• Title/Summary/Keyword: flood runoff

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Flood Runoff Computation for Mountainous Small Basins using HEC-HMS Model (HEC-HMS 모델을 이용한 산지 소하천유역의 홍수유출량 산정)

  • Chang, In-Soo
    • Journal of the Korean Society of Industry Convergence
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    • v.7 no.3
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    • pp.281-288
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    • 2004
  • The objective of this study is to propose a methodology of the flood runoff analysis in steep mountainous basins and the analysis basin is the Jasa valley basin in Chungju city Analyzing the spatial pattern of the rainfall in 1994. 6 30~7.1, the seasonal rainy front was tied up in the whole central district, and the rainfall center was moving from the northern Chungbuk province to the northern Kyongbuk province and caused heavy storm. Analyzing the temporal pattern with the Huff method, the 52.5% of the rainfall was concentrated on the 3rd quartile. Rainfall frequency analysis is accomplished by five distribution types; 2-parameter Lognomal, 3-parameter Lognomal, Pearson Type III, Log-Pearson Type III and Extremal Type I distribution Rainfall-runoff analysis in Jasa valley basin was made using HEC-HMS model. Jasa valley basin was divided into 3 sub-basins and the analysis point was 3 points{A, B and C point) With the rainfall data measured by the 10 minutes, the flood runoff also was calculated by as many minutes. SCS CN model, Clark UH model and Muskingum routing model in HEC-HMS model were used to simulate the runoff volume using selected rainfall event.

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Spatio-temporal dependent errors of radar rainfall estimate for rainfall-runoff simulation

  • Ko, Dasang;Park, Taewoong;Lee, Taesam;Lee, Dongryul
    • Proceedings of the Korea Water Resources Association Conference
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    • 2016.05a
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    • pp.164-164
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    • 2016
  • Radar rainfall estimates have been widely used in calculating rainfall amount approximately and predicting flood risks. The radar rainfall estimates have a number of error sources such as beam blockage and ground clutter hinder their applications to hydrological flood forecasting. Moreover, it has been reported in paper that those errors are inter-correlated spatially and temporally. Therefore, in the current study, we tested influence about spatio-temporal errors in radar rainfall estimates. Spatio-temporal errors were simulated through a stochastic simulation model, called Multivariate Autoregressive (MAR). For runoff simulation, the Nam River basin in South Korea was used with the distributed rainfall-runoff model, Vflo. The results indicated that spatio-temporal dependent errors caused much higher variations in peak discharge than spatial dependent errors. To further investigate the effect of the magnitude of time correlation among radar errors, different magnitudes of temporal correlations were employed during the rainfall-runoff simulation. The results indicated that strong correlation caused a higher variation in peak discharge. This concluded that the effects on reducing temporal and spatial correlation must be taken in addition to correcting the biases in radar rainfall estimates. Acknowledgements This research was supported by a grant from a Strategic Research Project (Development of Flood Warning and Snowfall Estimation Platform Using Hydrological Radars), which was funded by the Korea Institute of Construction Technology.

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Flood Runoff Estimation for the Streamflow Stations in Namgang-Dam Watershed Considering Forest Runoff Characteristics (산림지역의 유출특성을 고려한 남강댐유역내 주요 하천관측지점에 대한 홍수유출량 추정)

  • Kim, Sung-Jae;Park, Tae-Yang;Jang, Min-Won;Kim, Sang-Min
    • Journal of The Korean Society of Agricultural Engineers
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    • v.52 no.6
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    • pp.85-94
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    • 2010
  • The objective of this study is to estimate the flood runoff for three guaged stations within Namgang-Dam watershed which are operated by KWATER. For a flood runoff simulation, HEC-HMS was applied and the simulated runoff was compared with observed from 2004 to 2008. The watershed area of Sancheong, Shinan, and Changchon were 693.6 $km^2$, 413.4 $km^2$, and 346.48 $km^2$, respectively. The average runoff ratio of observed runoff for three watersheds were 0.725, 0.418, and 0.586, respectively. The dominant land cover of three watersheds are forest with the value of 71.6 %, 73.1 %, and 82.0 %. Three different cases according to the potential maximum retention of forest areas for calculating the curve number were applied to decrease the error between the simulated and observed. The simulated peak runoff of case 3 which applied the 90 % of potential maximum retention of curve number which is equivalent to AMCI for all the AMCI, AMCII, and AMCIII conditions showed least root mean square error (RMSE). The case 1, which was suggested by previous study, showed high discrepancy between the simulated and observed. Since the forest area consists of more than 70 % for all three watersheds, the application of curve number for forest is critical to improve the estimation errors. Further research is required to estimate the more accurate curve number for forest area.

