• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.149-153
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• 2009

Physics-based distributed rainfall-runoff models are now commonly used in a variety of hydrologic applications such as to estimate flooding, water pollutant transport, sedimentation yield and so on. Moreover, it is not surprising that GIS has become an integral part of hydrologic research since this technology offers abundant information about spatial heterogeneity for both model parameters and input data that control hydrological processes. This study presents the development of a distributed rainfall-runoff prediction system for the Guem river basin ($9,835km^2$) using an Object-oriented Hydrological Modeling System (OHyMoS). We developed three types of element modules: Slope Runoff Module (SRM), Channel Routing Module (CRM), and Dam Reservoir Module (DRM) and then incorporated them systemically into a catchment modeling system under the OHyMoS. The study basin delineated by the 250m DEM (resampled from SRTM90) was divided into 14 midsize catchments and 80 sub-catchments where correspond to the WAMIS digital map. Each sub-catchment was represented by rectangular slope and channel components; water flows among these components were simulated by both SRM and CRM. In addition, outflows of two multi-purpose dams: Yongdam and Daechung dams were calculated by DRM reflecting decision makers' opinions. Therefore, the Guem river basin rainfall-runoff modeling system can provide not only each sub-catchment outflow but also dam inand outflow at one hour (or less) time step such that users can obtain comprehensive hydrological information readily for the effective and efficient flood control during a flood season.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.253-257
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• 2007

Channel-aquifer interaction is one of the key hydrological processes that determine water flows in the stream/river channel. Field measurements of channel-aquifer interaction, however, is very difficult and costly, particularly when one intends to understand its variations across a catchment for a long period. Hydrological simulations using a catchment model are a relatively easier and cheaper alternative provided the model structure is appropriate for describing channel-aquifer interaction. In this study, a catchment model called CAMEL (Chemicals from Agricultural Management and Erosion Losses) is used for estimating channel-aquifer interaction over time and space. CAMEL is a distributed catchment model to simulate transformation and transport processes of sediment and pollutants as well as water flows at the catchment scale. In the model, a catchment is represented using a network of square columns each of which is comprised of various storages of water. CAMEL explicitly simulates both surface and subsurface processes including channel-aquifer interaction. This paper presents an application study results of CAMEL for the Tarland Burn Catchment, a small (catchment area $52\;km^2$) rural catchment in Scotland, UK, demonstrating some of the channel-aquifer interaction dynamics across the catchment during a 2-year period.

• Journal of the Korean association of regional geographers
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• v.17 no.2
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• pp.245-258
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• 2011

Best management practices (BMPs) are widely accepted and implemented as a mitigation method for soil erosion and non-point source problems. Estimating the amount of soil erosion and the effectiveness of BMPs using hydrological models help to understand the condition, identify the problems, and make plans for conservation practices in an area, typically a watershed. However, the accuracy and reliability of assessment of BMP impacts estimated by hydrological models can be often questionable due to the uncertainties from various sources including GIS(Geographic Information System) data, scale, and model. This study reviewed the development and the background of hydrological models, and the modeling issues such as the selection of models, scale, and uncertainties of data and models. This study also discussed the advantage of a small scale and spatially distributed model to estimate the impacts of BMPs.

• Journal of Korea Water Resources Association
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• v.46 no.11
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• pp.1053-1067
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• 2013

Distributed ecohydrological model which can simulate hydrological components, vegetation and landsurface temperature using practically available input and observed data with minimum parameters is introduced. This model is designed to properly simulate in area with lack of observed data. Parameter estimation and calibration of the model can be carried out with indirectly estimated data (monthly surface runoff by NRCS-CN method and annual actual vaporization by empirical equation) and remote sensing data (NDVI, LST) instead of observed data. We applied this model in the Naeseong creek basin to evaluate the model validity. Firstly, we found the sensitive parameters which largely influence the simulation results by sensitivity analysis, and then hydrological components, vegetation, land-surface temperature, routed streamflow and water temperature were simulated over 10 years (2001 to 2010) using calibrated parameters. Parameters are estimated by optimization method. It is shown that most of grids are well simulated. In the case of streamflow and water temperature, we checked two observed points in the outlet of watershed and it is shown that streamflow and water temperature are properly simulated as well. Hence, it can be shown that this model properly simulate the hydrological components, vegetation, land-surface temperature, routed streamflow and water temperature as well, even though in despite of using limited input data and minimum parameters.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.4
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• pp.88-97
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• 2004

A Grid-based distributed evaporation prediction model which calculates temporal and spatial evaporation with a heat balance method was developed. And, the model was considered as the integration with distributed hydrological model in near future. 'This model was programmed by fortran language and used ASCII formatted map data of DEM (Digital Elevation Model) and land cover map extracted by remote sensing data. Also, temporal variations and spatial distributions of evaporation are presented by using GIS. To verify the applicability of the model, it was applied to the Shonai river basin ($532km^2$) which has sufficient meteorological and hydrological data, Japan. The result shows that the estimated mean annual evaporation was 825.4mm, and this value is estimated as suitable things in considering rainfall and discharge data in study area.

