• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.45-45
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• 2018

오염물의 혼합거동을 해석하기 위해 물리기반 모델을 이용하는 경우 모델을 구축하고 운용하는데 많은 시간과 재정이 소요되며 현장검증을 통한 검증이 반드시 필요하다. 하지만 데이터 기반 모델의 경우 축적된 데이터만으로도 예측을 수행할 수 있으며 물리기반모델에 비해 결정해야할 입력인자가 적어 모델운용이 용이하다는 장점이 있다. 다양한 데이터 모델 중 인공신경망(ANN) 모델은 데이터가 가지는 불확실성 및 비정상성, 복잡한 상호관련성에 효과적으로 대응할 수 있는 모델로 수자원 및 환경 분야에서 자주 사용되고 있다. 본 연구에서는 인공신경망 모델을 이용하여 지천유입이 있는 대하천의 수질인자 (pH, 전기전도도, DO, chl-a)를 예측하였다. 다른 데이터기반 모델과 같이 인공신경망 모델 또한 수집된 데이터 질에 크게 영향을 받으며, 내부 입력인자의 선택이 모델의 예측 결과에 큰 영향을 미친다. 이러한 인공신경망 모델의 특성을 바탕으로 예측모형의 정확도를 향상하기 위해서는 크게 데이터 처리부분과 모델구축 부분에서의 접근이 필요하다. 본 연구에서는 데이터 처리 과정에서 연구대상지점의 각각의 수질인자가 가지는 분포 특성을 유지하기 위해 층화표츨추출법을 이용하여 데이터를 구성하였다. 모델의 구축 과정에서는 초기가중치 값의 영향을 줄이기 위해 앙상블기법을 사용하였으며, 좀 더 견고하고 정확한 결과를 예측하기 위해 탄력적 역전파알고리즘을 추가하였다. 추가적으로 합류 후 본류의 미 계측지역 수질 예측 정확도 향상을 위해 본류의 수질인자뿐만 아니라 지류의 수질인자를 입력자료로 사용하여 모의를 수행하였다. 또한 동일 구간에서 수행한 현장추적자실험 자료를 이용하여 수질인자의 분포특성을 비교, 검증하였다. 개발된 모델을 이용하여 낙동강과 금호강 합류부 하류의 수질인자를 예측한 결과 지류의 수질인자를 입력자료로 추가한 경우 예측의 정확도가 증가하였으며, 현장실험 자료를 통해 밝혀진 오염물의 거동현상을 인공신경망 모델로도 동일하게 재현하는 것으로 나타났다. 본 연구에서 제안한 인공신경모델을 이용한다면 물리기반 수치모델을 대체하여 지천으로 유입된 오염물의 거동을 정확하고 효율적으로 파악할 수 있을 것이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.386-386
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• 2017

지하수 해석을 위해 3차원 수치해석 모형이 적용되고 있으나, 다양한 매개변수를 명확히 적용하기에는 한계가 있다. 특히, 수리전도도는 지층의 투수성정도를 나타내는 계수로 지하수 분석에 매우 중요한 매개변수이다. 신뢰성의 확보를 위해 양수시험을 통해 산출된 결과를 이용하고 있으나 소수관정의 시험결과를 유역의 대푯값으로 적용하기에 불확실도가 매우 높고, 수위변화가 독특한 지역의 정확한 수리특성을 적용하기에 한계가 있다. 이 연구에서는 수리전도도 특성을 해석하기 위하여 3차원 수치해석모형을 적용하였으며, 모델보정 방법 중 Regularization(정규화)라고 불리는 Pilot point 기법을 사용하였다. 제주도와 같이 수리전도도 값이 지역별로 차이가 크고 동일 유역 내에도 다른 지질구조를 보이는 등 동일 매질에서 동일 투수성을 보이지 않는 다양함으로 실측값들을 적용하기에 어려운 곳에서 정규화라는 보정방법은 최적화된 방법이다. 지하수위는 중제주유역 내 위치한 12개소 수위관측정의 2016년 연평균수위를 적용하였다. 미계측지역은 제주도 등수위선자료를 이용하여 DEM을 구축하였으며, 임의지점 17개소를 선정하여 대표수위로 적용하였다. 중제주유역의 평균 수리전도도는 82.90 m/day로 분석되었으며, 유역의 동측 하류부는 최대 1,745 m/day로 비교적 큰 결과가 산출되었다. 유역의 중앙에 위치하는 OR관측정을 기준으로 동 서지역의 지하수위를 검토한 결과 서측은 지형구배에 따라 지하수위가 형성하고 있으나, 동측의 경우 상 하류의 표고차가 30m이상 발생되지만 지하수위는 유사한 형태를 보이고 있다. 지하수 흐름에 해석되는 Darcy의 방정식은 수리전도도와 동수경사는 반비례관계를 나타내며, 이 이론에 의해 상 하류 지하수위가 유사하게 형성되는 동측지역은 국부적으로 수리전도도가 높게 형성되는 것으로 확인되었다. 실무에서는 유역경계에 따라 평균화된 매개변수가 적용되므로 명확한 지하수 해석이 어렵고, 수리전도도와 같이 지역적 편차가 심한 매개변수는 다양한 연구를 통해 적용성검토가 수행되어야 한다.