Flood Runoff Analysis using a Distributed Rainfall Runoff Model (분포형 유출모형을 이용한 홍수유출해석)

  • Jo, Hong-Je;Jo, In-Ryul
    • Journal of Korea Water Resources Association
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    • v.31 no.2
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    • pp.199-208
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    • 1998
  • This study is on the application of TOPMDEL(Topographic based hydrologic model) Which is a distributed rainfall-runoff model to the flood runoff analysis. The test area was Wichun experimental catchment site which is mountainous mid-area (Dongok, 33.63$\textrm{km}^2$ and Goro, 109,725 $\textrm{km}^2$) and being operated by the Ministry of Construction and ransporation. A three-dimensional digital elevation model(DEM) map was constructed using a physiographic map(1/25,000) and GIS software, Arc/Info, was used to the analysis of geofraphic factors. The topographic index of Dongok and Goro subcatchment was similar. As a results of the analysis, the model was validated that the simulated peak flow of a flood runoff was fit to the observed data. For the analysis of the effects of grid size, Dongok subcatchment was divided into 100,120-,240 m grid and Goro subcatchment was divided into grid and 120,200,350 m grid. It was shown that the peak flow increased in proportion to the increases of the grid size, but peak times were constant regardless of the grid size in both of the watershed.

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Uncertainty Analysis based on LENS-GRM

  • Lee, Sang Hyup;Seong, Yeon Jeong;Park, KiDoo;Jung, Young Hun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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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.

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Calculation of the Flood Runoff of the River with Imaging Equipments (영상장비를 활용한 하천의 홍수유출량 산정)

  • Kang, Bo-Seong;Yang, Sung-Kee;Jung, Woo-Yeol;Kim, Yong-Seok
    • Journal of Environmental Science International
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    • v.23 no.4
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    • pp.585-594
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    • 2014
  • This study Analyzed four of seven runoffs which had happened in 2012 in comparison with the runoffs shown in Kalesto data, using the fixed surface image velocimetry (FSIV) installed at Oedo stream, Jeju Island. As a result of identifying a runoff curve graph, it was analyzed that the flood runoffs calculated with two observation devices were almost equivalent. As the differences in peak flows were 10 $m^3/s$, 0.7 $m^3/s$ and 3 $m^3/s$, the very similar result values were calculated. Even though there were errors in RMSE(Root Mean Square Error) made by two observation devices according to the degree of the peak flow, the values of $R^2$ by flood event were 0.89, 0.87, 0.86 and 0.82, showing the result values almost close to 1. Therefore, there was a very high correlation in flood runoffs calculated with two observation devices. This research method was considered to be a very suitable method to measure unexpected flood runoffs which could happen in the island area such as Jeju island during bad weather.

Improved Parameter Computation Method Applications of Storage Function Model for the Han River Basin (저류함수모형 매개변수 산정 개선방법의 한강유역 적용)

  • Jeong, Dong-Kug;Jeon, Yong-Woon;Lee, Beum-Hee
    • Journal of the Korean Society of Hazard Mitigation
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    • v.8 no.2
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    • pp.149-158
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    • 2008
  • The parameters of each basin, required for the accurate analysis of flood runoff using Storage Function Model, are estimated. Prior to the estimation, sensitivity analysis and extraction of new regional topographic factors for Han River basin are conducted. Based on the result, the outflow constant of basin model is calculated through regression analysis in relation with pre-flood runoff depth. The storage constant of basin model is derived by the optimum storage constant equation, according to the flood event of each basin. The model using the mentioned parameters was compared with K-Water model of Korea Water Resources Corporation and the model of Han River Flood Control Office, and proved to correspond to the observed hydrograph more.

