• 한국농공학회:학술대회논문집
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• 한국농공학회 2001년도 학술발표회 발표논문집
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• pp.93-98
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• 2001

This study was performed to analyse the rainfall and the rainfall-runoff characteristics of a rural watershed. The Sangwha basin($105.9km^{2}$) in the Geum river system was selected for this study. The arithmetic mean method, the Thiessen's weighing method, and the isohyetal method were used to analyse areal rainfall distribution and the Huff's quartile method was used to analyse temporal rainfall distribution. In addition, daily runoff analyses were peformed using the DAWAST and tank model. In the model calibration, the data from June through November, 1999 were used. In the model calibration, the observed runoff depth was 513.7mm and runoff rate was 45.2%, and the DAWAST model simulated runoff depth was 608.6mm and runoff rate was 53.5%, and the tank model runoff depth was 596.5mm and runoff rate was 52.5%, respectively. In the model test, the data from June through November, 2000 were used. In the model test, the observed runoff depth was 1032.3mm and runoff rate was 72.5%, and the DAWAST model simulated runoff depth was 871.6mm and runoff rate was 61.3%, and the tank model runoff depth was 825.4mm and runoff rate was 58%, respectively. The DAWAST and tank model's $R^{2}$ and RMSE were 0.85, 3.61mm, and 0.85, 2.77mm in 1999, and 0.83, 5.73mm, and 0.87, 5.39mm in 2000, respectively. Both models predicted low flow runoff better than flood runoff.

• 환경영향평가
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• 제15권6호
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• pp.435-441
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• 2006

For the calibration of rainfall-runoff model, automatic calibration methods are used instead of manual calibration to obtain the reliable modeling results. When mathematical programming techniques such as linear programming and nonlinear programming are applied, there is a possibility to arrive at the local optimum. To solve this problem, genetic algorithm is introduced in this study. It is very simple and easy to understand but also applicable to any complicated mathematical problem, and it can find out the global optimum solution effectively. The objective of this study is to develope a parameter optimization program that integrate a genetic algorithm and a rainfall-runoff model. The program can calibrate the various parameters related to the runoff process automatically. As a rainfall-runoff model, SWMM is applied. The automatic calibration program developed in this study is applied to the Jangcheon watershed flowing into the Youngrang Lake that is in the eutrophic state. Runoff surveys were carried out for two storm events on the Jangcheon watershed. The peak flow and runoff volume estimated by the calibrated model with the survey data shows good agreement with the observed values.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2012년도 학술발표회
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• pp.976-976
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• 2012

The applicability of a distributed rainfall-runoff model for large river basin flood forecasts is analyzed by applying the model to the Nakdong River basin. The spatially explicit hydrologic model was constructed and calibrated by the several storm events. The assimilation of the large scale Nakdong River basin were conducted by calibrating the sub-basin channel outflow, dam discharge in the basin rainfall-runoff model. The applicability of automatic and semi-automatic calibration methods was analyzed for real time calibrations. Further an ensemble distributed rainfall runoff model has been developed to measure the runoff hydrograph generated for any temporally-spatially varied rainfall events, also the runoff of basin can be forecast at any location as well. The results of distributed rainfall-runoff model are very useful for flood managements on the large scale basins. That offer facile, realistic management method for the avoiding the potential flooding impacts and provide a reference for the construct and developing of flood control facilities.

• 한국농공학회논문집
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• 제60권1호
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• pp.47-57
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• 2018

