• 제목/요약/키워드: Flow Duration Curve

검색결과 154건 처리시간 0.043초

도심지 토사재해 고위험지역 극치강우 시간분포 시나리오 분석 (Analysis of Extreme Rainfall Distribution Scenarios over the Landslide High Risk Zones in Urban Areas)

  • 윤선권;장상민;이진영
    • 한국농공학회논문집
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    • 제58권3호
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    • pp.57-69
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    • 2016
  • In this study, we analyzed the extreme rainfall distribution scenarios based on probable rainfall calculation and applying various time distribution models over the landslide high risk zones in urban areas. We used observed rainfall data form total 71 ASOS (Automated Synoptic Observing System) station and AWS (Automatic Weather Station) in KMA (Korea Meteorological Administration), and we analyzed the linear trends for 1-hr and 24-hr annual maximum rainfall series using simple linear regression method, which are identified their increasing trends with slopes of 0.035 and 0.660 during 1961-2014, respectively. The Gumbel distribution was applied to obtain the return period and probability precipitation for each duration. The IDF (Intensity-Duration-Frequency) curves for landslide high risk zones were derived by applying integrated probability precipitation intensity equation. Results from IDF analysis indicate that the probability precipitation varies from 31.4~38.3 % for 1 hr duration, and 33.0~47.9 % for 24 hr duration. It also showed different results for each area. The $Huff-4^{th}$ Quartile method as well as Mononobe distribution were selected as the rainfall distribution scenarios of landslide high risk zones. The results of this study can be used to provide boundary conditions for slope collapse analysis, to analyze sediment disaster risk, and to use as input data for risk prediction of debris flow.

화성호 유역의 수질관리를 위한 유역모델링 연구 (Watershed Modeling Research for Receiving Water Quality Management in Hwaseong Reservoir Watershed)

  • 장재호;강형식;정광욱
    • 한국물환경학회지
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    • 제28권6호
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    • pp.819-832
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    • 2012
  • HSPF model based on BASINS was applied for the Hwaseong Reservoir watershed (HRW) to evaluate the feasibility of water quality management. The watershed was divided into 45 sub-basins considering various watershed environment. Streamflow was calibrated based on the measured meteorological data, discharge data of treatment plants and observed streamflow data for 2010 year. Then the model was calibrated against the field measurements of water qualities, including BOD, T-N and T-P. In most cases, there were reasonable agreements between observed and predicted data. The validated model was used to analyze the characterization of pollutant load from study area. As a result, Non-point source pollutant loads during the rainy season was about 66~78% of total loads. In rainy-season, water quality parameters depended on precipitation and pollutant loads patterns, but their concentration were not necessarily high during the rainy season, and showed a decreasing trend with increasing water flow. As another result of evaluation for load duration curves, in order to improve water qualities to the satisfactory level, the watershed managements considering both time-variant and pollution sources must be required in the HRW. Overall, it was found that the model could be used conveniently to assess watershed characteristics and pollutant loads in watershed scale.

청미천 유역 유황조건별 오염원 기여율 평가 (Assessment of the contribution of pollutant load to flow duration conditions in Chungmi watershed)

  • 김계웅;강문성;전상민;류정훈;황순호
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2018년도 학술발표회
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    • pp.444-444
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    • 2018
  • 하천의 수질개선을 위해서는 유역에서 배출되는 배출량을 제어하는 것뿐만 아니라 오염원별 기여도를 파악하고 효과적인 수질개선대책을 수립하는 것이 필요하다. 또한, 계절 및 유량조건에 따라 오염원의 배출량, 배출특성이 상이하게 나타나기 때문에 이를 고려하여 기여도를 파악하는 것이 필요하다. 본 연구에서는 청미천 유역을 대상으로 계절 및 유량조건에 따라 오염원별 기여율를 산정하고, 해당 유역의 수질개선을 위한 주요 인자를 도출하고자 한다. 기여율 분석을 위해 청미천 내에 유량 및 수질측정지점을 기준으로 소유역 구분을 하였으며, 소유역별로 물환경정보시스템을 통해 받은 유량 및 수질 자료를 활용하여 유량-부하량 관계곡선을 도출하였다. 유황조건별 부하량을 도출하기 위해 실측 유량 및 수질자료를 활용하여 유황곡선과 LDC(Load Duration Curve) 곡선을 작성하였다. 오염원별 기여도 산정을 위해 환경부의 2015년 전국오염원조사자료를 활용하여 소유역별 배출부하량을 산정하였으며, 앞서 산정한 LDC 곡선과의 비교를 통해 오염원별로 기여율을 산정하였다. 본 연구의 방법은 향후 유역의 수질개선대책 수립 시 오염원별 기여도 도출을 위한 기초자료로 활용될 수 있을 것으로 사료된다.

