• Journal of Korea Water Resources Association
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• v.51 no.2
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• pp.175-182
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• 2018

Coastal sediment archives are used as indicators of changes on shore sediment production and fluvial sediment transport, but rivers crossing coastal plains may not be efficient conveyors of sediment to the coast. In some case there is a net loss of sediment in lower coastal plain reaches, so that sediment input from an upstream exceeds the sediment yield (SY) at the river mouth. The main source of sediment in coastal area is the load from land. In Korea, data on suspended SY are limited owing to a lack of logistic support for systematic sediment sampling activities. This paper presents an integrated approach to estimate SY for ungauged coastal basins, using a soil erosion model and a sediment delivery ratio (SDR) model. For applying the SDR model, a basin specific parameter was validated on the basis of field data. The proposed relationships may be considered useful for predicting suspended SY in ungauged basins that have geologic, climatic and hydrologic conditions similar to the study area.

• Journal of Korean Society on Water Environment
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• v.25 no.2
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• pp.245-255
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• 2009

CN values are changed by various surface condition, which is cover type or treatment, hydrologic condition, or percent impervious area, even the same combination of land use and hydrologic soil group. In this study, CN parameters were regionalized for Nakdong River Basin by Long-Term Hydrologic Impact Assessment (L-THIA) coupled with SCE-UA, which is one of the global optimization technique. Six watersheds were selected for calibration (optimization) and periodic validation and two watersheds for spatical validation as ungauged watershed within Nakdong River Basin. Nash-Sutcliffe (NS) values were 0.66~0.86 for calibration, 0.68~0.91 for validation, and 0.60 and 0.85 for ungauged watersheds, respectively. Urban area for the selected watersheds covered high impervious area with 85% for residential area and 92% for commercial/industrial/transportation area. Hydrologic characteristics for crop area was similar to row crop with contoured treatment and poor hydrologic condition. For the forested area, hydrologic characteristics could be clearly distinguished from the leaf types of plant. Deciduous, coniferous, and mixed forest showed low, moderate, and high runoff rates by representing wood with fair and poor hydrologic condition, and wood-grass combination with fair hydrologic condition, respectively. CN parameters from this study could be strongly recommended to be used to simulate runoff for ungauged watershed.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1193-1201
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• 2020

This study aims to develop a regression model that estimates a low-flow index that can be applied to ungauged basins. A total of 30 midsized basins in South Korea use long-term runoff data provided by the National Integrated Water Management System (NIWMS) to calculate average low-flow, average minimum streamflow, and low-flow index duration and frequency. This information is used in the correlation analysis with 18 basin factors and 3 climate change factors to identify the basin area, average basin altitude, average basin slope, water system density, runoff curve number, annual evapotranspiration, and annual precipitation in the low-flow index regression model. This study evaluates the model's accuracy by using the root-mean-square error (RMSE) and the mean absolute error (MAE) for 10 ungauged, verified basins and compares them with the previous model's low-flow calculations to determine the effectiveness of the newly developed model. Comparative analysis indicates that the new regression model produces average low-flow, attributed to the consideration of varied basin and hydrologic factors during the new model's development.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.6
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• pp.169-176
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• 2012

This study describes the estimation of upstream ungauged watershed streamflow using downstream discharge data. For downstream Dongchon (DC) and upstream Kumho (KH) water level stations in Kumho river basin ($2,087.9km^2$), three methods of Soil and Water Assessment Tool (SWAT) modeling, drainage-area ratio method and regional regression equation were evaluated. The SWAT was calibrated at DC with the determination coefficient ($R^2$) of 0.70 and validated at KH with $R^2$ of 0.60. The drainage-area ratio method showed $R^2$ of 0.93. For the regional regression, the watershed area, average slope, and stream length were used as variables. Using the derived equation at DC, the KH could estimate the flow with maximum 41.2 % error for the observed streamflow.

• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.563-574
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• 2023

Recently, climate change has affected functional responses of river basins to meteorological variables, emphasizing the importance of rainfall-runoff simulation research. Simultaneously, the growing interest in machine learning has led to its increased application in hydrological studies. However, it is not yet clear whether machine learning models are more advantageous than the conventional conceptual models. In this study, we compared the performance of the conventional GR6J model with the machine learning-based Random Forest model across 38 basins in Korea using both gauged and ungauged basin prediction methods. For gauged basin predictions, each model was calibrated or trained using observed daily runoff data, and their performance was evaluted over a separate validation period. Subsequently, ungauged basin simulations were evaluated using proximity-based parameter regionalization with Leave-One-Out Cross-Validation (LOOCV). In gauged basins, the Random Forest consistently outperformed the GR6J, exhibiting superiority across basins regardless of whether they had strong or weak rainfall-runoff correlations. This suggest that the inherent data-driven training structures of machine learning models, in contrast to the conceptual models, offer distinct advantages in data-rich scenarios. However, the advantages of the machine-learning algorithm were not replicated in ungauged basin predictions, resulting in a lower performance than that of the GR6J. In conclusion, this study suggests that while the Random Forest model showed enhanced performance in trained locations, the existing GR6J model may be a better choice for prediction in ungagued basins.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.3
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• pp.52-67
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• 2008

