• Journal of Wetlands Research
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• v.11 no.1
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• pp.49-64
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• 2009

Rainfall-runoff models are used for efficient management, distribution, planning, and design of water resources in accordance with the process of hydrologic cycle. The models simplify the transition of rainfall to runoff as rainfall through different processes including evaporation, transpiration, interception, and infiltration. As the models simplify complex physical processes, gaps between the models and actual rainfall events exist. For more accurate simulation, appropriate models that suit analysis goals are selected and reliable long-term hydrological data are collected. However, uncertainty is inherent in models. It is therefore necessary to evaluate reliability of simulation results from models. A number of studies have evaluated uncertainty ingrained in rainfall-runoff models. In this paper, Meta-Gaussian method proposed by Montanari and Brath(2004) was used to assess uncertainty of simulation outputs from rainfall-runoff models. The model, which estimates upper and lower bounds of the confidence interval from probabilistic distribution of a model's error, can quantify global uncertainty of hydrological models. In this paper, Meta-Gaussian method was applied to analyze uncertainty of simulated runoff outputs from $Vflo^{TM}$, a physically-based distribution model and HEC-HMS model, a conceptual lumped model.

• Journal of Environmental Science International
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• v.19 no.10
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• pp.1211-1217
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• 2010

For an accurate rainfall-runoff simulation in the river basin, it is important to consider not only evaluation of runoff model but also accurate runoff component. In this study long-term runoffs were simulated by means of watershed runoff model and the amounts of runoff components such as upstream inflow, surface runoff, return flow and dam release were evaluated based on the concept of water budget. SSARR model was applied to Daecheong basin, the upstream region of Geum river basin, and in turn the monthly runoff discharges of main control points in the basin were analyzed. In addition, for the purpose of providing the basic quantified water resources data the conceptual runoff amounts were estimated with water budget analysis and the reliability of the observations and the monthly runoff characteristics were investigated in depth. The yearly runoff ratios were also estimated and compared with the observations. From the results of the main control points, Yongdam, Hotan, Okcheon and Daecheong, the yearly runoff ratios of those points are consistent well with data reported previously.

• Korean Journal of Agricultural Science
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• v.48 no.3
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• pp.433-446
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• 2021

In this study, the future flood inundation changes under a climate change were simulated in the Tonle Sap basin in Cambodia, one of the countries with high vulnerability to climate change. For the flood inundation simulation using the rainfall-runoff-inundation (RRI) model, globally available geological data (digital elevation model [DEM]; hydrological data and maps based on Shuttle elevation derivatives [HydroSHED]; land cover: Global land cover facility-moderate resolution imaging spectroradiometer [GLCF-MODIS]), rainfall data (Asian precipitation-highly-resolved observational data integration towards evaluation [APHRODITE]), climate change scenario (HadGEM3-RA), and observational water level (Kratie, Koh Khel, Neak Luong st.) were constructed. The future runoff from the Kratie station, the upper boundary condition of the RRI model, was constructed to be predicted using the long short-term memory (LSTM) model. Based on the results predicted by the LSTM model, a total of 4 cases were selected (representative concentration pathway [RCP] 4.5: 2035, 2075; RCP 8.5: 2051, 2072) with the largest annual average runoff by period and scenario. The results of the analysis of the future flood inundation in the Tonle Sap basin were compared with the results of previous studies. Unlike in the past, when the change in the depth of inundation changed to a range of about 1 to 10 meters during the 1997 - 2005 period, it occurred in a range of about 5 to 9 meters during the future period. The results show that in the future RCP 4.5 and 8.5 scenarios, the variability of discharge is reduced compared to the past and that climate change could change the runoff patterns of the Tonle Sap basin.

• Korean Journal of Ecology and Environment
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• v.43 no.3
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• pp.349-355
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• 2010

This study aims at the augmentation of reliability of the long-term rainfall runoff model. To do so agricultural water uses are evaluated by analyzing the effects of small scale irrigational hydraulic structures on long term runoff processes and thereby rainfall-runoff model is modified considering them. As a result the simulation results of the sub-basins having more agricultural reservoirs than the others are disagreed with the observations. The 2nd quarter simulation results show similar trend to it. Especially the farming seasonal results of the drought year as the year of 2008 have many negative discharge values due to the lack of agricultural water uses. This result come from the water uses input data corresponding to not real water uses but water demands. In this study the formulas are derived to estimate the discharges and return ratios and the long term rainfall-runoff model is reformulated based on these. It is confirmed that the errors of the simulation results could be reduced by considering the effects of small scale irrigational hydraulic structures and the reliability of the simulation results improved greatly.