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유황분석과 수질변화 평가를 통한 비점오염원 관리대상지역 선정방법 연구 (Watershed Selection for Diffuse Pollution Management Based on Flow Regime Alteration and Water Quality Variation Analysis)

  • 정우혁;이상진;김건하;정상만
    • 한국물환경학회지
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    • 제27권2호
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    • pp.228-234
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    • 2011
  • The goal of water quality management on stream and watershed is to focus not on discharged loads management but on a water quality management. Discharged loads management is not goal of water quality management but way for perform with total maximum daily loads management. It is necessary to estimate the relation between non-point source with stromwater runoff (NPSSR) and water quality to select a watershed where it is required to manage NPSSR for water quality improvement. To evaluate the effects of NPSSR on stream's water quality, we compare the aspects of water quality in dry and wet seasons using flow duration curve analysis based on flow rate variation data by actual surveying. In this study we attempt to quantify the variation characteristic of water quality and estimate the Inflow characteristic of pollution source with water quality and flow rate monitoring on 10 watersheds. We try to estimate water quality and flow rate by regression analysis and try again regression analysis with each high and low water quality data more than estimations. An analysis of relation between water quality and flow rate of 10 watersheds shows that the water quality of the Nonsan and the Ganggyeong streams had been polluted by NPSSR pollutants. Other eight streams were important point source more than NPSSR. It is wide variation range of $BOD_5$ also high average concentration of $BOD_5$. We have to quantify water quality variation by cv1 in wet season and cv365 in dry season with comparing the estimate of high water quality and low water quality. This method can be used to indicator for water quality variation according to flow rate.

부하지속곡선을 이용한 삽교천 유역의 오염총량관리제도 시행효과 분석 (Analysis of the Implementation Effect of Total Water Load Management System Using Load Duration Curves in Sapgyo Watershed)

  • 이은정;김태근
    • 환경영향평가
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    • 제28권6호
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    • pp.536-548
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    • 2019
  • 기타 수계 중 삽교천 유역에 새롭게 수립된 오염총량관리제도의 시행에 따른 효과를 정량화하기 위해 2015년을 기준으로 유역유출모형인 HSPF 모형을 구축한 후, 최종 목표연도인 2030년의 부하량을 입력하여 각 단위유역 말단에 설정된 목표수질 달성여부를 평가하였으며, 미시행지역인 무한천과 삽교천 유역을 포함하여 유량구간별 수질(BOD, T-P)을 예측하였다. 보정 및 검증이 완료된 모형에 2030년의 부하량을 입력하여 재구동한 후, 모의결과로부터 부하지속곡선을 작성함으로써 기준년도 부하량을 입력하여 구동한 모의 수질과 목표연도 부하량을 입력하여 모의한 예측 수질을 유량구간별로 도식화한 결과, 평수량 구간(40~60%)에서 3개의 단위유역 모두 BOD 목표수질에 근접하게 모의되었으며, 목표수질 달성율도 높게 산정되었다. T-P의 경우, 천안A 46%, 곡교A 29%, 남원A 25% 정도의 수질이 개선되는 것으로 예측되었으며, 무한천과 삽교천유역은 중권역 목표기준인 III등급 이내의 수질로 모의되었다. 총량관리 대상 단위유역은 목표수질을 달성하고, 미시행지역은 목표등급을 달성하는 수준의 수질이 삽교호 내로 유입될 것으로 예측됨으로써 총량제 시행에 따른 삽교천 유역의 수질개선효과가 긍정적일 것으로 판단된다.

댐운영에 따른 하류하천 유량의 공간적 변동성 평가 (Effect of Dam Operation on the Spatial Variability of Downstream Flow)

  • 이정은;이정우;김철겸;정일문
    • 지질공학
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    • 제33권4호
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    • pp.627-638
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    • 2023
  • 본 연구에서는 김천부항댐이 위치한 감천유역을 대상으로 댐운영에 따른 하류하천 유량의 공간적인 변동성을 평가하고자 하였다. 특히, 다목적댐의 주요기능인 치수적인 측면에서의 홍수저감과 이수적인 측면에서의 갈수기 유량확보 효과를 정량적으로 분석하였다. 대상유역에 대하여 SWAT-K 모델링을 수행하여, 댐 하류하천의 4개 수위관측지점 관측유량과 모의유량을 비교한 결과, R2와 NSE 모두 0.75 이상의 적합도를 확보하였다. 댐의 홍수저감효과의 공간적 분석을 위해 연최대 홍수량을 중심으로 분석한 결과, 4개 지점에서의 홍수저감율은 8.5~25.0%로 나타났다. 갈수기 유량확보 효과에 대해서는 유황곡선을 중심으로 평가하였으며, 특히 평균갈수량의 경우에는 33~198%의 유량증가가 이루어짐을 알 수 있었다.

