• Korean Journal of Hydrosciences
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• v.7
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• pp.125-137
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• 1996

The subject of the paper is the selection of the number and location of raingauge stations among existing ones for the computation of mean areal precipitation and for use as input of real-time flow prediction models. The weighted average method developed by National Weather Service was used to compute MAP over the Boone River basin in Iowa with a 40 year daily data set. Two different searching methods were used to find local optimal solutions. An operational rainfall-runoff model was used to determine the optimal location and number of stations for flow prediction.

• Journal of Korea Water Resources Association
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• v.56 no.1
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• pp.35-43
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• 2023

Future runoff analysis is influenced by climate change scenarios and hydrologic model parameters, with uncertainties. In this study, the uncertainty of future runoff analysis according to the shared socioeconomic pathway (SSP) scenario and hydrologic model parameters was analyzed. Among the SSP scenarios, the SSP2-4.5 and SSP5-8.5 scenarios were used, and the soil and water assessment tool (SWAT) model was used as the hydrologic model. For the parameters of the SWAT model, a total of 11 parameter were optimized to the observed runoff data using SWAT-CUP. Then, uncertainty analysis of future estimated runoff compared to the observed runoff was performed using jensen-shannon divergence (JS-D), which can calculate the difference in distribution. As a result, uncertainty of future runoff was analyzed to be larger in SSP5-8.5 than in SSP2-4.5, and larger in the far future (2061-2100) than in the near future (2021-2060). In this study, the uncertainty of future runoff using future climate data according to the parameters of the hydrologic model is as follows. Uncertainty was greatly analyzed when parameters used observed runoff data in years with low flow rates compared to average years. In addition, the uncertainty of future runoff estimation was analyzed to be greater for the parameters of the period in which the change in runoff compared to the average year was greater.

• Journal of Korea Water Resources Association
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• v.36 no.6
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• pp.1025-1033
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• 2003

In common with workers in hydrologic fields, scientists and engineers relate one variable to two or more other variables for purposes of predication, optimization, and control. Statistics methods have improved to establish such relationships. Regression, as it is called, is indeed the most commonly used statistics technique in hydrologic fields; relationship between the monitored variable stage and the corresponding discharges(rating curve). Regression methods expressed in the form of mathematical equations which has parameters, so called parametric methods. some times, the establishment of parameters is complicated and uncertain. Many non-parametric regression methods which have not parameters, have been proposed and studied. The most popular of these are kernel regression method. Kernel regression offer a way of estimation the regression function without the specification of a parametric model. This paper conducted comparisons of some bandwidth selection methods which are using the least squares and cross-validation.

• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.3
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• pp.59-68
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• 2005

The rainfall-runoff potential of Jangseong reservoir watershed was studied based on SCS (Soil Conservation Service, which is now the NRCS, Natural Resources Conservation Service, USDA) runoff curve number (CN) technique. Precipitation and reservoir operation data had been collected. The rainfall-runoff pairs from the watershed for ten years was estimated using reservoir water balance analysis using reservoir operation records. The maximum retention, S, for each storm event from rainfall-runoff pair was estimated for selected storm events. The estimated S values were arranged in descending order, then its probability distribution was determined as log-normal distribution, and associated CNs were found about probability levels of Pr=0.1, 0.5, and 0.9, respectively. A subwatershed that has the similar portions of land use categories to the whole watershed of Jangseong reservoir was selected and hydrologic monitoring was conducted. CNs for subwatershed were determined using observed data. CNs determined from observed rainfall-runoff data and reservoir water balance analysis were compared to the suggested CNs by the method of SCS-NEH4. The $CN_{II}$ measured and estimated from water balance analysis in this study were 78.0 and 78.1, respectively. However, the $CN_{II}$, which was determined based on hydrologic soil group, land use, was 67.2 indicating that actual runoff potential of Jangseong reservoir watershed is higher than that evaluated by SCS-NEH4 method. The results showed that watershed runoff potential for large scale agricultural reservoirs needs to be examined for efficient management of water resources and flood prevention.

