• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.1214-1218
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• 2005

지금까지 국내에서의 수질개선을 위한 노력은 점오염원에 대한 저감만을 중심으로 진행되어 왔기 때문에, 보다 획기적인 수질개선을 위해서는 비점오염에 대한 연구와 관리가 진행되어야 한다. 그러므로 본 연구에서는 도시지역, 농촌지역, 임야지역의 토지이용특성이 다른 3유역을 대상으로 현장연구를 실시하여 비점오염물질의 발생특성 및 유역별 비교를 실시하였다. 측정은 도시지역의 가장 큰 오염원인 CSOs(Combined Sewer Overflows)에 대하여 측정을 실시하였고, 농촌지역 및 임야지역의 경우 각 유역의 출구 지점에서 측정을 실시하였다. 강우특성이 다른 15개의 강우사상을 대상으로 유량 및 SS, TCOD, TN, TP의 항목에 대하여 한 강우사상당 $15\~20$회의 측정을 실시하였다. 각각의 강우사상에 대하여 EMCs(Event Mean Concentrations)를 산출하여 도시지역, 농촌지역, 임야지역의 각 유역에 대한 확률별 EMCs를 산정한 결과 3개 유역의 EMCs는 도시지역>농촌지역>임야지역 순으로 나타났다. $EMC_{TCOD}$는 도시지역과 농촌임야지역간에 가장 큰 차이를 보이는 것으로 나타났으며, $EMC_{TN}$에서 가장 작은 차이가 나타났다. 각 유역별 EMCs의 로그-정규 확률그래프의 분산계수를 비교한 결과 농촌임야지역은 도시지역에 비하여 오염물질의 농도 변화가 강우특성에 따라 보다 큰 변화를 보이는 것으로 나타났다. 연구유역에서 $EMC_{TN}$의 발생확률 $50\% 값이 도시지역은 17.0mg/L, 농촌임야지역은 4.5mg/L로 나타났으며, 이는 유사한 유역특성을 나타내는 타 지역에서의 연구자료를 분석 값과 매우 유사한 크기를 가지는 것으로 나타났다.를 분석하였다. 실험을 수행하여 보다 정밀한 공식으로 개선할 수 있었다.$10,924m^3/s$ 및 $10,075m^3/s$로서 실험 I의 $2,757m^3/s$에 비해 통수능이 많이 개선되었음을 알 수 있다.함을 알 수 있다. 상수관로 설계 기준에서는 관로내 수압을 $1.5\~4.0kg/cm^2$으로 나타내고 있는데 $6kg/cm^2$보다 과수압을 나타내는 경우가 $100\%$로 밸브를 개방하였을 때보다 $60\%,\;80\%$ 개방하였을 때가 더 빈번히 발생하고 있으므로 대상지역의 밸브 개폐는 $100\%$ 개방하는 것이 선계기준에 적합한 것으로 나타났다. 밸브 개폐에 따른 수압 변화를 모의한 결과 밸브 개폐도를 적절히 유지하여 필요수량의 확보 및 누수방지대책에 활용할 수 있을 것으로 판단된다.8R(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 해

• Water for future
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• v.19 no.1
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• pp.65-74
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• 1986

The purpose of this study was to investigate the applicability of Single Linear Reservoir (SLR) model for runoff computations of small river basins in Korea. In the existing watershed flood routing methods the storage coefficient(K), which is the dominant parameter in the model, has been proposed to be computed in terms of the wqtershed characteristics. However, in the prsent study, the rainfall characteristics in addition to the watershed characteristics were taken into account in the multiple regression analysis for more accurate estimation of storage coefficient. The parameters finally adopted for the regressions were the drainge are, mean stream slope of the watershed, and the duration and total dffective amount of rainfalls. To verify the applicability of SLR model the computed results by SLR model with K determined by the regression equation were compared with the observed gydrographs, and also with those by other runoff computation methods; namely, the Clark method, nakayasu's synthetic unit hydrograph method and Nash model. The results showed that the present zSLR model gave the best results among these methods in the case of small river basins, but for the whatersheds with significant draingage area the Clark method gave the best results. However, it was speculated that the SLR model could also be accurately applied for flood compuatation in large wagersheds provided that the regression for storage coefficients were made with the actual data obtained in the large river basins.