유역모형을 이용한 유량조건별 배출계수 산정 및 활용방안 연구 (Study on Estimation and Application of Discharge Coefficient about Nonpoint Source Pollutants using Watershed Model)

  • 황하선;이한필;박지형;김용석;이성준;안기홍
    • 한국물환경학회지
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    • 제31권6호
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    • pp.653-664
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    • 2015
  • TPLMS (Total water pollutant load management system) that is the most powerful water-quality protection program have been implemented since 2004. In the implementation of TPLMS, target water-quality and permissible discharged load from each unit watershed can be decided by water-quality modeling. And NPS (Non-point sources) discharge coefficients associated with certain (standard) flow are used on estimation of input data for model. National Institute of Environmental Research (NIER) recommend NPS discharge coefficients as 0.15 (Q275) and 0.50 (Q185) in common for whole watershed in Korea. But, uniform coefficient is difficult to reflect various NPS characteristics of individual watershed. Monthly NPS discharge coefficients were predicted and estimated using surface flow and water-quality from HSPF watershed model in this study. Those coefficients were plotted in flow duration curve of study area (Palger stream and Geumho C watershed) with monthly average flow. Linear regression analysis was performed about NPS discharge coefficients of BOD, T-N and T-P associated with flow, and R2 of regression were distributed in 0.893~0.930 (Palger stream) and 0.939~0.959 (Geumho C). NPS Discharge coefficient through regression can be estimated flexibly according to flow, and be considered characteristics of watershed with watershed model.

강우자료 분석에 의한 소수력 발전소의 성능예측 (Performance Prediction of Small Hydropower Plant through Analyzing Rainfall Data)

  • 이철형;박완순;신동렬;정헌생
    • 태양에너지
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    • 제9권3호
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    • pp.81-91
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    • 1989
  • This study represents the method to predict the flow duration curve and primary design specifications of small hydropower plant at hydropower site through analyzing the monthly rainfall data. Weibull distribution was selected to characterize the rainfall data and Thiessen method was used to calculate monthly average flowrate at site. Application of these results, primary design specifications such as design flowrate, annual average load factor and utility factor, annual average hydropower density and annual electric energy production were estimated and discussed for surveyed site located in Daigi-ri, Kangwon province. And performance characteristic model of small hydro-power plant was applied to estimate these specifications.

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LSTM 딥러닝 예측기법과 SWAT을 이용한 유량지속곡선 도출 및 민감도 분석 (Derivation of Flow Duration Curve and Sensitivity analysis using LSTM deep learning prediction technique and SWAT)

  • 안성욱;최정렬;김병식
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2022년도 학술발표회
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    • pp.354-354
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    • 2022
  • 딥러닝(Deep Learning)은 일반적으로 인공신경망(Artificial Neural Network) 를 의미하는데, 이에 따른 결과는 데이터의 양, 변수, 학습모델의 학습횟수, 은닉층(Hidden Layer)의 개수 등 여러 요소로 인해 결정된다. 본 연구에서는 물리적 장기유출 모형인 SWAT의 결과를 참값으로 LSTM모형의 매개변수인 은닉층 갯수와 학습횟수등의 시나리오를 바탕으로 검보정을 수행하였으며, 최적의 목적함수를 갖는 매개변수를 도출하였다. 이를 이용하여 유량지속곡선을 도출한결과를 SWAT의 결과와 비교해본 결과 매우 높은 상관성을 도출하였으며 이를 통해 수자원분야에서 인공신경망의 활용 가능성을 확인하였다.

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TANK 모형의 매개변수 추정을 위한 베이지안 접근법의 적용: MCMC 및 GLUE 방법의 비교 (Application of Bayesian Approach to Parameter Estimation of TANK Model: Comparison of MCMC and GLUE Methods)

  • 김령은;원정은;최정현;이옥정;김상단
    • 한국물환경학회지
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    • 제36권4호
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    • pp.300-313
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    • 2020
  • The Bayesian approach can be used to estimate hydrologic model parameters from the prior expert knowledge about the parameter values and the observed data. The purpose of this study was to compare the performance of the two Bayesian methods, the Metropolis-Hastings (MH) algorithm and the Generalized Likelihood Uncertainty Estimation (GLUE) method. These two methods were applied to the TANK model, a hydrological model comprising 13 parameters, to examine the uncertainty of the parameters of the model. The TANK model comprises a combination of multiple reservoir-type virtual vessels with orifice-type outlets and implements a common major hydrological process using the runoff calculations that convert the rainfall to the flow. As a result of the application to the Nam River A watershed, the two Bayesian methods yielded similar flow simulation results even though the parameter estimates obtained by the two methods were of somewhat different values. Both methods ensure the model's prediction accuracy even when the observed flow data available for parameter estimation is limited. However, the prediction accuracy of the model using the MH algorithm yielded slightly better results than that of the GLUE method. The flow duration curve calculated using the limited observed flow data showed that the marginal reliability is secured from the perspective of practical application.