• Journal of Korea Water Resources Association
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• v.39 no.11 s.172
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• pp.905-914
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• 2006

For an accurate rainfall-runoff simulation in the river basin, not evaluation of runoff model but accurate runoff data are very important. In this study, SSARR model was applied to the Geum River basin and these results are compared with runoff data observed at the Gongju gauging station. The model results didn't good fit the discharge data determined from the rating curve at Gongju gauging station during normal and dry season, especially. For the reliability analysis for the existing rating curve, we observed new stream discharge set from 2003 to 2005. We also estimated long term runoff data from the base flow separation method and defined the hydraulic characteristics. The results show that the new observed stream discharge is similar to the rainfall-runoff model results but existing rating curve seems to be overestimated about 10-20% during normal and dry season. We found that the continuous monitoring and update for the existing rating curve at the gaging station are needed for accurate estimation of runoff data.

• Water for future
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• v.24 no.3
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• pp.95-104
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• 1991

The study was focused on developing a new model to estimate annual runoff. This model can be used to estimate the available water resources for ungaged catchments for long-term water resources development planning. Data used in the model development were daily rainfall and daily runoff of the sample basin with record length from 1945 to 1988 years in Korea. The sample basin selected by consideration whether the flow is virgin and quality of discharge data is good. As a result, 46 stage gaging station were selected. Annual runoff was determined by sum of daily runoff calculated by daily stage data of the sample basin. Also, the annual mean precipitation by using daily rainfall data was estimated and the annual runoff ratio for each sample basin was calculated, and the annual mean runoff ratio was estimated. The linear regression model was proposed and calibrated using auunal mean precipitation values and geomorphological characteristics of the basins. To verify reasonableness of this model, the regression model was applied to the gaging stations which have historical data.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.97-104
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• 2009

GIS (Geographic Information System) is very useful in describing basin wide geographic characteristics and hydrologic analysis. This study estimated long term hydrologic variations in the Geum river basin using the SSARR rainfall runoff simulation model to provide reliable hydrologic information associated with rainfall runoff management module. Calibrated various hydrologic information such as soil moisture index, water use, direct and base flow are generated using GIS tools to display spatial hydrologic information in the unit of subbasin of target watershed. In addition, the graphic user interface toolkit designed for data compilation is expected to support efficient basin wide rainfall runoff analysis.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.6
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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.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.127-137
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• 2024

Physical models, which are often used for water resource management, are difficult to build and operate with input data and may involve the subjective views of users. In recent years, research using data-driven models such as machine learning has been actively conducted to compensate for these problems in the field of water resources, and in this study, an artificial neural network was used to simulate long-term rainfall runoff in the Osipcheon watershed in Samcheok-si, Gangwon-do. For this purpose, three input data groups (meteorological observations, daily precipitation and potential evapotranspiration, and daily precipitation - potential evapotranspiration) were constructed from meteorological data, and the results of training the LSTM (Long Short-term Memory) artificial neural network model were compared and analyzed. As a result, the performance of LSTM-Model 1 using only meteorological observations was the highest, and six LSTM-MLP ensemble models with MLP artificial neural networks were built to simulate long-term runoff in the Fifty Thousand Watershed. The comparison between the LSTM and LSTM-MLP models showed that both models had generally similar results, but the MAE, MSE, and RMSE of LSTM-MLP were reduced compared to LSTM, especially in the low-flow part. As the results of LSTM-MLP show an improvement in the low-flow part, it is judged that in the future, in addition to the LSTM-MLP model, various ensemble models such as CNN can be used to build physical models and create sulfur curves in large basins that take a long time to run and unmeasured basins that lack input data.

• Journal of Korea Water Resources Association
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• v.53 no.7
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• pp.493-505
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• 2020

The rainfall-runoff model has been generally adopted to obtain a consistent runoff sequence with the use of the long-term ground-gauged based precipitation data. The Thiessen polygon is a commonly applied approach for estimating the mean areal rainfall from the ground-gauged precipitation by assigning weight based on the relative areas delineated by a polygon. However, spatial bias is likely to increase due to a sparse network of the rain gauge. This study aims to generate continuous runoff sequences with the mean areal rainfall obtained from radar rainfall estimates through a PRMS rainfall-runoff model. Here, the systematic error of radar rainfall is corrected by applying the G/R Ratio. The results showed that the estimated runoff using the corrected radar rainfall estimates are largely similar and comparable to that of the Thiessen. More importantly, one can expect that the mean areal rainfall obtained from the radar rainfall estimates are more desirable than that of the ground in terms of representing rainfall patterns in space, which in turn leads to significant improvement in the estimation of runoff.