• Journal of Korea Water Resources Association
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• v.45 no.5
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• pp.481-493
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• 2012

The Uncertainty of drought events can be regarded as supernatural phenomena so that the uncertainty of water supply system will be also uncontrollable. Decision making for water supply system operation must be dealt with in consideration of hydrologic uncertainty conditions. When ultimate small quantity of precipitation or streamflow lasts, water supply system might be impacted as well as stream pollution, aqua- ecosystem degradation, reservoir dry-up and river aesthetic waste etc. In case of being incapable of supplying water owing to continuation of severe drought, it can make the damage very serious beyond our prediction. This study analyzes comprehensively sustained drought impacts on the Han River Basin Water Supply System. Drought scenarios consisted of several sustained times and return periods for 5 sub-watersheds are generated using a stochastic hydrologic time series model. The developed drought scenarios are applied to assess water supply performance at the Paldang Dam. The results show that multi-year drought events reflecting spatial hydrologic diversity need to be examined in order to recognize variation of the unexpected drought impacts.

• Journal of Korea Water Resources Association
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• v.45 no.11
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• pp.1169-1186
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• 2012

Storage function method has been used for flood forecasting in the major rivers in Korea, however, the researches on the relationship between the parameters and runoff characteristics was not sufficient. In addition, there has been a controversy about the optimized parameters without the consideration of the physical characteristics of the basin. Therefore, in this study, the SCE-UA method is used to optimize the parameters and the proposed method was applied with two stage optimization in the Jeongseon and Yeongwol watersheds located in the most upstream in the South Han river. The contour map was developed to investigate parameters and the error surface calculated from the runoff. The proposed parameters is to provide a range of the possible parameter set in a watershed, rather than a specific value. However, the applicability is examined using the average value of the proposed ranged parameters. In this study, the criticism about the optimization technique to find an optimal value having no physical meaning on a watershed is tried to avoid. The objective of this study is to provide a range of parameters for the flood forecasting model and the intuition about the behavior of the parameters, so the efficiency of flood forecasting is increased.

• Journal of Korea Water Resources Association
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• v.41 no.11
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• pp.1123-1133
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• 2008

It needs to conceptualize watershed with triangular or rectangular elements and to analyze the changes in hydrological components of each element for distributed modeling of rainfall-runoff process. This study is the network analysis of watershed grid for flow routing occurred in each element when analyzing rainfall-runoff process by one-dimensional kinematic wave equation. Single flow direction from D8-method(deterministic eight-neighbors method) is used, and the information of flow direction and flow accumulation are used to determine the computation order of each element. The application theory of finite volume method is suggested for each flow direction pattern between elements, and it is applied it to calculate the flow of each grid. Network analysis method from this study is applied to GRM(Grid based Rainfall-runoff Model) which is physically based distributed rainfall-runoff model, and the results from simplified hypothetical watersheds are compared with $Vflo^{TM}$ to examine the reasonability of the method. It is applied to Jungrangcheon watershed in Han river for verification, and examination of the applicability to real site. The results from Jungrangcheon watershed show good agreement with measured hydrographs, and the application of the network analysis method to real site is proper.

• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.1057-1066
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• 2019

The storage function method is used as a flood prediction model for four flood control offices in Korea as a method to analyze the actual rainfall-runoff relationship with non-linearity. It is essential to accurately estimate the parameters of the storage function method for accurate runoff analysis. However, the parameters of the storage function method currently in use are estimated by the empirical formula developed by the limited hydrological analysis in 2012; therefore, they are somewhat inaccurate. The kinematic wave method is a method based on physical variables of watershed and channel and is widely used for rainfall-runoff analysis. By adopting the two-term storage function method by the conversion of the kinematic wave method, parameters can be estimated based on physical variables, which can increase the accuracy of runoff calculation. In this research, the reproducibility of the kinematic wave method by the two-term storage function method was investigated. It is very easy to estimate the parameters because equivalent roughness, which is an important physical variable in watershed runoff, can be easily obtained by using land use and land cover, and the physical variable of channel runoff can be easily obtained from the basic river planning report or topographic map. In addition, this research examined the applicability of the two-term storage function method to runoff simulation of Naechon Stream, a tributary of the Hongcheon River in the Han River basin. As a result, it is considered that more accurate runoff calculation results could be obtained than the existing one-term storage function method. It is expected that the utilization of the storage function method can be increased because the parameters can be easily estimated using physical variables even in unmeasured watersheds and channels.

• Current Research on Agriculture and Life Sciences
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• v.7
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• pp.55-66
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• 1989

The purpose of this study is to estimate the flood discharge and peak time by the SCS method and the probability method using the geomorpologic parameters obtained from the topographic maps following the law of stream classifying and, ordering by Horton and Strahler. The SCS method and the probability method are used in estimating the times to peak and the flood discharges at An-dong, Im-ha, and Sun-san basins in the Nakdong River system. The results obtained are as follows : 1. The range of the values of the area ratio, the bifurcation ratio and the length ratio agree with those of natural streams presented by Horton and Strahler. 2. Comparisons of the probability method and observed values show that small relative errors of 0-7% of flood discharge, and 0-2hr, difference in time to peak respectivly. But the SCS method shows that large relative errors of 10-40% of flood discharge, and 0-4hr, difference in time to peak. 3. When the rainfall intensity is large, the error of flood discharge estimated by using the probability method is relativly small.

• Journal of Korea Water Resources Association
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• v.44 no.8
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• pp.667-681
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• 2011

The objective of this study is to evaluate the applicability of a Land Surface Model (LSM) for drought analysis in Korea. For evaluating the applicability of the model, the model was calibrated on several upper dam site watersheds and the hydrological components (runoff and soil moisture) were simulated over the whole South Korea at grid basis. After converting daily series of runoff and soil moisture data to accumulated time series (3, 6, 12 months), drought indices such as SRI and SSI are calculated through frequency analysis and standardization of accumulated probability. For evaluating the drought indices, past drought events are investigated and drought indices including SPI and PDSI are used for comparative analysis. Temporal and spatial analysis of the drought indices in addition to hydrologic component analysis are performed to evaluate the reproducibility of drought severity as well as relieving of drought. It can be concluded that the proposed indices obtained from the LSM model show good performance to reflect the historical drought events for both spatially and temporally. From this point of view, the LSM can be useful for drought management. It leads to the conclusion that these indices are applicable to domestic drought and water management.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05a
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• pp.43-50
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.303-314
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• 2020

The hydrological characteristics of watersheds and hydraulic systems of urban and river floods are highly nonlinear and contain uncertain variables. Therefore, the predicted time series of rainfall-runoff data in flood analysis is not suitable for existing neural networks. To overcome the challenge of prediction, a NARX (Nonlinear Autoregressive Exogenous Model), which is a kind of recurrent dynamic neural network that maximizes the learning ability of a neural network, was applied to forecast a flood in real-time. At the same time, NARX has the characteristics of a time-delay neural network. In this study, a hydrological model was constructed for the Taehwa river basin, and the NARX time-delay parameter was adjusted 10 to 120 minutes. As a result, we found that precise prediction is possible as the time-delay parameter was increased by confirming that the NSE increased from 0.530 to 0.988 and the RMSE decreased from 379.9 ㎥/s to 16.1 ㎥/s. The machine learning technique with NARX will contribute to the accurate prediction of flow rate with an unexpected extreme flood condition.