• Journal of Korea Water Resources Association
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• v.42 no.1
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• pp.51-60
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• 2009

2/3 of the Imjin River Basin area is located in North Korea, so it was hard to acquire reliable rainfall and hydrological information. This point is one of the factors that has added to flood damage. In this study, flood runoff for the river basin was simulated using hydrological radar, which is installed in an effort to reduce flood damage in the Imjin River Basin, which habitually suffers from flood damage. The feasibility of the distributed flood model was reviewed for the river basin, which is lacking in hydrological data such as rainfall and recent soil data. Based on the hydrograph, observed value was not consistent partially because of insufficient data, but peak discharge and the overall pattern showed relatively precise runoff results which can be applied in actual work.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.25-25
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• 2023

The ensemble optimal interpolation (EnOI) scheme is a sub-optimal alternative to the ensemble Kalman filter (EnKF) with a reduced computational demand making it potentially more suitable for operational applications. Since only one model is integrated forward instead of an ensemble of model realizations, online estimation of the background error covariance matrix is not possible in the EnOI scheme. In this study, we investigate two Gaussian noise based ensemble generation strategies to produce dynamic covariance matrices for assimilation of water level observations into a distributed hydrological model. In the first approach, spatially correlated noise, sampled from a normal distribution with a fixed fractional error parameter (which controls its standard deviation), is added to the model forecast state vector to prepare the ensembles. In the second method, we use an adaptive error estimation technique based on the innovation diagnostics to estimate this error parameter within the assimilation framework. The results from a real and a set of synthetic experiments indicate that the EnOI scheme can provide better results when an optimal EnKF is not identified, but performs worse than the ensemble filter when the true error characteristics are known. Furthermore, while the adaptive approach is able to reduce the sensitivity to the fractional error parameter affecting the first (non-adaptive) approach, results are usually worse at ungauged locations with the former.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.247-247
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• 2015

Global Climate Model (GCM) is too coarse to apply at a basin scale. The spatial downcsaling is needed to used to permit the assessment of the hydrological changes of a basin. Furthermore, temporal downscaling is required to obtain hourly precipitation to analyze a small or medium basin because only few or several hours are used to determine the peak flows after it rains. In the current study, the spariotemporal distribution of downscaled hourly precipitation for RCP4.5 and RCP8.5 scenarios over South Korea is presented as well as its implications over hydrologica responses. Mean hourly precipitation significantly increases over the southern part of South Korea, especially during the morning time, and its increase becomes lower at later times of day in the RCP8.5 scenario. However, this increase cannot be propagated to the mainland due to the mountainous areas in the southern part of the country. Furthermore, the hydrological responses employing a distributed rainfall-runoff model show that there is a significant increase in the peak flow for the RCP8.5 scenario with a slight decrease for the RCP4.5 scenario. The current study concludes that the employed temporal downscaling method is suitable for obtaining the hourly precipitation data from daily GCM scenarios. In addition, the rainfall runoff simulation through the downscaled hourly precipitation is useful for investigating variations in the hydrological responses as related to future scenarios.

• Journal of Korea Water Resources Association
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• v.40 no.5
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• pp.419-430
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• 2007

Integrated modelling of surface water and groundwater has become important to satisfy the growing demands for sustainable water resources and improved water quality. In this study, the integrated model of the semi-distributed watershed model, SWA T and the fully-distributed groundwater flow model, MODFLOW is applied to Musirn river basin for the purpose of investigating its applicability to reproduce watershed-scale hydrological processes. This objective is accomplished by first demonstrating good agreement between the simulated discharge hydrographs with the measured hydrographs for the period of 2001 -2004 while simultaneously calibrating the calculated groundwater level distribution to observation wells. Next, the integrated model is used to evaluate the effect of different temporal precipitation averages on hydrodynamic processes of streamflow, percolation, recharge and groundwater discharge. Moreover, comprehensive simulations are performed to present the relationships between monthly precipitation and each hydrological component, and to analyze the temporal-spatial variability of recharge. The results show that the components are highly interrelated, and that the heterogeneity of watershed characteristics such as subbasin slope, land use, soil type causes a significant spatial variation of recharge. Overall it is concluded that the model is capable of reproducing the temporally and spatially varied surface and subsurface hydrological processes at the watershed scale.

• Journal of Wetlands Research
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• v.22 no.1
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• pp.15-23
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• 2020

The purpose of this study is to investigate how the degree of distribution influences the calibration of snow and runoff in distributed hydrological models using a multi-criteria calibration method. The Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) developed by NOAA-National Weather Service (NWS) is employed to estimate optimized parameter sets. We have 3 scenarios depended on the model complexity for estimating best parameter sets: Lumped, Semi-Distributed, and Fully-Distributed. For the case study, the Durango River Basin, Colorado is selected as a study basin to consider both snow and water balance components. This study basin is in the mountainous western U.S. area and consists of 108 Hydrologic Rainfall Analysis Project (HRAP) grid cells. 5 and 13 parameters of snow and water balance models are calibrated with the Multi-Objective Shuffled Complex Evolution Metropolis (MOSCEM) algorithm. Model calibration and validation are conducted on 4km HRAP grids with 5 years (2001-2005) meteorological data and observations. Through case study, we show that snow and streamflow simulations are improved with multiple criteria calibrations without considering model complexity. In particular, we confirm that semi- and fully distributed models are better performances than those of lumped model. In case of lumped model, the Root Mean Square Error (RMSE) values improve by 35% on snow average and 42% on runoff from a priori parameter set through multi-criteria calibrations. On the other hand, the RMSE values are improved by 40% and 43% for snow and runoff on semi- and fully-distributed models.