• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.439-439
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• 2015

The temporal and spatial relationship of the weather elements such as rainfall and temperature is closely linked to the streamflow simulation, especially, to the flood forecasting problems. For the study area, Imjin river basin, which has the specific characteristics in geography with river cross operation between North and South Korea, the meteorological information in the northern area is totally deficiency, lead to the inaccuracy of streamflow estimation. In the paper, this problem is solved by using the combination of global (such as soil moisture content, land use) and local hydrologic components data such as weather data (precipitation, evapotranspiration, humidity, etc.) for the model-driven runoff (surface flow, lateral flow and groundwater flow) data in each subbasin. To compute the streamflow in Imjin river basin, this study is applied the hydrologic model SURR (Sejong Univ. Rainfall-Runoff) which is the continuous rainfall-runoff model used physical foundations, originally based on Storage Function Model (SFM) to simulate the intercourse of the soil properties, weather factors and flow value. The result indicates the spatial variation in the runoff response of the different subbasins influenced by the input data. The dependancy of runoff simulation accuracy depending on the qualities of input data and model parameters is suggested in this study. The southern region with the dense of gauges and the adequate data shows the good results of the simulated discharge. Eventually, the application of SURR model in Imjin riverbasin gives the accurate consequence in simulation, and become the subsequent runoff for prediction in the future process.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.134-134
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• 2022

Streamflow forecasting plays a crucial role in water resource control, especially in highly urbanized areas that are very vulnerable to flooding during heavy rainfall event. In addition to providing the accurate prediction, the evaluation of effects and importance of the input predictors can contribute to water manager. Recently, machine learning techniques have applied their advantages for modeling complex and nonlinear hydrological processes. However, the techniques have not considered properly the importance and uncertainty of the predictor variables. To address these concerns, we applied the GA-BART, that integrates a genetic algorithm (GA) with the Bayesian additive regression tree (BART) model for hourly streamflow forecasting and analyzing input predictors. The Jungrang urban basin was selected as a case study and a database was established based on 39 heavy rainfall events during 2003 and 2020 from the rain gauges and monitoring stations. For the goal of this study, we used a combination of inputs that included the areal rainfall of the subbasins at current time step and previous time steps and water level and streamflow of the stations at time step for multistep-ahead streamflow predictions. An analysis of multiple datasets including different input predictors was performed to define the optimal set for streamflow forecasting. In addition, the GA-BART model could reasonably determine the relative importance of the input variables. The assessment might help water resource managers improve the accuracy of forecasts and early flood warnings in the basin.

• Water for future
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• v.15 no.3
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• pp.37-47
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• 1982

In the past, the design flow of the urban storm drainage systems has been used largely on a basis of empirical and experience, and the rational formula one of empirical method has been widely used for our country, as well as world wide. But the empirical method has insufficient factor because minimal consideration is given to the relationship of the parameters in the equation to the processes being considered, and considerable use of experience and judgment in setting values to the coefficients in the equation is made. The postcomputer era of hydrology has brought an acceleration development of mathematical methods, thus mathematical models are methods which will greatly increase our understanding in hydrology. On this study, a simple mathematical model of urban presented by British Road Research Laboratory is tested on urban watersheds in Ju An Ju Gong Apartment. The basin is located in Kan Seog Dong, Inchon. The model produces a runoff hydrograph by applying rain all to only the directly connected impervious area of the basin. To apply this model the basin is divided into contributing areas or subbasins. With this information the time area for contributing is derived. The rainfall hyetograph to design storm for the basin flow has been obtained by determination of total rainfall and the temporal distribution of that rainfall determined on the basis of Huff's method form historical rainfall data of the basin. The inflows from several subbaisns are successively routed down the network of reaches from the upstream end to the outlet. A simple storage routing technique is used which involves the use of the Manning equation to compute the stage discharge curve for the cross-section in question. To apply the model to a basin, the pattern of impervious areas must be known in detail, as well as the slopes and sizes of all surface and subsurface drains.

