• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6B
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• pp.503-512
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• 2009

Watershed models, which are a tool for water cycle mechanism, are classified as the distributed model and the lumped model. Currently, the distributed models have been more widely used than lumped model for many researches and applications. The lumped model estimates the parameters in the conceptual and empirical sense, on the other hand, in the case of distributed model the first-guess value is estimated from the grid-based watershed characteristics and rainfall data. Therefore, the distributed model needs more detailed parameter adjustment in its calibration and also one should precisely understand the model parameters' characteristics and sensitivity. This study uses Jungnang basin as a study area and $Vflo^{TM}$ model, which is a physics-based distributed hydrologic model, is used to analyze its parameters' sensitivity. To begin with, 100 years frequency-design rainfall is derived from Huff's method for rainfall duration of 6 hours, then the discharge is simulated using the calibrated parameters of $Vflo^{TM}$ model. As a result, hydraulic conductivity and overland's roughness have an effect on runoff depth and peak discharge, respectively, while channel's roughness have influence on travel time and peak discharge.

• Journal of Satellite, Information and Communications
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• v.12 no.3
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• pp.22-34
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• 2017

The K-DRUM(K-water hydrologic & hydraulic Distributed RUnoff Model), a distributed rainfall-runoff model of K-water, calculates predicted runoff and water surface level of a dam using precipitation data. In order to obtain long-term hydrometeorological information, K-DRUM requires long-term weather forecast. In this study, we built a system providing long-term hydrometeorological information using predicted rainfall ensemble of GloSea5(Global Seasonal Forecast System version 5), which is the seasonal meteorological forecasting system of KMA introduced in 2014. This system produces K-DRUM input data by automatic pre-processing and bias-correcting GloSea5 data, then derives long-term inflow predictions via K-DRUM. Web-based UI was developed for users to monitor the hydrometeorological information such as rainfall, runoff, and water surface level of dams. Through this UI, users can also test various dam management scenarios by adjusting discharge amount for decision-making.

• Water Engineering Research
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• v.5 no.2
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• pp.81-99
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• 2004

Long term streamflow regime under virtual climate change scenario was examined. Rainfall forecast simulation of the Canadian Global Coupled Model (CGCM2) of the Canadian Climate Center for modeling and analysis for the IPCC SRES B2 scenario was used for analysis. The B2 scenario envisions slower population growth (10.4 billion by 2010) with a more rapidly evolving economy and more emphasis on environmental protection. The relatively large scale of GCM hinders the accurate computation of the important streamflow characteristics such as the peak flow rate and lag time, etc. The GCM rainfall with more than 100km scale was downscaled to 2km-scale using the space-time stochastic random cascade model. The HEC-HMS was used for distributed hydrologic model which can take the grid rainfall as input data. The result illustrates that the annual variation of the total runoff and the peak flow can be much greater than rainfall variation, which means actual impact of rainfall variation for the available water resources can be much greater than the extent of the rainfall variation.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05a
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• pp.27-40
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• 2002

Developed at Colorado State University, CASC2D-SED is a physically-based model simulating the hydrologic response of a watershed to a distributed rainfall field. The time-dependent processes include: precipitation, interception, infiltration, surface runoff and channel routing, upland erosion, transport and sedimentation. CASC2D-SED is applied to Goodwin Creek, Mississippi. The watershed covers 21 $\textrm{km}^2$ and has been extensively monitored both at the outlet and at several internal locations by the ARS-NSL at Oxford, MS. The model has been calibrated and validated using rainfall data from 16 meteorological stations,6 stream gaging stations and 6 sediment gaging stations. Sediment erosion/deposition rates by size fraction are predicted both in space and time. Geovisualization, a powerful data exploration technique based on GIS technology, is used to analyze and display the dynamic output time series generated by the CASC2D-SED model.

• KIEAE Journal
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• v.13 no.4
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• pp.33-41
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• 2013

The impervious area on the surface of urban area has been increased as buildings and artificial land cover have continually been increased. Urban development has gradually decreased the green zone in downtown and alienated the city from the natural environment on outskirt area devastating the natural ecosystem. There arise the environmental problems to urban area including urban heat island phenomenon, urban flood, air pollution and urban desertification. As one of urban plans to solve such problems, green roof system is attracting attentions. The purpose of this study was to investigate flood discharge and heat reduction effect according to the green roof system and to quantify effect by analyzing through simulation water and heat cycle before and after green roof system. For the analysis, Distributed hydrologic model, WEP (Water and Energy transfer Processes) and WEP+ model were used. WEP was developed by Dr. Jia, the Public Works Research Institute in Japan (Jia et al., 2005), which can simulate water and heat cycle of an urban area with complex land uses including calculation of spatial and temporal distributions of water and heat cycle components. The WEP+ is a visualization and analysis system for the WEP model developed by Korea Institute of Construction Technology (KICT).

