• Water for future
• /
• v.26 no.4
• /
• pp.117-125
• /
• 1993

A flood -flow management system model of river basin has been developed in this study. The system model consists of the observation and telemetering system, the rainfall forecasting and data-bank system, the flood runoff simulation system, the dam operation simulation system, the flood forecasting simulation system and the flood warning system. The Multivariate model(MV) and Meterological-factor regression model(FR) for rainfall forecasting and the Streamflow synthesis and reservoir regulation(SSARR) model for flood runoff simulation have been adopted for the development of a new system model for flood-flow management. These models are calibrated to determine the optimal parameters on the basis of observed rainfall, streamflow and other hydrological data during the past flood periods. The flood-flow management system model with SSARR model(FFMM-SR,FFMM-SR(FR) and FFMM-SR(MV)), in which the integrated operation of dams and rainfall forecasting in the basin are considered, is then suggested and applied for flood-flow management and forecasting. The results of the simulations done at the base stations are analysed and were found to be more accurate and effective in the FFMM-SR and FFMM0-SR(MV).

• Water for future
• /
• v.10 no.1
• /
• pp.79-94
• /
• 1977

This study is aimed at the establishment and examination of stochastic model to simulate Run-length and Run-sum of daily rainfall and streamflow. In the analysis, daily rainfall records in major cities (Seoul, Kangnung, Taegu, Kwangju, Busan, and Cheju) and daily streamflow records of Major rivers (Han, Nakdong and Geum River) were used. Also, the fitness of daily rainfall and streamflow to Weibull and one parameter exponential distribution was tested by Chi-square and Kolmogorov-Smirnov test, from which it was found that daily rainfall and streamflow generally fit well to exponential type distribution function. The Run-length and Run-sum were simulated by the Weibull Model (WBL Model), one parameter exponential model (EXP-1 Model) based on the Nonte Carlo technique. In this result, Run-length of rainfall was fitted for one parameter exponential model and Run-length of streamflow was fitted for Weibull model. And Run-sum of rainfall and streamflow were fit comparatively for regression model. Hereby, statistical charactristics of Simulation data were sinilar to historical data.

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

• Proceedings of the Korea Water Resources Association Conference
• /
• 2009.05a
• /
• pp.1142-1146
• /
• 2009

A rainfall simulation and forecasting technique that can generate daily rainfall sequences conditional on multi-model ensemble GCMs is developed and applied to data in Korea for the major rainy season. The GCM forecasts are provided by APEC climate center. A Weather State Based Downscaling Model (WSDM) is used to map teleconnections from ocean-atmosphere data or key state variables from numerical integrations of Ocean-Atmosphere General Circulation Models to simulate daily sequences at multiple rain gauges. The method presented is general and is applied to the wet season which is JJA(June-July-August) data in Korea. The sequences of weather states identified by the EM algorithm are shown to correspond to dominant synoptic-scale features of rainfall generating mechanisms. Application of the methodology to seasonal rainfall forecasts using empirical teleconnections and GCM derived climate forecast are discussed.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2009.05a
• /
• pp.540-544
• /
• 2009

Hydrologic pattern under climate change has been paid attention to as one of the most important issues in hydrologic science group. Rainfall and runoff is a key element in the Earth's hydrological cycle, and associated with many different aspects such as water supply, flood prevention and river restoration. In this regard, a main objective of this study is to evaluate design flood using simulation techniques which can consider a full spectrum of uncertainty. Here we utilize a weather state based stochastic multivariate model as conditional probability model for simulating the rainfall field. A major premise of this study is that large scale climatic patterns are a major driver of such persistent year to year changes in rainfall probabilities. Uncertainty analysis in estimating design flood is inevitably needed to examine reliability for the estimated results. With regard to this point, this study applies a Bayesian Markov Chain Monte Carlo scheme to the NWS-PC rainfall-runoff model that has been widely used, and a case study is performed in Soyang Dam watershed in Korea. A comprehensive discussion on design flood under climate change is provided.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2021.06a
• /
• pp.141-141
• /
• 2021

This study proposed an equation for Rainfall Threshold for Flood Warning (RTFW) for urban areas based on computer simulations. First, a coupled 1D-2D dual-drainage model was developed for nine watersheds in Seoul, Korea. Next, the model simulation was repeated for a total of 540 combinations of the synthetic rainfall events and watershed imperviousness (9 watersheds × 4 NRCS Curve Number (CN) values × 15 rainfall events). Then, the results of the 101 simulations with the critical flooded depth (0.25m-0.35m) were used to develop the equation that relates the value of RTFW to the rainfall event temporal variability (represented as coefficient of variation) and the watershed Curve Number. The results suggest that 1) the rainfall with greater temporal variability causes critical floods with less amount of total rainfall; and that 2) the greater imperviousness requires less rainfall to have critical floods. For validation, the proposed equation was applied for the flood warning system with two storm events occurred in 2010 and 2011 over 239 watersheds in Seoul. The results of the application showed high performance of the warning system in issuing the flood warning, with the hit, false and missed alarm rates at 68%, 32% and 7.4% respectively for the 2010 event and 49%, 51% and 10.7% for the event in 2011.