Parameter Optimization of Long and Short Term Runoff Models Using Genetic Algorithm (유전자 알고리즘을 이용한 장·단기 유출모형의 매개변수 최적화)

  • Kim, Sun-Joo;Jee, Yong-Geun;Kim, Phil-Shik
    • Journal of The Korean Society of Agricultural Engineers
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    • v.46 no.5
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    • pp.41-52
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    • 2004
  • In this study, parameters of long and short term runoff model were optimized using genetic algorithm as a basic research for integrated water management in a watershed. In case of Korea where drought and flood occurr frequently, the integrated water management is necessary to minimize possible damage of drought and flood. Modified TANK model was optimized as a long term runoff model and storage-function model was optimized as a short term runoff model. Besides distinguished parameters were applied to modified TANK model for supplementing defect that the model estimates less runoff in the storm period. As a result of application, simulated long and short term runoff results showed 7% and 5% improvement compared with before optimized on the average. In case of modified TANK model using distinguished parameters, the simulated runoff after optimized showed more interrelationship than before optimized. Therefore, modified TANK model can be applied for the long term water balance as an integrated water management in a watershed. In case of storage-function model, simulated runoff in the storm period showed high interrelationship with observed one. These optimized models can be applied for the runoff analysis of watershed.

Application of a Distributed Model for Evaluating the Effect of Sacheonman Spillway on the Flood Reduction in the Downstream of Namgang Dam (사천만 방수로가 남강댐 하류의 홍수량 저감에 미치는 영향 평가를 위한 분포형 모형의 적용)

  • Choi, Cheon Kyu;Choi, Yun Seok;Kim, Kyung Tak
    • Journal of Wetlands Research
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    • v.14 no.3
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    • pp.399-411
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    • 2012
  • Namgang Dam is located in the upstream of Nam river. Namgang Dam controls flood for the downstream of Namgang Dam using the Namgang spillway and the Sacheonman spillway with planned discharge. However, it had not been evaluated adequately that the effect of the discharge through Sacheonman spillway on the flood reduction of the downstream of Namgang Dam. This study performs runoff simulation considering the discharge from Namgang Dam and Sacheonman spillway. And modeling results are evaluated for the flood reduction effect of Sacheonman spillway on the downstream of Namgang Dam. This study uses a distributed model, GRM(Grid based Rainfall-runoff Model) for runoff analysis. As a result, Sacheonman spillway is assigned more discharge than Namgang Dam, and Sacheonman spillway greatly affects flood reduction in the downstream of Namgang Dam.

An Analysis for Goodness of Fit on Trigger Runoff of Flash Flood and Topographic Parameters Using GIS (GIS를 이용한 돌발홍수의 한계유량과 유역특성인자의 적합도 분석)

  • Oh, Myung-Jin;Yang, In-Tae;Park, Byung-Soo
    • Journal of Korean Society for Geospatial Information Science
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    • v.14 no.3 s.37
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    • pp.87-95
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    • 2006
  • Recently, local heavy rain for a short term is caused by unusual changing in the weather. This phenomenon has, several times, caused an extensive flash flood, casualties, and material damage. This study is aimed at calculating the characteristics of flash floods in streams. For this purpose, the analysis of topographical characteristics of water basin through applying GIS techniques will be conducted. The flash flood prediction model we used is made with GCIUH (geomorphoclimatic instantaneous unit hydrograph). The database is established by the use of GIS and by the extraction of streams and watersheds from DEM. The streams studied are included small, middle and large scale watersheds. For the first, for the establishment or criteria on the flash flood warning, peak discharge and trigger runoff must be decided. This study analyzed the degree or aptitude of topographical factors to the trigger runoff calculated by GCUH model.

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