• Journal of Korea Water Resources Association
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• v.30 no.5
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• pp.431-439
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• 1997

This paper describes the development of a decision support system (DSS) for the real time reservoir operation that aims to maximize the flood control effect. In the decision support system, model base and real time data processing subsystem are included along with the graphical user interface(GUI) that is able to visualize the forecasted runoff hydrographs at the flood control points and reservoir water levels resulting from the model run as well as the current hydrologic status. The system was verified through the pseudo real time applications to the Taechong reservoir operation with the historical flood events of the Kum river basin occurred in July, 1987 and August, 1995, Decision making processes were performed using the developed system and the results were compared with the real operations at that time. The reservoir operation using the pseudo real time application of DSS were simulated by the flood runoff simulation model, that shows the reservoir operation by DSS were successful in flood control for the lower Kum River.

• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.1057-1066
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• 2019

The storage function method is used as a flood prediction model for four flood control offices in Korea as a method to analyze the actual rainfall-runoff relationship with non-linearity. It is essential to accurately estimate the parameters of the storage function method for accurate runoff analysis. However, the parameters of the storage function method currently in use are estimated by the empirical formula developed by the limited hydrological analysis in 2012; therefore, they are somewhat inaccurate. The kinematic wave method is a method based on physical variables of watershed and channel and is widely used for rainfall-runoff analysis. By adopting the two-term storage function method by the conversion of the kinematic wave method, parameters can be estimated based on physical variables, which can increase the accuracy of runoff calculation. In this research, the reproducibility of the kinematic wave method by the two-term storage function method was investigated. It is very easy to estimate the parameters because equivalent roughness, which is an important physical variable in watershed runoff, can be easily obtained by using land use and land cover, and the physical variable of channel runoff can be easily obtained from the basic river planning report or topographic map. In addition, this research examined the applicability of the two-term storage function method to runoff simulation of Naechon Stream, a tributary of the Hongcheon River in the Han River basin. As a result, it is considered that more accurate runoff calculation results could be obtained than the existing one-term storage function method. It is expected that the utilization of the storage function method can be increased because the parameters can be easily estimated using physical variables even in unmeasured watersheds and channels.

• Journal of Korea Water Resources Association
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• v.32 no.2
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• pp.163-176
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• 1999

Hydrology-based topographical informations generated by GIS techniques could be changed according to the selection of base map, algorithm of extraction, and so on. The purpose of this paper is to investigate the variation of SCS CN extracted by GIS technique and to propose the effective strategy for applying GIS to the rainfall-runoff simulation in ungaged basin. For experimental implementation, GIS spatial data, such as reconnaissance soil map, detailed interpretative soil map, landuse planning map and remotely sensed data(Landsat TM), were collected and generated to calculate the amount of effective rainfall in Pyungchang river basin. In applying SCS Runoff Curve Number to the test basin, the hydrological attribute data were analyzed. In addition, the characteristics of runoff responses according to the selection of GIS spatial data for SCS CN were reviewed. This study shows the applicability of GIS techniques to runoff simulation in ungaged basin by comparing with the measured flood hydrograph. It has been found that the detained interpretative soil map and remote sensing data are appropriate for calculating of SCS CN.

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

• International conference on construction engineering and project management
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• 2015.10a
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• pp.54-55
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• 2015

