a river is commonly made in terms of the mean daily discharge Since. a single observation of stage is converted into discharge by means of rating curve, it is essential that the stage discharge relations shall be accurately established. All rating curves have the looping effect due chiefly to channel storage and variation in surface slope. Loop rating curves are most characteristic on streams with somewhat flatter gradients and more constricted channels. The great majority of gauge readings are taken by unskilled observers once a day without any indication of whether the stage is rising or falling. Therefore, normal rating curves shall show one discharge for one gauge height, regardless of falling or rising stage. The above reasons call for the correction of the discharge measurements taken on either side of flood waves to the theoretical steady-state condition. The correction of the discharge measurement is to consider channel storage and variation in surface slope. (1) Channel storage As the surface elevation of a river rises, water is temporarily stored in the river channel. There fore, the actual discharge at the control section can be attained by substracting the rate of change of storage from the measured discharge. (2) Variation in surface slope From the Manning equation, the steady state discharge Q in a channel of given roughness and cross-section, is given as {{{{Q PROPTO SQRT { 1} }}}} When the slope is not equal, the actual discharge will be {{{{ { Q}_{r CDOT f } PROPTO SQRT { 1 +- TRIANGLE I} CDOT TRIANGLE I }}}} may be expressed in the form of {{{{ TRIANGLE I= { dh/dt} over {c } }}}} and the celerity is approximately equal to 1.3 times the mean watrr velocity. Therefore, The steady-state discharge can be estimated from the following equation. {{{{Q= { { Q}_{r CDOT f } } over { SQRT { (1 +- { A CDOT dh/dt} over {1.3 { Q}_{r CDOT f }I } )} } }}}} If a sufficient number of observations are available, an alternative procedure can be applied. A rating curve may be drawn as a median line through the uncorrected values. The values of {{{{ { 1} over {cI } }}}} can be yielded from the measured quantities of Qr$.$f and dh/dt by use of Eq. (7) and (8). From the 1/cI v. stage relationship, new vlues of 1/cI are obtained and inserted in Eq. (7) and (8) to yield the steady-state discharge Q. The new values of Q are then plotted against stage as the corrected steadystate curve.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.6
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• pp.51-64
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• 2022

Along with the urbanization, the risk of urban flooding due to climate change is increasing. Flood regulation, one of the ecosystem services, is implemented in the different level of function of flood risk mitigation by the type of ecosystem such as forests, arable land, wetlands etc. Land use changes due to development pressures have become an important factor in increasing the vulnerability by flash flood. This study has conducted evaluating the urban flood regulation service using InVEST UFRM(Urban Flood Risk Model). As a result of the simulation, the potential water retention by ecosystem type in the event of a flash flood according to RCP 4.5(10 year frequency) scenario was 1,569,611 tons in urbanized/dried areas, 907,706 tons in agricultural areas, 1,496,105 tons in forested areas, 831,705 tons in grasslands, 1,021,742 tons in wetlands, and 206,709 tons in bare areas, the water bodies was estimated to be 38,087 tons. In the case of more severe 100-year rainfall, 1,808,376 tons in urbanized/dried areas, 1,172,505 tons in agricultural areas, 2,076,019 tons in forests, 1,021,742 tons in grasslands, 47,603 tons in wetlands, 238,363 tons in bare lands, and 52,985 tons in water bodies. The potential economic damage from flood runoff(100 years frequency) is 122,512,524 thousand won in residential areas, 512,382,410 thousand won in commercial areas, 50,414,646 thousand won in industrial areas, 2,927,508 thousand won in Infrastructure(road), 8,907 thousand won in agriculture, Total of assuming a runoff of 50 mm(100 year frequency) was estimated at 688,245,997 thousand won. In a conclusion. these results provided an overview of ecosystem functions and services in terms of flood control, and indirectly demonstrated the possibility of using the model as a tool for policy decision-making. Nevertheless, in future research, related issues such as application of models according to various spatial scales, verification of difference in result values due to differences in spatial resolution, improvement of CN(Curved Number) suitable for the research site conditions based on actual data, and development of flood damage factors suitable for domestic condition for the calculation of economic loss.

• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.121-129
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• 2020

The increase of impervious surface and development along the river due to urbanization not only causes an increase in the number of associated flood risk factors but also exacerbates flood damage, leading to difficulties in flood management. Flood control measures should be prioritized based on various geographical information in urban areas. In this study, a probabilistic flood hazard assessment was applied to flood-prone areas near an urban river. Flood hazard maps were alternatively considered and used to describe the expected inundation areas for a given set of predictors such as elevation, slope, runoff curve number, and distance to river. This study proposes a Bayesian logistic regression-based flood risk model that aims to provide a probabilistic risk metric such as population-at-risk (PAR). Finally, the logistic regression model demonstrates the probabilistic flood hazard maps for the entire area.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.553-557
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• 2005