• Journal of Korea Water Resources Association
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• v.44 no.11
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• pp.853-861
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• 2011

The objective of this study is to assess Sejong University River Forecast (SURF) model which consists of a continuous rainfall-runoff model and measured streamflow assimilation using ensemble Kalman filter technique for streamflow forecast on Nakdong river basin. The study area is divided into 43 subbasins. The forecasted streamflows are evaluated at 12 measurement sites during flood season from 2006 to 2007. The forecasted ones are improved due to the impact of the measured streamflows assimilation. In effectiveness indices corresponding to 1~5 h forecast lead times, the accuracy of the forecasted streamflows with the assimilation approach is improved by 46.2~30.1% compared with that using only the rainfall-runoff model. The mean normalized absolute error of forecasted peak flow without and with data assimilation approach in entering 50% of the measured rainfall, respectively, the accuracy of the latter is improved about 40% than that of the former. From these results, SURF model is able to be used as a real-time river forecast model.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.752-757
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• 2009

In the last decade, many methods such as greet chamber, reservoir, or debris barrier, have been utilized to manage and prevent muddy water problem. The Vegetative Filter Strip (VFS) has been thought to be one of the most effective methods to trap sediment effectively. The VFS are usually installed at the edge of agricultural areas adjacent to stream or drainage ditches, and it has been shown that the VFS effectively removes pollutants transported with upland runoff. But, if the VFS is installed without any scientific analysis of rainfall-runoff characteristics, soil erosion, and sediment analysis, it may not reduce the sediment as much as expected. Although Soil and Water Assessment Tool (SWAT) model has been used worldwide for many hydrologic and Non-Point Source Pollution (NPSP) analysis at a watershed scale. but it has many limitations in simulating the VFS. Because it considers only 'filter strip width' when the model estimates sediment trapping efficiency, and does not consider the routing of sediment with overland flow option which is expected to maximize the sediment trapping efficiency from upper agricultural subbasin to lower spatially-explicit filter strip. Therefore, the SWAT overland flow option between landuse-subbasins with sediment routing capability was enhanced with modifications in SWAT watershed configuration and SWAT engine. The enhanced SWAT can simulate the sediment trapping efficiency of the VFS in the similar way as the desktop VFSMOD-w system does. Also it now can simulate the effects of overland flow from upper subbasin to reflect the increased runoff volume at the receiving subbasin, which is what is occurring at the field if no diversion channel is installed. In this study, the enhanced SWAT model was applied to small watershed located at Jaun-ri in South Korea to simulate diversion channel and spatially-explicit VFS. It was found that approximately sediment can be reduced by 31%, 65%, 68%, with diversion channel, the VFS, and the VFS with diversion channel, respectively.

• Journal of Korean Society on Water Environment
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• v.25 no.5
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• pp.735-741
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• 2009

In order to support the basic information for planning and performing the environment management such as Total Maximum Daily Loads (TMDLs), it is highly recommended to understand the spatial distribution of water quality and runoff data in the unit watersheds. Therefore, in the present study, we applied Self-Organizing Map (SOM) to detect the characteristics of spatial distribution of Biological Oxygen Demand (BOD) concentration and runoff data which have been measured in the Yeongsan, Seomjin, and Tamjin River basins. For the purpose, the input dataset for SOM was constructed with the mean, standard deviation, skewness, and kurtosis values of the respective data measured from the stations of 22-subbasins in the rivers. The results showed that the $4{\times}4$ array structure of SOM was selected by the trial and error method and the best performance was revealed when it classified the stations into three clusters according to the basic statistics. The cluster-1 and 2 were classified primarily by the skewness and kurtosis of runoff data and the cluster-3 including the basic statistics of YB_B, YB_C, and YB_D stations was clearly decomposed by the mean value of BOD concentration showing the worst condition of water quality among the three clusters. Consequently, the methodology based on the SOM proposed in the present study can be considered that it is highly applicable to detect the spatial distribution of BOD concentration and runoff data and it can be used effectively for the further utilization using different water quality items as a data analysis tool.