Increase of impervious areas due to expansion of housing area, commercial and business building of urban is resulting in property change of stormwater runoff. Also, rapid urbanization and heavy rain due to climate change lead to urban flood and debris flow damage. In 2010 and 2011, Seoul had experienced shocking flooding damages by heavy rain. All these have led to increased interest in applying LID and decentralized rainwater management as a means of urban hydrologic cycle restoration and Natural Disaster Prevention such as flooding and so on. Urban development is a cause of expansion of impervious area. It reduces infiltration of rain water and may increase runoff volume from storms. Low Impact Development (LID) methods is to mimic the predevelopment site hydrology by using site design techniques that store, infiltrate, evaporate, detain runoff, and reduction flooding. Use of these techniques helps to reduce off-site runoff and ensure adequate groundwater recharge. The contents of this paper include a hydrologic analysis on a site and an evaluation of flooding reduction effect of LID practice facilities planned on the site. The region of this Case study is LID Rainwater Management Demonstration District in A-new town and P-new town, Korea. LID Practice facilities were designed on the area of rainwater management demonstration district in new town. We performed analysis of reduction effect about flood discharge. SWMM5 has been developed as a model to analyze the hydrologic impacts of LID facilities. For this study, we used weather data for around 38 years from January 1973 to August 2014 collected from the new town City Observatory near the district. Using the weather data, we performed continuous simulation of urban runoff in order to analyze impacts on the Stream from the development of the district and the installation of LID facilities. This is a new approach to stormwater management system which is different from existing end-of-pipe type management system. We suggest that LID should be discussed as a efficient method of urban disasters and climate change control in future land use, sewer and stormwater management planning.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.24-27
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• 1996

The storage function method(SFM) is one of hydrologic flood routings which has been used most widely in Korea and Japan. This paper presents a storage function method using multiple model adaptive estimation(MMAE), in which a model set is generated by partitioning storage parameters over feasible range, and each storage function model is estimated, and then the weighted average of them is calculated. Finally, the future runoff is predicted in real time by means of observed data of water level at dam and rainfall. Simulation results applied to actual data show that the proposed method has much better performance than that of conventional SFM.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.4
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• pp.95-102
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• 1994

The series of the papers consist of three parts to describe the development, calibration, and applications of the flood forecasting models for the Youngsan Estuarine Dam located at the mouth of the Youngsan river. And this paper discusses the hydrologic model for inflow simulation at Naju station, which constitutes 64 percent of the drainage basin of 3521 .6km$^2$ in area. A simplified TANK model was formulated to simulate hourly runoff from rainfall And the model parameters were optirnized using historical storm data, and validated with the records. The results of this paper were summarized as follows. 1. The simplified TANK model was formulated to conceptualize the hourly rainfall-run-off relationships at a watershed with four tanks in series having five runoff outlets. The runoff from each outlet was assumed to be proportional to the storage exceeding a threshold value. And each tank was linked with a drainage hole from the upper one. 2. Fifteen storm events from four year records from 1984 to 1987 were selected for this study. They varied from 81 to 289rn'm The watershed averaged, hourly rainfall data were determined from those at fifteen raingaging stations using a Thiessen method. Some missing and unrealistic records at a few stations were estimated or replaced with the values determined using a reciprocal distance square method from abjacent ones. 3. An univariate scheme was adopted to calibrate the model parameters using historical records. Some of the calibrated parameters were statistically related to antecedent precipitation. And the model simulated the streamflow close to the observed, with the mean coefficient of determination of 0.94 for all storm events. 4. The simulated streamflow were in good agreement with the historical records for ungaged condition simulation runs. The mean coefficient of determination for the runs was 0.93, nearly the same as calibration runs. This may indicates that the model performs very well in flood forecasting situations for the watershed.

• Journal of Korea Water Resources Association
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• v.35 no.3
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• pp.331-344
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• 2002

This study is aimed at the development of a deterministic runoff model which can be used for flood runoff. The model is formulated by the watershed runoff model. Based on the assumptions that runoff system is nonlinear, the proposed watershed runoff model is the conceptual model. In the model structure, the conceptual model divides the runoff system into a surface structure and a subsurface structure corresponding to the surface flow, and inter flow and ground water flow respectively. The lag time effect of surface can be represented by the sub-tank of surface structure in the conceptual model. The parameter calibration of inter flow and ground water flow in the subsurface structure of the conceptual model is performed by separating the components with numeric filter The runoff coefficient($\alpha$$_2$) is expressed as the function of antecedent precipitation index(API). The parameters with the surface flow can be calibrated with the runoff coefficient($\alpha$$_1$ and $\alpha$/$_{11}$) in the conceptual model. In the conceptual model, an algorithm is developed to calibrate the parameters automatically based on efficiency criteria. The comparative study shows that simulated value from the conceptual model well agreed to observed value.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.6
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• pp.51-64
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• 2022