Recently, frequent occurrence of flash floods caused by climactic change has necessitated prompt and quantitative prediction of precipitation. In particular, the usability of rainfall radar that can carry out real-time observation and prediction of precipitation behavior has increased. Moreover, the use of distributed hydrological model that enables grid level analysis has increased for an efficient use of rainfall radar that provides grid data at 1km resolution. The use of distributed hydrologic model necessitates grid-type spatial data about target basins; to enhance reliability of flood runoff simulation, the use of visible and precise data is necessary. In this paper, physically based $Vflo^{TM}$ model and ModClark, a quasi-distributed hydrological model, were used to carry out flood runoff simulation and comparison of simulation results with data from Imjin River Basin, two-third of which is ungauged. The spatial scope of this study was divided into the whole Imjin River basin area, which includes ungauged area, and Imjin River basin area in South Korea for which relatively accurate and visible data are available. Peak flow and lag time outputs from the two simulations of each region were compared to analyze the impact of uncertainty in topographical parameters and soil parameters on flood runoff simulation and to propose effective methods for flood runoff simulation in ungauged regions.

• Journal of Korean Society on Water Environment
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• v.34 no.5
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• pp.537-547
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• 2018

Sediment discharge by rainfall runoff affects water quality in rivers such as turbid water, eutrophication. In order to solve various problems caused by soil loss, it is important to establish a sediment management plan for watersheds and rivers in advance. However, there is a lack of sediment data available for estimating sediment discharge in ungauged basins.. Thus, reasonable research is very important to evaluate and predict the sediment discharge quantitatively. In this study, cluster analysis was conducted to classify gauged watersheds into hydrologically homogeneous groups based on the watershed characteristics. Also, this study suggests a method to efficiently predict the sediment discharge for ungauged basins by developing and evaluating the SDR equations based on the PA-SDR module. As the result, the SDR equations for the classified watersheds were derived to predict the most reasonable sediment discharge of ungauged basins with 0.24 % ~ 10.89 % errors. It was found that the optimal parameters for the gauged basins reflect well characteristic of sediment movement. SDR equations proposed in this study will be available for estimating sediment discharge on ungauged basins. Also it is possible to utilize establishing the appropriate sediment management plan for integrated management of watershed and river in Korea.

• Journal of Korea Water Resources Association
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• v.49 no.8
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• pp.645-656
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• 2016

The study performed a regional flood frequency analysis and proposed a regression equation to estimate design floods corresponding to return periods for ungauged basins in Geum-river basin. Five preliminary tests were employed to investigate hydrological independence and homogeneity of streamflow data, i.e. the lag-one autocorrelation test, time homogeneity test, Grubbs-Beck outlier test, discordancy measure test ($D_i$), and regional homogeneity measure (H). The test results showed that streamflow data were time-independent, discordant and homogeneous within the basin. Using five probability distributions (generalized extreme value (GEV), three-parameter log-normal (LN-III), Pearson type 3 (P-III), generalized logistic (GLO), generalized Pareto (GPA)), comparative regional flood frequency analyses were carried out for the region. Based on the L-moment ratio diagram, average weighted distance (AWD) and goodness-of-fit statistics ($Z^{DIST}$), the GLO distribution was selected as the best fit model for Geum-river basin. Using the GLO, a regression equation was developed for estimating regional design floods, and validated by comparing the estimated and observed streamflows at the Ganggyeong station.

• Journal of Korea Water Resources Association
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• v.43 no.4
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• pp.353-365
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• 2010

Generally, river discharge is measured at flood forecasting points, upstream dam points, large rivers, and important points over a basin, and it is hard to estimate discharge of medium or small stream and small catchment. Physically based rainfall-runoff model with geographical parameters can simulate discharge at all the points within a basin with optimized parameters for a point in the basin. In this study, GRM (Grid based Rainfall-runoff Model) calibrated at the outlet is applied. The discharge at upstream point is estimated and the possibility of model regionalisation is examined for ungauged catchment of small or medium stream within a river system. Wicheon and Boksu watershed in Nakdonggang (Riv.) and Yudeungcheon (Riv.) respectively are selected. The discharge at Miseong and Sindae station is simulated with the parameters estimated at Museong and Boksu station. The results of Miseong and Sindae station show good agreement with observed hydrographs in peak discharge and peak time and consistently linear relationships with high correlations in discharge volume, peak discharge, and peak time. And it shows GRM could be applied to estimate discharge at ungauged catchments along a river system.

• Spatial Information Research
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• v.14 no.1 s.36
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• pp.15-27
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• 2006

This paper is about the threshold discharge computation using GIUH(Geomorphoclimatic Instantaneous Unit Hydrograph) on ungauged small basin. GIUH is one of the possible approaches to predicting the hydrograph characteristics. This study is calculated the various ways which are hydrologic characteristics, bankfull flows, unit peak flows(the Clark, the Nakayasu and the S.C.S) as well as threshold runoffs on about $5km^2$ scale at Kyungbuk gampo in subbasin. We are estimated propriety that peak discharge calculated the GIUH from acquiring data by GIS(Geographic Information System) compared to observed peak discharge. And, the threshold discharge was calculated by NRCS(Natural Resources Conservation Service) for a flash flood standard rainfall.