• Journal of Korea Water Resources Association
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• v.46 no.9
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• pp.921-932
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• 2013

Runoff data availability is a substantial factor for precise flood control such as flood frequency or flood forecasting. However, runoff depths and/or peak discharges for small watersheds are rarely measured which are necessary components for hydrological analysis. To compensate for this discrepancy, a lumped concept such as a Storage Function Method (SFM) was applied for the partitioned Choongju Dam Watershed in Korea. This area was divided into 22 small watersheds for measuring the capability of spatial extension of runoff data. The chosen total number of flood events for searching parameters of SFM was 21 from 1991 to 2009. The parameters for 22 small watersheds consist of physical property based (storage coefficient: k, storage exponent: p, lag time: $T_l$) and flood event based parameters (primary runoff ratio: $f_1$, saturated rainfall: $R_{sa}$). Saturated rainfall and base flow from event based parameters were explored with respect to inflow at Choongju Dam while other parameters for each small watershed were fixed. When inflow of Choongju Dam was optimized, Youngchoon and Panwoon stations obtained average of Nash-Sutcliffe Efficiency (NSE) were 0.67 and 0.52, respectively, which are in the satisfaction condition (NSE > 0.5) for model evaluation. This result is showing the possibility of spatial data extension using a lumped concept model.

• Journal of Korea Water Resources Association
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• v.49 no.5
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• pp.439-450
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• 2016

For the design of infrastructures controlling the flood events at ungauged basins, this study tries to find the regional flood frequencies using peak flow data generated by the spatial extension of flood records. The Chungju Dam watershed is selected to validate the possibility of regional flood frequency analysis using the spatially extended flood data. Firstly, based on the index flood method, the flood event data from the spatial extension method is evaluated for 22 mid/smaller sub-basins at the Chungju Dam watershed. The homogeneity of the Chungju dam watershed was assessed in terms of the different size of watershed conditions such as accumulated and individual sub-basins. Based on the result of homogeneity analysis, this watershed is heterogeneous with respect to individual sub-basins because of the heterogeneity of rainfall distribution. To decide the regional probability distribution, goodness-of fit measure and weighted moving averages method from flood frequency analysis were adopted. Finally, GEV distribution was selected as a representative distribution and regional quantile were estimated. This research is one step further method to estimate regional flood frequency for ungauged basins.

• Korean Journal of Environmental Agriculture
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• v.30 no.3
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• pp.268-274
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• 2011

BACKGROUND: A large scale of sediment load delivered from watershed causes substantial waterway damages and water quality degradation. Controlling sediment loading requires the knowledge of the soil erosion and sedimentation. The various factors such as watershed size, slope, climate, land use may affect sediment delivery processes. Traditionally sediment delivery ratio prediction equations have been developed by relating watershed characteristics to measured sediment yield divided by predicted gross erosion. However, sediment prediction equations have been developed for only a few regions because of limited sediment data. Besides, little research has been done on the prediction of sediment delivery ratio for asia monsoon period in mountainous watershed. METHODS AND RESULTS: In this study Tank model was expanded and applied for estimating sediment yield to Oship River of east coast. The rainfall-runoff in 2006 was verified using the Tank model and we derived good result between observed and calculated discharge in 2009 at the same conditions. In relation to sediment yield, the sediment delivery rate of 2006 was very high than 2009 regardless of methods for estimating sediment load. It was thought to be affected by heavy rainfall due to the typhoon. CONCLUSION(s): For estimating sediment volume from watershed, long-term monitoring data on discharge and sediment is needed. This model will be able to apply to predict discharge and sediment yield simultaneously in ungauged area. This approach is more effective and less expensive method than the traditional method which needs a lot of data collection.

• Journal of Korea Water Resources Association
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• v.40 no.6 s.179
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• pp.447-458
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• 2007

In this study, the coastal urban flood prediction and warning system based on HEC-RAS and SWMM were investigated to evaluate a watershed of On-Cheon stream in Busan which has characteristics of costal area cased by flooding of coastal urban areas. The basis of this study is a selection of various geological data from the numerical map that is a watershed of On-Cheon stream and computation of hydrologic GIS data. Thiessen method was used for analyzing of rainfall on the On-Cheon stream and 6th regression equation, which is Huff's Type II was time-distribution of rainfall. To evaluate the deployment of flood prediction and warning system, risk depth was used on the 3 selected areas. To find the threshold runoff for hydraulic analysis of stream, HEC-RAS was used and flood depth and threshold runoff was considered with the effect of tidal water level. To estimate urban flash flood trigger rainfall, PCSWMM 2002 was introduced for hydrologic analysis. Consequently, not only were the criteria of coastal urban flood prediction and warning system decided on the watershed of On-Cheon stream, but also the deployment flow charts of flood prediction and warning system and operation system was evaluated. This study indicates the criteria of flood prediction and warning system on the coastal areas and modeling methods with application of ArcView GIS, HEC-RAS and SWMM on the basin. For the future, flood prediction and warning system should be considered and developed to various basin cases to reduce natural flood disasters in coastal urban area.

• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.737-748
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• 2022

Due to the lack of flood data, the water engineering practice calculates the design flood using rainfall frequency analysis and rainfall-runoff model. However, the rainfall frequency analysis for arbitrary duration does not reflect the regional characteristics of the duration and amount of storm event. This study proposed a practical method to calculate the design flood in a watershed considering the characteristics of storm event, based on the bivariate rainfall frequency analysis. After extracting independent storm events for the Pyeongchang River basin and the upper Namhangang River basin, we performed the bivariate rainfall frequency analysis to determine the design storm events of various return periods, and calculated the design floods using the HEC-1 model. We compared the design floods based on the bivariate rainfall frequency analysis (DF_BRFA) with those estimated by the flood frequency analysis (DF_FFA), and those estimated by the HEC-1 with the univariate rainfall frequency analysis (DF_URFA). In the case of the Pyeongchang River basin, except for the 100-year flood, the average error of the DF_BRFA was 11.6%, which was the closest to the DF_FFA. In the case of the Namhangang River basin, the average error of the DF_BRFA was about 10%, which was the most similar to the DF_FFA. As the return period increased, the DF_URFA was calculated to be much larger than the DF_FFA, whereas the BRFA produced smaller average error in the design flood than the URFA. When the proposed method is used to calculate design flood in an ungauged watershed, it is expected that the estimated design flood might be close to the actual DF_FFA. Thus, the design of the hydrological structures and water resource plans can be carried out economically and reasonably.

• Journal of Korea Water Resources Association
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• v.41 no.10
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• pp.969-982
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• 2008

As hydrological models have been progressively developed, they are recognized as appropriate tools to manage water resources. Especially, the need to evaluate the effects of landuse and climate change on hydrological phenomena has been increased, which requires powerful validation methods for the hydrological models to be employed. As measured streamflow data at many locations may not be available, or include significant errors in application of hydrological models, streamflow data simulated by models only might be used to conduct hydrological analysis. In many cases, reducing errors in model simulations requires a powerful model validation method. In this research, we demonstrated a validation methodology of SWAT model using observed flow in two basins with different physical characteristics. First, we selected two basins, Gap-cheon basin and Yongdam basin located in the Guem River Basin, showing different hydrological characteristics. Next, the methodology developed to estimate parameter values for the Gap-cheon basin was applied for estimating those for the Yongdam basin without calibration a priori, and sought for validation of the SWAT. Application result with SWAT for Yongdam basin showed $R_{eff}$ ranging from 0.49 to 0.85, and $R^{2}$ from 0.49 to 0.84. As well, comparison of predicted flow and measured flow in each subbasin showed reasonable agreement. Furthermore, the model reproduced the whole trends of measured total flow and low flow, though peak flows were rather underestimated. The results of this study suggest that SWAT can be applied for predicting effects of future climate and landuse changes on flow variability in river basins. However, additional studies are recommended to further verify the validity of the mixed method in other river basins.

• Korean Journal of Soil Science and Fertilizer
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• v.43 no.3
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• pp.363-373
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• 2010

"Curve number" (CN) indicates the runoff potential of an area. The US Soil Conservation Service (SCS)'s CN method is a simple, widely used, and efficient method for estimating the runoff from a rainfall event in a particular area, especially in ungauged basins. The use of soil maps requested from end-users was dominant up to about 80% of total use for estimating CN based rainfall-runoff. This study introduce the use of soil maps with respect to hydrologic and watershed management focused on hydrologic soil group and a case study resulted in assessing effective rainfall and runoff hydrograph based on SCS-CN method in a small watershed. The ratio of distribution areas for hydrologic soil group based on detailed soil map (1:25,000) of Korea were 42.2% (A), 29.4% (B), 18.5% (C), and 9.9% (D) for HSG 1995, and 35.1% (A), 15.7% (B), 5.5% (C), and 43.7% (D) for HSG 2006, respectively. The ratio of D group in HSG 2006 accounted for 43.7% of the total and 34.1% reclassified from A, B, and C groups of HSG 1995. Similarity between HSG 1995 and 2006 was about 55%. Our study area was located in Sosu-myeon, Goesan-gun including an approx. 44 $km^2$-catchment, Chungchungbuk-do. We used a digital elevation model (DEM) to delineate the catchments. The soils were classified into 4 hydrologic soil groups on the basis of measured infiltration rate and a model of the representative soils of the study area reported by Jung et al. 2006. Digital soil maps (1:5,000) were used for classifying hydrologic soil groups on the basis of soil series unit. Using high resolution satellite images, we delineated the boundary of each field or other parcel on computer screen, then surveyed the land use and cover in each. We calculated CN for each and used those data and a land use and cover map and a hydrologic soil map to estimate runoff. CN values, which are ranged from 0 (no runoff) to 100 (all precipitation runs off), of the catchment were 73 by HSG 1995 and 79 by HSG 2006, respectively. Each runoff response, peak runoff and time-to-peak, was examined using the SCS triangular synthetic unit hydrograph, and the results of HSG 2006 showed better agreement with the field observed data than those with use of HSG 1995.