Along with the urbanization, the risk of urban flooding due to climate change is increasing. Flood regulation, one of the ecosystem services, is implemented in the different level of function of flood risk mitigation by the type of ecosystem such as forests, arable land, wetlands etc. Land use changes due to development pressures have become an important factor in increasing the vulnerability by flash flood. This study has conducted evaluating the urban flood regulation service using InVEST UFRM(Urban Flood Risk Model). As a result of the simulation, the potential water retention by ecosystem type in the event of a flash flood according to RCP 4.5(10 year frequency) scenario was 1,569,611 tons in urbanized/dried areas, 907,706 tons in agricultural areas, 1,496,105 tons in forested areas, 831,705 tons in grasslands, 1,021,742 tons in wetlands, and 206,709 tons in bare areas, the water bodies was estimated to be 38,087 tons. In the case of more severe 100-year rainfall, 1,808,376 tons in urbanized/dried areas, 1,172,505 tons in agricultural areas, 2,076,019 tons in forests, 1,021,742 tons in grasslands, 47,603 tons in wetlands, 238,363 tons in bare lands, and 52,985 tons in water bodies. The potential economic damage from flood runoff(100 years frequency) is 122,512,524 thousand won in residential areas, 512,382,410 thousand won in commercial areas, 50,414,646 thousand won in industrial areas, 2,927,508 thousand won in Infrastructure(road), 8,907 thousand won in agriculture, Total of assuming a runoff of 50 mm(100 year frequency) was estimated at 688,245,997 thousand won. In a conclusion. these results provided an overview of ecosystem functions and services in terms of flood control, and indirectly demonstrated the possibility of using the model as a tool for policy decision-making. Nevertheless, in future research, related issues such as application of models according to various spatial scales, verification of difference in result values due to differences in spatial resolution, improvement of CN(Curved Number) suitable for the research site conditions based on actual data, and development of flood damage factors suitable for domestic condition for the calculation of economic loss.

• Journal of Korea Water Resources Association
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• v.52 no.1
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• pp.21-33
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• 2019

This study performed to simulate the watershed storm runoff using data of S-band dual-polarization radar rain, GPM (Global Precipitation Mission) satellite rain, and observed rainfall at 21 ground stations operated by KMA (Korea Meteorological Administration) respectively. For the 3 water level gauge stations (Sancheong, Changchon, and Namgang) of NamgangDam watershed ($2,293km^2$), the KIMSTORM2 (KIneMatic wave STOrm Runoff Model2) was applied and calibrated with parameters of initial soil moisture contents, Manning's roughness of overland and stream to the event of typhoon CHABA (82 mm in watershed aveprage) in $5^{th}$ October 2016. The radar and GPM data was corrected with CM (Conditional Merging) method such as CM-corrected Radar and CM-corrected GPM. The CM has been used for accurate rainfall estimation in water resources and meteorological field and the method combined measured ground rainfall and spatial data such as radar and satellite images by the kriging interpolation technique. For the CM-corrected Radar and CM-corrected GPM data application, the determination coefficient ($R^2$) was 0.96 respectively. The Nash-Sutcliffe efficiency (NSE) was 0.96 and the Volume Conservation Index (VCI) was 1.03 respectively. The CM-corrected data of Radar and GPM showed good results for the CHABA peak runoff and runoff volume simulation and improved all of $R^2$, NSE, and VCI comparing with the original data application. Thus, we need to use and apply the radar and satellite data to monitor the flood within the watershed.