This study implemented the rainfall-runoff analysis of the Mekong River basin using the SWAT (Soil and Water Assessment Tool). The runoff analysis was simulated for 2000~2007, and 11 parameters were calibrated using the SUFI-2 (Sequential Uncertainty Fitting-version 2) algorithm of SWAT-CUP (Calibration and Uncertainty Program). As a result of analyzing optimal parameters and sensitivity analysis for 6 cases, the parameter ALPHA_BF was found to be the most sensitive. The reproducibility of the rainfall-runoff results decreased with increasing number of stations used for parameter calibration. The rainfall-runoff simulation results of Case 6 showed that the RMSE of Nong Khai and Kratie stations were 0.97 and 0.9, respectively, and the runoff patterns were relatively accurately simulated. The runoff patterns of Mukdahan and Khong Chaim stations were underestimated during the flood season from 2004 to 2005 but it was acceptable in terms of the overall runoff pattern. These results suggest that the combination of SWAT and SWAT-CUP models is applicable to very large watersheds such as the Mekong for rainfall-runoff simulation, but further studies are needed to reduce the range of modeling uncertainty.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.208-208
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• 2022

Recently, the frequency of abnormal weather due to complex factors such as global warming is increasing frequently. From the past rainfall patterns, it is evident that climate change is causing irregular rainfall patterns. This phenomenon causes difficulty in predicting rainfall and makes it difficult to prevent and cope with natural disasters, casuing human and property damages. Therefore, accurate rainfall estimation and rainfall occurrence time prediction could be one of the ways to prevent and mitigate damage caused by flood and drought disasters. However, rainfall prediction has a lot of uncertainty, so it is necessary to understand and reduce this uncertainty. In addition, when accurate rainfall prediction is applied to the rainfall-runoff model, the accuracy of the runoff prediction can be improved. In this regard, this study aims to increase the reliability of rainfall prediction by analyzing the uncertainty of the Korean rainfall ensemble prediction data and the outflow analysis model using the Limited Area ENsemble (LENS) and the Grid based Rainfall-runoff Model (GRM) models. First, the possibility of improving rainfall prediction ability is reviewed using the QM (Quantile Mapping) technique among the bias correction techniques. Then, the GRM parameter calibration was performed twice, and the likelihood-parameter applicability evaluation and uncertainty analysis were performed using R², NSE, PBIAS, and Log-normal. The rainfall prediction data were applied to the rainfall-runoff model and evaluated before and after calibration. It is expected that more reliable flood prediction will be possible by reducing uncertainty in rainfall ensemble data when applying to the runoff model in selecting behavioral models for user uncertainty analysis. Also, it can be used as a basis of flood prediction research by integrating other parameters such as geological characteristics and rainfall events.

• 한국습지학회지
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• 제11권2호
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• pp.107-121
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• 2009

현재 홍수예보를 위하여 많은 강우-유출 모형이 사용되고 있으나, 이러한 모형의 매개변수를 결정하는 것은 매우 난해하다. 본 연구에서는 저류함수모형과 Tank 모형, SSARR 모형을 이용하여 미호천 유역에 대하여 홍수모의 예측을 수행하고 그 효율성을 분석하였다. 연구에 적용된 강우-유출 모형에 최적화 방법을 적용하여 매개 변수 산정을 수행하였으며, 패턴탐색과 유전자 알고리즘의 최적화 방법을 적용 시, 보정과정 내에서 매개변수 간 민감도를 분석하고 이를 바탕으로 매개변수를 소군집으로 분류하여 민감도에 따른 순차 보정 방법을 적용하고 이 결과를 비교 분석하였다. 매개변수 소군집을 이용한 보정 방법과 기존에 사용되는 매개변수 군집을 이용한 보정 방법을 비교한 결과, SSR에 소군집을 이용한 순차보정 방법을 적용하였을 때 첨두 유량과 보정 시간 면에서 유리한 것으로 나타났다.

• 한국농공학회지
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• 제45권2호
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• pp.45-57
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• 2003

An artificial neural network model was developed to analyze and forecast Short-term river runoff from the Naju watershed, in Korea. Error back propagation neural networks (EBPN) of hourly rainfall and runoff data were found to have a high performance In forecasting runoff. The number of hidden nodes were optimized using total error and Bayesian information criterion. Model forecasts are very accurate (i.e., relative error is less than 3% and $R^2$is greater than 0.99) for calibration and verification data sets. Increasing the time horizon for application data sets, thus mating the model suitable for flood forecasting. decreases the accuracy of the model. The resulting optimal EBPN models for forecasting hourly runoff consists of ten rainfall and four runoff data(ANN0410 model) and ten rainfall and ten runoff data(ANN1010 model). Performances of the ANN0410 and ANN1010 models remain satisfactory up to 6 hours (i.e., $R^2$is greater than 0.92).