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.1
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• pp.17-29
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• 2013

Long-Term Hydrologic Impact Assessment (L-THIA) model which is a distributed watershed model was applied to analyze the spatial distribution of surface runoff and nonpoint source pollutant loading from Imha watershed during 2001~2010. L-THIA CN Calibration Tool linked with SCE-UA was developed to calibrate surface runoff automatically. Calibration (2001~2005) and validation (2006~2010) of monthly surface runoff were represented as 'very good' model performance showing 0.91 for calibration and 0.89 for validation as Nash-Sutcliffe (NS) values. Average annual surface runoff from Imha watershed was 218.4 mm and Banbyun subwatershed was much more than other watersheds due to poor hydrologic condition. Average annual nonpoint source pollutant loading from Imha wateshed were 2,295 ton/year for $BOD_5$, 14,752 ton/year for SS, 358 ton/year for T-N, and 79 ton/year for T-P. Amount of pollutant loading and pollutant loading rates from Banbyun watershed were much higher than other watersheds. As results of analysis of loading rate from grid size ($30m{\times}30m$), most of high 10 % of loading rate were generated from upland. Therefore, major hot spot area to manage nonpoint source pollution in Imha watershed is the combination of upland and Banbyun subwatershed. L-THIA model is easy to use and prepare input file and useful tool to manage nonpoint source pollution at screening level.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.5
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• pp.35-42
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• 1995

his paper is to develop a GIS application model (GISCELWAB) for the spatial simulation of surface runoff from a small watershed. The model was constituted by three submodels : The input data extraction model (GISINDATA) which prepares cell-based input data automatically for a given watershed, the cell water balance model (CELWAB) which calculates the water balance for a cell and simulates surface runoff of watershed simultaneously by the interaction of cells, and the output data management model (GISOUTDISP) which visualize the results of temporal and spatial variation of surface runoff. The input data extraction model was developed to solve the time-consuming problems for the input-data preparation of distributed hydrologic model. The input data for CELWAB can be obtained by extracting ASCII data from a vector map. The output data management model was developed to convert the storage depth and discharge of cells into grid map. This model enables to visualize the spatial formulation process of watershed storage depth and surface runoff wholly with time increment.

• Journal of Korea Water Resources Association
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• v.43 no.12
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• pp.1011-1027
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• 2010

In hydrologic modeling, prediction uncertainty generally stems from various uncertainty sources associated with model structure, data, and parameters, etc. This study aims to assess the parameter uncertainty effect on hydrologic prediction results. For this objective, a distributed rainfall-sediment yield-runoff model, which consists of rainfall-runoff module for simulation of surface and subsurface flows and sediment yield module based on unit stream power theory, was applied to the mesoscale mountainous area (Cheoncheon catchment; 289.9 $km^2$). For parameter uncertainty evaluation, the model was calibrated by a multi-objective optimization algorithm (MOSCEM) with two different objective functions (RMSE and HMLE) and Pareto optimal solutions of each case were then estimated. In Case I, the rainfall-runoff module was calibrated to investigate the effect of parameter uncertainty on hydrograph reproduction whereas in Case II, sediment yield module was calibrated to show the propagation of parameter uncertainty into sedigraph estimation. Additionally, in Case III, all parameters of both modules were simultaneously calibrated in order to take account of prediction uncertainty in rainfall-sediment yield-runoff modeling. The results showed that hydrograph prediction uncertainty of Case I was observed over the low-flow periods while the sedigraph of high-flow periods was sensitive to uncertainty of the sediment yield module parameters in Case II. In Case III, prediction uncertainty ranges of both hydrograph and sedigraph were larger than the other cases. Furthermore, prediction uncertainty in terms of spatial distribution of erosion and deposition drastically varied with the applied model parameters for all cases.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.145-151
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• 2009

Recently, the rapid development of GIS technology has made it possible to handle a various data associated with spatially hydrological parameters with their attribute information. Therefore, there has been a shift in focus from lumped runoff models to distributed runoff models, as the latter can consider temporal and spatial variations of discharge. This research is to evaluate the feasibility of GIS based distributed model using radar rainfall which can express temporal and spatial distribution in actual dam watershed during flood runoff period. K-DRUM (K-water hydrologic & hydaulic Distributed flood RUnoff Model) which was developed to calculate flood discharge connected to radar rainfall based on long-term runoff model developed by Kyoto- University DPRI (Disaster Prevention Research Institute), and Yondam-Dam watershed ($930km^2$) was applied as study site. Distributed rainfall according to grid resolution was generated by using preprocess program of radar rainfall, from JIN radar. Also, GIS hydrological parameters were extracted from basic GIS data such as DEM, land cover and soil map, and used as input data of distributed model (K-DRUM). Results of this research can provide a base for building of real-time short-term rainfall runoff forecast system according to flash flood in near future.

• 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.