• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.633-641
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• 2018

The risk of disasters, such as floods and drought, has increased. Reliable hydrological data is important for analyzing the water resource and designing hydraulic structure to manage these risks. The Yongdam Guryang river catchment located in the central of Korea is the research catchment of K-water and UNESCO IHP, and the hydrological data, such as rainfall, runoff, evapotranspiration, etc. has been observed at the catchment. The aim of this study was to assess the runoff characteristics of the small mountainous catchment of Korea based on the observed hydrological data, and the Probability Distributed Model was applied as the Rainfall-Runoff Model at the Yongdam Guryang river catchment. The hydrological data was divided into the wet period from June to September and dry period from October to May according to data analysis. The runoff ratio was 0.27~0.41 in the wet period and 0.30~0.45 in the dry period. The calibration result by the Probability Distributed Model showed a difference in the calibrated model parameters according to the periods. In addition, the model simulated the runoff accurately except for the dry period of 2015, and the result revealed the applicability of the PDM. This study showed the runoff characteristics of the small mountainous catchment by dividing the hydrological data into dry and wet periods.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.316-316
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• 2021

Erosion in a watershed is one of the main sources of sediment inflow in dams. While sediment management practices can be performed to reduce and manage sedimentation in reservoirs, managing the sediment inflow before it reaches the reservoir should also be consider. The accurate location of areas with high erosion and deposition rates should be determined in order to propose an appropriate sediment management procedure such as the construction of check dams. In this study, the projected rainfall from HadGEMRA-3 for RCP 8.5, was used in C-SEM, a distributed rainfall-erosion model, to determine the projected spatial erosion patterns in Cheoncheon catchment, which is located in the upstream part of Yongdam Dam.

• 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.

• Journal of Korea Water Resources Association
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• v.53 no.6
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• pp.437-450
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• 2020

This study presents a probabilistic distributed hydrological model for Ephemeral catchment, where zero flow often occurs due to the influence of distinct climate characteristics in South Korea. The gridded hydrological model is developed by combining the Sacramento Soil Moisture Accounting Model (SAC-SMA) runoff model with a routing model. In addition, an error model is employed to represent a probabilistic hydrologic model. To be specific, the hydrologic model is coupled with a censoring error model to properly represent the features of ephemeral catchments. The performance of the censoring error model is evaluated by comparing it with the Gaussian error model, which has been utilized in a probabilistic model. We first address the necessity to consider ephemeral catchments through a review of the extensive research conducted over the recent decade. Then, the Yongdam Dam catchment is selected for our study area to confirm the usefulness of the hydrologic model developed in this study. Our results indicate that the use of the censored error model provides more reliable results, although the two models considered in this study perform reliable results. In addition, the Gaussian model delivers many negative flow values, suggesting that it occasionally offers unrealistic estimations in hydrologic modeling. In an in-depth analysis, we find that the efficiency of the censored error model may increase as the frequency of zero flow increases. Finally, we discuss the importance of utilizing the censored error model when the hydrologic model is applied for ephemeral catchments in South Korea.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.2
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• pp.1-11
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• 2018

Probable Maximum Flood (PMF) is mostly applied for the designs of large-scale hydraulic structures and it is estimated by computing the runoff hydrograph where Probable Maximum Precipitation (PMP) is inserted as design rainfall. The existing PMP is estimated by transferring the heavy rainfall from all watersheds of korea to the design watershed, however, in this study, PMP was analyzed by selecting only rainfall events occurred in the design watershed. And then, Catchment-scale Soil Erosion Model (CSEM) was used to estimate the PMF and sediment-runoff yield according to the watershed-based estimated PMP. Although the PMF estimated in this study was lower than the existing estimated PMF in the Yongdam-dam basin, it was estimated to be higher than the 200-year frequency design flood discharge. In addition, sediment-runoff yield was estimated with a 0.05 cm of the maximum erosion and a 0.06 cm of the maximum deposition, and a total sediment-runoff yield of 168,391 tons according to 24-hour PMP duration.