• 대한토목학회논문집
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• 제28권1B호
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• pp.1-9
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• 2008

소양강댐 유역의 관측유입량과 융설 모의의 포함 유무에 따른 모의 결과를 비교함으로써 적설 및 융설 모형의 필요성을 분석하였다. 사용한 융설 모형은 Sugawara 등의 개념적 융설 모형이고, 강우-유출 모형은 NWS-PC를 사용하였다. 모형의 매개변수는 다단계 자동보정법에 의해 추정하였고, 각 단계별로 SCE-UA 알고리즘에 의해 최적화되었다. 매개변수 추정시와 검증 모의에서 RMSE, PBIAS, NSE, PME 통계량은 융설을 포함한 모의가 그렇지 않은 모의보다 좋은 결과를 나타내었다. 소양강댐의 관측유입량은 약 두 달 이상의 자기상관성을 나타내었고, 융설을 포함하지 않은 경우에 모의된 유량시계열은 20일 정도의 자기상관성을 나타내었다. 융설을 포함한 경우의 모의유량 시계열은 관측 유량시계열과 유사하게 약 두 달 이상의 자기상관성을 나타내었다. 이와 같은 결과로 소양강댐 유역의 강우-유출 모의시 적설 및 융설 모형을 포함하여야 모형의 정확성을 향상시킬 수 있다.

• 한국수자원학회논문집
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• 제32권6호
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• pp.657-664
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• 1999

본 논문은 이상호와 이길성(1995)에 의해서 제안된 LRCS(Linear Reservoir and Channel System) 강우-유출 모형의 기본 이론을 소개하였고, 모형의 민감도 분석 및 보정과정에서 나타나는 목적함수에 따른 모형 출력의 변화를 파악하고자 하였다. 보정시 매개변수 영향성 분석을 위한 "hat" 행렬과 영향성 척도의 사용을 제안하였고, 매개변수 추정시 오차 전파에 따른 모형 출력의 변화 정도 및 모형 예측치 분산과 매개변수 변화에 따른 모형 출력의 민감도와의 관련성을 조사하였다. 민감도계수와 hi의 대각 요소와 Di 값의 분석으로 매개변수 추정치의 정확성을 알 수 있었다.을 알 수 있었다.

• 한국농공학회논문집
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• 제53권6호
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• pp.171-183
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• 2011

Temporal and spatical surface runoff by heavy rainfall during 25~28 July, 2011 causing urban flooding at Seoul were analyzed using Long-Term Hydrologic Impact Assessment (L-THIA). L-THIA was calibrated for 1988~1997 and validated for 1998~2007 using monthly observed data at Hangangseoul watershed which covers 90 % of Seoul city. As a results of calibration and validation of L-THIA at Hangangseoul watershed, Nash-Sutcliffe coefficients were 0.99 for calibration and 0.99 for validation. The simulated values were good agreement with observed data and both calibrated and validated levels were "very good" based on calibration criteria. The calibrated curve number (CN) values of residential and other urban area represented 87 % and 93 % of impervious area, respectively, which were maximum percentage of impervious area. As a result of L-THIA application at Seoul city during 25~28 July, 2011, most of rainfall (54 %, 287.49 mm) and surface runoff (65 %, 247.32) were generated at 27 July, 2011 and a significant amount of rainfall and surface runoff were occurred at southeastern Seoul city. As a result of bi-hourly spatial and temporal analysis during 27 July, 2011, surface runoff during 2:00~4:00 and 8:00~10:00 were much higher than those during other times and surface runoff located at Seocho-gu during 6:00~8:00 represented maximum value with maximum rainfall intensity which caused landslide from Umyun mountain.