유역의 강우-유출 분석에서 유효우량의 산정은 매우 중요하다고 할 수 있다. 이러한 유효우량의 산정에서 대상호우에 대한 유출량 자료가 있는 경우는 침투지수법(infiltration index method)중 하나인 $\Phi$-지표법이나 W-지표법을 사용하여 그 양을 산정할 수 있다. 그러나 대상호우에 대한 유출량 자료가 없는 경우는 침투지수법을 이용하여 유효우량을 산정 할 수 없으며, 이러한 경우 유역의 토양 특성과 식생피복 상태에 대한 자료만으로 총우량으로부터 유효우량을 산정할 수 있는 NRCS(Natural Resources Conservation Service)의 유효우량 산정방법이 널리 사용되고 있다. NRCS유효우량 산정 방법은 선행토양함수조건(antecedent moisture condition, AMC)을 이 용하여 유출곡선지수(runoff curve number, CN)를 결정하는데, 이때 AMC의 산정을 위해 선행5일강우량(total 5-day antecedent rainfall)을 그 기준으로 하고 있으나, 이는 미국의 유역을 대상으로 하여 얻어진 결과이므로 이를 국내 유역에 검증 없이 적용하는 데에는 문제가 있을 것으로 예상되었다. 따라서 본 연구에서는 HEC-HMS모형을 이용하여 선행강우일수을 변화시켜 가면서 실제 유역의 강우-유출에 적용하여 본 뒤 강우-유출을 가장 잘 모의하는 선행강우일수을 결정하였다. 이를 위해, IHP 대상유역인 보청천의 탄부소유역에 대하여 AMC의 산정을 위한 선행강우량을 1일부터 7일까지 변화시키며 적용한 결과 탄부소유역에서는 선행2일강우량이 가장 적합한 결과를 주는 것으로 나타났다. 국내 유역에서 NRCS유효유량 산정방법을 통한 강우-유출모의시 보다 정확한 값을 산정하기 위해서는 대상유역에 적합한 선행 강우일수의 결정이 중요하리라 판단된다.인 분석을 수행하고, 배수갑문 개방에 의한 수질개선효과를 최대화하기 위한 환경관리 방안 제시에 중점을 두어 수행하였다.ncy), 환경성(environmental feasibility) 등을 정성적으로(qualitatively) 파악하여 실현가능한 대안을 선정하였다. 이렇게 선정된 대안들은 중유역별로 검토하여 효과가 있을 것으로 판단되는 대안들을 제시하는 예비타당성(Prefeasibility) 계획을 수립하였다. 이렇게 제시된 계획은 향후 과학적인 분석(세부평가방법)을 통해 대안을 평가하고 구체적인 타당성(feasibility) 계획을 수립하는데 토대가 될 것이다.{0.11R(mm)}(r^2=0.69)$로 나타났다. 이는 토양의 투수특성에 따라 강우량 증가에 비례하여 점증하는 침투수와 구분되는 현상이었다. 경사와 토양이 같은 조건에서 나지의 경우 역시 $Ro_{B10}(mm)=20.3e^{0.08R(mm)(r^2=0.84)$로 지수적으로 증가하는 경향을 나타내었다. 유거수량은 토성별로 양토를 1.0으로 기준할 때 사양토가 0.86으로 가장 작았고, 식양토 1.09, 식토 1.15로 평가되어 침투수에 비해 토성별 차이가 크게 나타났다. 이는 토성이 세립질일 수록 유거수의 저항이 작기 때문으로 생각된다. 경사에 따라서는 경사도가 증가할수록 증가하였으며 $10\% 경사일 때를 기준으로 $Ro(mm)=Ro_{10}{\times}0.797{\times}e^{-0.021s(\%)}$로 나타났다.천성 승모판 폐쇄 부전등을 초래하는 심각한 선천성 심질환이다. 그러나 진단 즉시 직접 좌관상동맥-대동맥 이식술로 수술적 교정을 해줌으로써 좋은 성적을 기대할 수 있음을 보여주었다.특히 교사들이 중요하게 인식하는 해방적 행동에 대한 목표를 강조하여 적용할 필요가 있음을 시사하고

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1107-1118
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• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

• Journal of Korea Water Resources Association
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• v.48 no.6
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• pp.491-500
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• 2015

In order to improve the runoff estimation accuracy of the Natural Resources Conservation Service (NRCS) curve number (CN) model, this study incorporated rainfall and maximum potential retention as contributors for initial abstraction. The modification was proposed based on 658 rank-order data of rainfall and subsequent runoff from 15 watersheds. The NRCS-CN model (M1), one of its inspired modified model (M2), and the proposed model (M3) were analyzed employing different CN approaches. Using tabulated, calculated and least squares fitted CNs ($CN_T$, $CN_C$, $CN_{LSF}$, respectively), the models' performances were evaluated based on Root Mean Square Error (RMSE), Nash-Sutcliffe Efficiency (NSE), and Percent Bias (PBIAS). Applications of model M1, M2, and M3, respectively exhibited watershed cumulative mean [RMSE (23.60, 18.12, 16.04), NSE (0.54, 0.73, 0.79), and PBIAS (36.54, 20.25, 12.00)]. Similarly, using CNC (for M1 and M2 model) and $CN_{LSF}$ (for M3 model), the performance of three models respectively were assessed based on watershed cumulative mean [RMSE (17.17, 15.88, 13.82), NSE (0.76, 0.80, 0.85), and PBIAS (3.06, 4.47, 0.11)]. The proposed model (M3) that linked all of the NRCS-CN variants showed more statistically significant agreement between the observed and estimated data.

• 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.