• Journal of Korea Water Resources Association
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• v.50 no.4
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• pp.241-252
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• 2017

This study aims to evaluate applicability of both online and offline parameter calibration techniques on rainfall-runoff modeling using a conceptual lumped hydrologic model. To achieve the goal, the storage function model was selected and then two different automatic calibration techniques: SCE-UA (offline method) and particle filter (online method) were applied to calibrate the optimal parameter sets for 9 rainfall events in the Cheoncheon catchment, upper area of the Yongdam multi-purpose dam. In order to assess reproducibility of hydrographs from the parameter sets of both techniques, the observed discharge of each event was divided into low flow (below average flow) and high flow (over average flow). The results show that the particle filter method, updating the parameters in real-time, provides more stable reproducibility than the SCE-UA method regardless of low and high flow. The optimal parameters estimated by SCE-UA are very sensitive to the selected objective functions used in this study: RMSE and HMLE. In particular, the parameter sets from RMSE and HMLE demonstrate superior goodness-of-fit values for high flow and low flow periods, respectively.

• Journal of Korea Water Resources Association
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• v.42 no.2
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• pp.149-160
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• 2009

The objective of this study is to suggest parameter regionalization scheme which is integrated two multivariate statistical methods: principal components analysis(PCA) and hierarchical cluster analysis(HCA). This technique is to apply semi-distributed rainfall-runoff model on ungauged catchments. 7 catchment characteristics (area, mean altitude, mean slope, ratio of forest, water content at saturation, field capacity and wilting point) are estimated for 109 mid-sized sub-basins. The first two components from PCA results account for 82.11% of the total variance in the dataset. Component 1 is related to the location of the catchments relevant to the altitude and Component 2 is connected with the area of these. 103 ungauged catchments are clustered using HCA as the following 6 groups: Goesan 23, Andong 6, Imha 5, Hapcheon 21, Yongdam 4, Seomjin 44. SWAT model is used to simulate runoff and the parameters of the model on the 6 gauged basins are estimated. The model parameters were regionalized for Soyang, Chungju and Daecheong dam basins which are assumed as ungauged ones. The model efficiency coefficients of the simulated inflows for these three dams were at least 0.8. These results also mean that goodness of fit is high to the observed inflows. This research will contribute to estimate and analyze hydrologic components on the ungauged catchments.

• Journal of Korea Water Resources Association
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• v.43 no.11
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• pp.995-1009
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• 2010

Accelerated soil erosion due to extreme climate change, such as increased rainfall intensity, and human-induced environmental changes, is a widely recognized problem. Existing soil erosion models are generally based on the gross erosion concept to compute annual upland soil loss in tons per acre per year. However, such models are not suitable for event-based simulations of erosion and deposition in time and space. Recent advances in computer geographic information system (GIS) technologies have allowed hydrologists to develop physically based models, and the trend in erosion prediction is towards process-based models, instead of conceptually lumped models. This study aims to propose an effective and robust distributed rainfall-sediment yield-runoff model consisting of basic element modules: a rainfall-runoff module based on the kinematic wave method for subsurface and surface flow, and a runoff-sediment yield-runoff model based on the unit stream power method. The model was tested on the Cheoncheon catchment, upstream of the Yongdam dam using hydrological data for three extreme flood events due to typhoons. The model provided acceptable simulation results with respect to both discharge and sediment discharge even though the simulated sedigraphs were underestimated, compared to observations. The spatial distribution of erosion and deposition demonstrated that eroded sediment loads were deposited in the cells along the channel network, which have a short overland flow length and a gentle local slope while the erosion rate increased as rainfall became larger. Additionally, spatially heterogeneous rainfall intensity, dependant on Thiessen polygons, led to spatially-distinct erosion and deposition patterns.

• Journal of Korea Water Resources Association
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• v.45 no.7
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• pp.657-674
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• 2012

This paper presents the effect of spatially-distributed rainfall on both rainfall-sediment-runoff and erosion or deposition in the experimental Cheoncheon catchment: upstream of Yongdam dam basin. The rainfall fields were generated by three rainfall interpolation techniques (Thiessen polygon: TP, Inverse Distance Weighting: IDW, Kriging) based only on ground gauges and two radar rainfall synthetic techniques (Gauge-Radar ratio: GR, Conditional Merging: CM). Each rainfall field was then assessed in terms of spatial feature and quantity and also used for rainfall-sediment-runoff and erosion-deposition simulation due to the spatial difference of rainfall fields. The results showed that all the interpolation methods based on ground gauges provided very similar hydrologic responses in spite of different spatial pattern of erosion and deposition while raw radar and GR rainfall fields led to underestimated and overestimated simulation results, respectively. The CM technique was acceptable to improve the accuracy of raw radar rainfall for hydrologic simulation even though it is more time consuming to generate spatially-distributed rainfall.