• Journal of Korea Water Resources Association
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• v.44 no.9
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• pp.721-730
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• 2011

The objective of this study is to assess the availability of streamflow simulation using Radar-AWS Rain rate (RAR) data which is produced by KMA on real-time. Chuncheon dam upstream basin is selected as study area and total area is 4859.73 $km^2$. Mean Areal Precipitation (MAP) using AWS and RAR are calculated on 5 subbasin. The correlationship of hourly MAPs between AWS and RAR is weak on ungauged subbasins but that is relatively high on gauged ones. We evaluated the simulated discharge using the MAPs derived from two data types during flood season from 2006 to 2009. The simulated discharges using AWS on Chuncheon dam (gauged basin) are well fitted with measured ones. In some cases, however, discharges using AWS on Hwacheon dam and Pyeonghwa dam with some ungauged subbasins are overestimated on the other hand, ones using RAR in the same case are well fitted with measured ones. The hourly RAR data is useful for the real-time river forecast on the ungauged basin in view of the results.

• Journal of Korea Water Resources Association
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• v.51 no.9
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• pp.769-782
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• 2018

Estimation of design floods is typically required for hydrologic design purpose. Design floods are routinely estimated for water resources planning, safety and risk of the existing water-related structures. However, the hydrologic data, especially streamflow data for the design purposes in South Korea are still very limited, and additionally the length of streamflow data is relatively short compared to the rainfall data. Therefore, this study collected a large number design flood data and watershed characteristics (e.g. area, slope and altitude) from the national river database. We further explored to formulate a scaling approach for the estimation of design flood, which is a function of the watershed characteristics. Then, this study adopted a Hierarchical Bayesian model for evaluating both parameters and their uncertainties in the regionalization approach, which models the hydrologic response of ungauged basins using regression relationships between watershed structure and model. The proposed modeling framework was validated through ungauged watersheds. The proposed approach have better performance in terms of correlation coefficient than the existing approach which is solely based on area as a predictor. Moreover, the proposed approach can provide uncertainty associated with the model parameters to better characterize design floods at ungauged watersheds.

• Journal of Korean Society on Water Environment
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• v.32 no.3
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• pp.310-317
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• 2016

It has been a big problem to estimate rainfall for the studies of mud-debris flows because the estimated rainfall from the nearest AWS (Automatic Weather Station) can tend to be quite inaccurate at individual sites. This study attempts to improve this problem through accurate rainfall depth estimation by applying an artificial neural network with radar rainfall data. For this, three models were made according to utilizing methodologies of rainfall data. The first model uses the nearest rainfall, observing the site from an ungauged site. The second uses only radar rainfall data and the third model integrates the above two models using both radar and observed rainfall at the sites around the ungauged site. This methodology was applied to the metropolitan area in Korea. It appeared as though the third model improved rainfall estimations by the largest margin. Therefore, the proposed methodology can be applied to forecast mud-debris flows in ungageed sites.

• Journal of Korean Society on Water Environment
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• v.27 no.5
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• pp.670-679
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• 2011

Chlorophyll-a is a major water quality indicator for an algal bloom in streams and lakes. The purpose of the study is to estimate chlorophyll-a concentration in tributaries of the Seonakdonggang by an artificial neural network (ANN). As the tributaries are ungauged streams, a watershed runoff and quality model was used to simulate water quality parameters. The tributary watersheds include urban area and thus Storm Water Management Model (SWMM) was used to simulate TN, TP, BOD, COD, and SS. SWMM, however, can not simulate chlorophyll-a. The chlorophyll-a series data from the tributaries were estimated by the ANN and the simulation results of water quality parameters using SWMM. An assumption used is as follows: the relation between water quality parameters and chlorophyll-a in the tributaries of the Seonakdonggang would be similar to that in the mainstream of the Seonakdonggang. On the assumption, the measurement data of water quality and chlorophyll-a in the mainstream of the Seonakdonggang were used as the learning data of the ANN. Through the sensitivity analysis, the learning data combination of water quality parameters was determined. Finally, chlorophyll-a series were estimated for tributaries of the Seonakdonggang by the ANN and TN, TP, BOD, COD, and temperature data from those streams. The relative errors between the estimated and measured chlorophyll-a were approximately 40 ~ 50%. Though the errors are somewhat large, the estimation process for chlorophyll-a may be useful in ungauged streams.

• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.797-808
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• 2019

This study evaluated the applicability of spacebourne datasets to the flood analysis in an ungauged watershed where is no discharge measurements. The Duman River basin of North Korea was selected as a target area which was flooded by recent Typhoon Lionrock. Topographical parameters for flood analysis were estimated from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM). GDEM includes the shortcomings of information on river cross-section, and conducted 2 dimensional flood analysis when considering virtual river cross-section and not considering it. As a result of comparative analysis, an error occurs in the inundation area and depth, but when used carefully, it is considered that the satellite image can be used for creating flood hazard map and utilizing information for response and preparation.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.1
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• pp.51-64
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• 2020

The purpose of this study is to present a method for quantitative analysis of flooding at the flood plain in an ungauged area using satellite rainfall and global geographic data. For this, flooding of the Tumen/Namyang area in the Duman-gang(Riv.) was simulated and the flood conditions were quantitatively analyzed. The IMERG data, a rainfall data derived from satellite images, was used as rainfall data. The GRM model was applied to the watershed runoff simulation, and the G2D model was applied to the flooding simulation of the Tumen/Namyang area. Flood event caused by Typhoon Lionrock in August 2016 was applied. Recorded peak discharge of the Tumen/Namyang region was used to verify the runoff simulation results. To verify the result of the inundation simulation, the flood situation collected through field survey and satellite image data before and after the flood were used. The peak flow rates by the runoff simulation and flood record were 7,639㎥/s and 7,630㎥/s, respectively, with a relative error of about 0.1%. In the flood simulation, the results were similar to the flooding ranges identified in the survey data and satellite images. And the changes of flooding depth and flooding time in the flood plain in Tumen/Namyang area could also be assessed. The methods and results of this study will be useful for the quantitative assessment of floods in the ungauged areas.

• 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.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1207-1214
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• 2021

In thisletter, we developed technology which can exclude effect of cloudsto perform remote waterbody detection based on Sentinel-2 optical satellite imagery to calculate the area of ungauged reservoirs and applied to the Hwanggang dam reservoir, a representative ungauged reservoir, to verify usability. The remote waterbody detection technology calculates the cloud blocking ratio by comparing the cloud boundary in the Sentinel-2 imagery and the reservoir boundary first. Next, itselects data whose cloud blocking ratio does not exceed a specific value and calculates NDWI (Normalized Difference Water Index) with selected imagery. In last, it calculatesthe area of the reservoir by counting the number of grids which have NDWI value considered as waterbody within the boundary of the target reservoir and correcting with cloud blocking ratio. To determine cloud blocking ratio threshold forselecting image, we performed the area calculation of Hwanggang dam reservoir from July 2018 to October 2021. As a result, when the cloud blocking ratio threshold wasset 10%, we confirmed that the result with large error due to clouds were filtered well and obtained 114 results that can show changes in Hwanggang dam reservoir area among 220 images.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.4
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• pp.121-133
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• 2015

The TANK model has been widely used in rainfall-runoff modeling due to its simplicity of concept and computation while achieving forecast accuracy. A major barrier to the model application is to determine parameter values for ungauged watersheds, leading to the need of a method for the parameter estimation. The objective of this study was to develop regression equations for estimating the 3th TANK model parameters considering their variations for the ungauged watersheds. Thirty watersheds of dam sites and stream stations were selected for this study. A genetic algorithm was used to optimize TANK model parameters. Watershed characteristics used in this study include land use percent, watershed area, watershed length, and watershed average slope. Generalized equations were derived by correlating to the optimized parameters and the watershed characteristics. The results showed that the TANK model, with the parameters determined by the developed regression equations, performed reasonably with 0.60 to 0.85 of Nash-Sutcliffe efficiency for daily runoff. The developed regression equations for the TANK model can be applied for the runoff simulation particularly for the ungauged watersheds, which is common for upstream of agricultural reservoirs in Korea.

• KCID journal
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• v.18 no.2
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• pp.87-100
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• 2011

This study is to delineate the watershed hydrological parameters such as area, slope, rain gauge weight, NRCS-CN and time of concentration (Tc) by using the Geographic Information Sytem (GIS) technique, and estimation of design flood for an ungauged watershed. Especially, we attempted to determine the Tc of ungauged watershed and develop simple program using the cell-based algorithm to calculates upstream or downstream flow time along a flow path for each cell. For a $19km^2$ watershed of tributary of Nakdong river (Seupmoon), the parameters including flow direction, flow accumulation, watershed boundary, stream network and Tc map were extracted from 30m Agreeburn DEM (Digital Elevation Model) and landcover map. And NRCS-CN was extracted from 30m landcover map and soil map. Design rainfall estimation for two rainfall gauge which are Sunsan and Jangcheon using FARD2006 that developed by National Institute for Disaster Prevention (NIDP). Using the parameters as input data of HEC-l model, the design flood was estimated by applying Clark unit hydrograph method. The results showed that the design flood of 50 year frequency of this study was $8m^3/sec$ less than that of the previous fundamental plan in 1994. The value difference came from the different application of watershed parameter, different rainfall distribution (Huff quartile vs. Mononobe) and critical durations. We could infer that the GIS-based parameter preparation is more reasonable than the previous hand-made extraction of watershed parameters.