• Title/Summary/Keyword: 첨두유출량

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SWAT model calibration/validation using SWAT-CUP I: analysis for uncertainties of objective functions (SWAT-CUP을 이용한 SWAT 모형 검·보정 I: 목적함수에 따른 불확실성 분석)

  • Yu, Jisoo;Noh, Joonwoo;Cho, Younghyun
    • Journal of Korea Water Resources Association
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    • v.53 no.1
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    • pp.45-56
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    • 2020
  • This study aims to quantify the uncertainty that can be induced by the objective function when calibrating SWAT parameters using SWAT-CUP. SWAT model was constructed to estimate runoff in Naesenong-cheon, which is the one of mid-watershed in Nakdong River basin, and then automatic calibration was performed using eight objective functions (R2, bR2, NS, MNS, KGE, PBIAS, RSR, and SSQR). The optimum parameter sets obtained from each objective function showed different ranges, and thus the corresponding hydrologic characteristics of simulated data were also derived differently. This is because each objective function is sensitive to specific hydrologic signatures and evaluates model performance in an unique way. In other words, one objective function might be sensitive to the residual of the extreme value, so that well produce the peak value, whereas ignores the average or low flow residuals. Therefore, the hydrological similarity between the simulated and measured values was evaluated in order to select the optimum objective function. The hydrologic signatures, which include not only the magnitude, but also the ratio of the inclining and declining time in hydrograph, were defined to consider the timing of the flow occurrence, the response of watershed, and the increasing and decreasing trend. The results of evaluation were quantified by scoring method, and hence the optimal objective functions for SWAT parameter calibration were determined as MNS (342.48) and SSQR (346.45) with the highest total scores.

Design of Edtention Pond and Critical Duration of Design Rainfall in Seoul (유수지 설계를 위한 계획강우의 임계지속기간 -서울 지역을 중심으로-)

  • 이종태;윤세의
    • Water for future
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    • v.26 no.1
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    • pp.115-124
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    • 1993
  • This study is to determine the critical duration of design rainfall and to utilize it for the design of detention pond with pump station. To examine the effect of the duration and temporal distribution of the design rainfall, Huff's quartile method is used for the 9 cases of durations ranging from 20 to 240 minutes with 10 years return period, and the ILLUDAS model is used for runoff analysis. The storage ration which is the ratio of maximum storage amounts to total runoff volume, is introduced to determine the critical duration of design rainfall. The duration which maximizes the storage ratio is adopted as the critical duration. This study is applied to 18 urban drainage watersheds with pump station in Seoul, of which the range of watershed area is $0.24-12.70\textrm{km}^2.$ The result of simulation shows that the duration which maximizes storage ration is 30 and 60 minutes on the whole. It is shown also that the storage ration of 2nd- and 3rd-quartile pattern is larger than that of 1st- and 4th-quartile pattern of temporal distribution. A simplified empirical formula for Seoul area is suggested by using the regression analysis between the maximum storage ration and the peak ratio, and can be utilized for the preliminary design and planning of detention pond with pump station.

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A Study on the Public Evacuation Time Estimates for Radiological Emergency Plan and Preparedness of Wolsong Nuclear Power Plant Site (방사선 비상계획을 위한 월성원전 주변 주민 소개시간 예측 연구)

  • Lee, Gab-Bock;Bang, Sun-Young;Chung, Yang-Geun
    • Journal of Radiation Protection and Research
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    • v.32 no.2
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    • pp.79-88
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    • 2007
  • When an accident occurs at nuclear power plant and radionuclide material is released to the area around the plant, public evacuation is considered as a measure to protect the safety of the residents nearby. This study draws factors required to estimate evacuation time and make estimation of the time to evacuate all residents from the EPZ of Wolsong site in consideration of traffic condition in the neighborhood and on the basis of field data around the site for each factor. The traffic capacity and the traffic volume by season were investigated for the traffic analysis and simulation within EPZ of Wolsong site. As a result, the background traffic volume by season were established. To estimate TGT(Trip Generation Time), the questionnaire surveys were carried out for resident and transient. The TSIS code was applied to traffic analysis in the events of daytime/night and normal/adverse weather under normal day/summer peak traffic condition. The results showed that the evacuation time required for total vehicles to move out from EPZ took generally from 118 to 150 minutes. The evacuation time took longer maximum 17 minutes at night than daytime during summer peak traffic.

Application of Proxy-basin Differential Split-Sampling and Blind-Validation Tests for Evaluating Hydrological Impact of Climate Change Using SWAT (SWAT을 이용한 기후변화의 수문학적 영향평가를 위한 Proxy-basin Differential Split-Sampling 및 Blind-Validation 테스트 적용)

  • Son, Kyong-Ho;Kim, Jeong-Kon
    • 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.

Comparative analysis of activation functions of artificial neural network for prediction of optimal groundwater level in the middle mountainous area of Pyoseon watershed in Jeju Island (제주도 표선유역 중산간지역의 최적 지하수위 예측을 위한 인공신경망의 활성화함수 비교분석)

  • Shin, Mun-Ju;Kim, Jin-Woo;Moon, Duk-Chul;Lee, Jeong-Han;Kang, Kyung Goo
    • Journal of Korea Water Resources Association
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    • v.54 no.spc1
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    • pp.1143-1154
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    • 2021
  • The selection of activation function has a great influence on the groundwater level prediction performance of artificial neural network (ANN) model. In this study, five activation functions were applied to ANN model for two groundwater level observation wells in the middle mountainous area of the Pyoseon watershed in Jeju Island. The results of the prediction of the groundwater level were compared and analyzed, and the optimal activation function was derived. In addition, the results of LSTM model, which is a widely used recurrent neural network model, were compared and analyzed with the results of the ANN models with each activation function. As a result, ELU and Leaky ReLU functions were derived as the optimal activation functions for the prediction of the groundwater level for observation well with relatively large fluctuations in groundwater level and for observation well with relatively small fluctuations, respectively. On the other hand, sigmoid function had the lowest predictive performance among the five activation functions for training period, and produced inappropriate results in peak and lowest groundwater level prediction. The ANN-ELU and ANN-Leaky ReLU models showed groundwater level prediction performance comparable to that of the LSTM model, and thus had sufficient potential for application. The methods and results of this study can be usefully used in other studies.