• Journal of Wetlands Research
• /
• v.12 no.1
• /
• pp.51-61
• /
• 2010

Changes in climate have largely increased concentrated heavy rainfall, which in turn is causing enormous damages to humans and properties. Therefore, it is important to understand the spatial-temporal features of rainfall. In this study, RADAR rainfall was used to calculate gridded areal rainfall which reflects the spatial-temporal variability. In addition, Kalman-filter method, a stochastical technique, was used to combine ground rainfall network with RADAR rainfall network to calculate areal rainfall. Thiessen polygon method, Inverse distance weighting method, and Kriging method were used for calculating areal rainfall, and the calculated data was compared with adjusted areal RADAR rainfall measured using the Kalman-filter method. The result showed that RADAR rainfall adjusted with Kalman-filter method well-reproduced the distribution of raw RADAR rainfall which has a similar spatial distribution as the actual rainfall distribution. The adjusted RADAR rainfall also showed a similar rainfall volume as the volume shown in rain gauge data. Anseong-Cheon basin was used as a study area and the RADAR rainfall adjusted with Kalman-filter method was applied in $Vflo^{TM}$ model, a physical-based distributed model, and ModClark model, a semi-distributed model. As a result, $Vflo^{TM}$ model simulated peak time and peak value similar to that of observed hydrograph. ModClark model showed good results for total runoff volume. However, for verifying the parameter, $Vflo^{TM}$ model showed better reproduction of observed hydrograph than ModClark model. These results confirmed that flood runoff simulation is applicable in domestic settings(in South Korea) if highly accurate areal rainfall is calculated by combining gauge rainfall and RADAR rainfall data and the simulation is performed in link to the distributed hydrological model.

• Journal of Korean Society for Geospatial Information Science
• /
• v.18 no.3
• /
• pp.37-48
• /
• 2010

The purpose of this paper is to evaluate how the rainfall field effect on a runoff simulation using grid radar rainfall data and ground gauge rainfall. The Gwangdeoksan radar and ground-gauge rainfall data were used to estimate a spatial rainfall field, and a hydrologic model was used to evaluate whether the rainfall fields created by each method reproduced a realistically valid spatial and temporal distribution. Pilot basin in this paper was the Naerin stream located in Inje-gun, Gangwondo, 250m grid scale digital elevation data, land cover maps, and soil maps were used to estimate geological parameters for the hydrologic model. For the rainfall input data, quantitative precipitation estimation(QPE), adjusted radar rainfall, and gauge rainfall was used, and then compared with the observed runoff by inputting it into a $Vflo^{TM}$ model. As a result of the simulation, the quantitative precipitation estimation and the ground rainfall were underestimated when compared to the observed runoff, while the adjusted radar rainfall showed a similar runoff simulation with the actual observed runoff. From these results, we suggested that when weather radars and ground rainfall data are combined, they have a greater hydrological usability as input data for a hydrological model than when just radar rainfall or ground rainfall is used separately.

• Journal of Wetlands Research
• /
• v.7 no.3
• /
• pp.41-48
• /
• 2005

Generally the estimation of effective rainfall is important in the rainfall-runoff analysis. So, we must pay attention to selecting more accurate effective rainfall estimation method. Although there are many effective rainfall estimation methods, the NRCS method is widely used for the estimation of effective rainfall in the ungaged basin. However, the NRCS method was developed based on the characteristics of the river basin in USA. So, it may have problems to use the NRSC method in Korea without its verification. In the NRCS method, the antecedent precipitation of 5-day is usually used for the estimation of effective rainfall. The main purpose of this study is to investigate the suitable antecedent precipitation day in Korea river basin through the case study. This study performs the rainfall-runoff simulation for the Tanbu river basin by HEC-HMS model under the condition of varying the antecedent precipitation day from 1-day to 7-day and performs goodness of fit test by Monte Carlo simulation method. The antecedent precipitation of 2-day shows the most preferable result in the analysis. This result indicates that the NRCS method should be applied with caution according to the characteristics of the river basin.

• Journal of Korea Water Resources Association
• /
• v.37 no.4
• /
• pp.329-339
• /
• 2004

The main objective of this study is to develop a GIS-based two-dimensional model for the simulation of rainfall-runoff process and overland flow of a watershed. The tasks of this study are summarized: to develop a two-dimensional model for overland flow and to construct a rainfall-runoff simulation system linked with GIS. The mathematical formulation of the model incorporates four parts: spatially varied rainfall, spatially distributed infiltration, 1-directional, 4-directional and 8-directional overland flow routing scheme, and one-dimensional channel routing scheme. For the development of stochastic model, Monte Carlo simulation method has been directly integrated into the model. GIS using Arc/Info and ArcView has been applied to prepare the model input data(elevation, soil type, rainfall data, etc.) for a simulation and to demonstrate the simulation results.