• Journal of Korea Water Resources Association
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• v.30 no.1
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• pp.55-62
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• 1997

To quantitatively investigate the nationwide drought characteristics and to comparatively evaluate the 1994-1995 drought with several past droughts of significant magnitude regional frequency analysis is made for the meteorological stations in each of the 47 subbasins covering the whole nation. With monthly precipitation data for the period of records at the stations in each subbasin low precipitation data series of various durations are formulated with the running totals of monthly data and fitted to probability distributions. The method of L-method of L-moments is used to determine the unbiased parameters of each distribution, and using the best-fit distribution for each subbasin the low precipitations of various durations with return periods of 5, 10, 20, 30, and 50 years are estimated. The drought frequency maps are drawn with the low drought frequency analysis the drought of 1994-1995 is evaluated in its severity and areal extent in comparison with four other past drought of significance. The current practice of safety standards for the design of impounding facilities is also evaluated with reference to the recurrence interval of the severe drought, and a recommendation is made for the future design standard.

• Journal of Korean Society on Water Environment
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• v.25 no.6
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• pp.821-831
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• 2009

The study was aimed to assess the expected impact of climate change on the water cycle and soil losses in Daecheong Reservoir watershed, Korea using the Soil and Water Assessment Tool (SWAT) that was validated for the watershed in a previous study. Future climate data including precipitation, temperature and humidity generated by introducing a regional climate model (Mesoscale Model Version 5, MM5) to dynamically downscale global circulation model (European Centre Hamburg Model Version 4, ECHAM4) were used to simulate the hydrological responses and soil erosion processes in the future 100 years (2001~2100) under the Special Report on Emissions Scenario (SRES) A1B. The results indicated that the climate change may increase in the amount of surface runoff and thereby sediment load to the reservoir. Spatially, the impact was relatively more significant in the subbasin Bocheongcheon because of its lower occupation rate of forest land compared to other subbasins. Seasonally, the increase of surface runoff and soil losses was more significant during late summer and fall season when both flood control and turbidity flow control are necessary for the reservoir and downstream. The occurrence of extreme turbidity flow events during these period is more vulnerable to reservoir operation because the suspended solids that remained water column can be resuspended by vertical mixing during winter turnover period. The study results provide useful information for the development of adaptive management strategy for the reservoir to cope with the expected impact of future climate change.

• Journal of Korea Water Resources Association
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• v.37 no.3
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• pp.233-240
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• 2004

Most of hydrological analyses in the field of water resources are launched by gathering and analyzing rainfall data. Several methods have been developed to estimate areal rainfall from point rainfall data and to fill missing or ungaged data. Thiessen and Reciprocal Distance Squared(RDS) methods whose parameters are only dependent on inter-station distance are classical work in hydrology, but these techniques do not provide a continuous representation of the hydrologic process involved. In this study, kriging technique was applied to rainfall analysis in Nakdong river basin in order to complement the defects of these classical methods and to reflect spatial characteristics of regional rainfall. After spatial correlation and semi-variogram analyses were performed to perceive regional rainfall property, kriging analysis was performed to interpolate rainfall data for each grid Thus, these procedures were enable to estimate average rainfall of subbasins. In addition, poor region of rainfall observation was analyzed by spatial interpolation error for each grid and mean error for each subbasin.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.3
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• pp.87-98
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• 2002

Point & nonpoint source pollutant loads were calculated in Juam lake watershed using GIS, and water quality was simulated using water quality model. Point source pollutant loads were estimated using the unit pollutant loads presented by the Ministry of Environment(MOE, 1998). Nonpoint source pollutant loads were estimated using the value of the direct runoff multiplied by expected mean concentration. The direct runoff was calculated using SCS curve number method. Water quality simulation was conducted using WASP model(2001) developed by U.S. EPA. In order to apply the model, Juam lake watershed was divided into 44 subbasins according to slope, elevation, soil type, landuse and precipitation. Then the model was applied to one subbasin. Simulation results were compared to observed values and the result should good agreement with each other.