• Journal of Korea Water Resources Association
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• v.42 no.11
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• pp.953-961
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• 2009

The objective of this study is to develop a stochastic continuous storage function model for enhancement of an event-oriented watershed and channel storage function models which have been used as an official flood forecast model in Korea. For this study, soil moisture accounting component is added to the original storage function model and each hydrologic component, such as surface flow, subsurface flow, groundwater flow and actual evaportranspiration, is simulated as a function of soil water content. And also, ensemble Kalman filtering technique is used for real-time assimilation of measured streamflow from various stream locations in the watershed. Therefore the enhanced model will be able to simulate hydrologic components for long-term period without additional estimation of model parameters and to give more accurate and reliable results than those from the existing deterministic model due to the assimilation of measured streamflow data.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.106-106
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• 2015

The information of flow regimes continues to be norm in water resource and watershed management, in that stream flow regime is a crucial factor influencing water quality, geomorphology, and the community structure of stream biota. The objectives of this study were to estimate Korean stream flows from landscape variables, classify stream flow gages using hydraulic characteristics, and then apply these methods to ungaged biological monitoring sites for effective ecological assessment. Here I used a linear modeling approach (MLR, PCA, and PCR) to describe and predict seasonal flow statistics from landscape variables. MLR models were successfully built for a range of exceedance discharges and time frames (annual, January, May, July, and October), and these models explained a high degree of the observed variation with r squares ranging from 0.555 (Q95 in January) to 0.899 (Q05 in July). In validation testing, predicted and observed exceedance discharges were all significantly correlated (p<0.01) and for most models no significant difference was found between predicted and observed values (Paired samples T-test; p>0.05). I classified Korean stream flow regimes with respect to hydraulic and hydrologic regime into four categories: flashier and higher-powered (F-HP), flashier and lower-powered (F-LP), more stable and higher-powered (S-HP), and more stable and lower-powered (S-LP). These four categories of Korean streams were related to with the characteristics of environmental variables, such as catchment size, site slope, stream order, and land use patterns. I then applied the models at 684 ungaged biological sampling sites used in the National Aquatic Ecological Monitoring Program in order to classify them with respect to basic hydrologic characteristics and similarity to the government's array of hydrologic gauging stations. Flashier-lower powered sites appeared to be relatively over-represented and more stable-higher powered sites under-represented in the bioassessment data sets.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2B
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• pp.155-162
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• 2009

Univariate frequency analyses are widely used in practical hydrologic design. However, a storm event is usually characterized by amount, intensity, and duration of the storm. To fully understand these characteristics and to use them appropriately in hydrologic design, a multivariate statistical approach is necessary. This study applied a Gumbel mixed model to a bivariate storm frequency analysis using hourly rainfall data collected for 46 years at the Seoul rainfall gauge station in Korea. This study estimated bivariate return periods of a storm such as joint return periods and conditional return periods based on the estimation of joint cumulative distribution functions of storm characteristics. These information on statistical behaviors of a storm can be of great usefulness in the analysis and assessment of the risk associated with hydrologic design problems.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.1
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• pp.1-11
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• 2010

Generation and transportation of runoff and pollutant loads within watershed generated eutrophication at Daecheong reservoir. To improve water quality at Daecheong reservoir, the best management practices should be developed and applied at upper watersheds for water quality improvement at downstream areas. In this study, two small watersheds of upper Daecheong reservoir were selected. The Long-Term Hydrologic Impact Assessment (L-THIA) model has been widely used for the estimation of the direct runoff worldwide. To apply the L-THIA ArcView GIS model was evaluated for direct runoff and water quality estimation at small watershed. And the Web-based Hydrograph Analysis Tool (WHAT) was used for direct runoff separating from total flow. As a result, the $R^2$ (Coefficient of determination) value and Nash-Sutcliffe coefficient value for direct runoff comparison at An-nae watershed were 0.81 and 0.71, respectively. And the $R^2$ value and Nash-Sutcliffe coefficient value at Wol-oe were 0.95 and 0.93. The $R^2$ value of BOD, TOC, T-N and T-P at An-nae watershed were BOD 0.94, TOC 0.81, T-N 0.94 and T-P 0.89. And the $R^2$ value of BOD, TOC, T-N and T-P at Wol-oe watershed were BOD 0.80, TOC 0.93, T-N 0.86 and T-P 0.65. The result that estimated pollutant loadings using the L-THIA ArcView GIS model reflected well the measured pollutant loadings except for T-P in Wol-oe watershed. With L-THIA ArcView GIS model, the direct runoff and non-point pollutant (NPS) loadings in the watershed could be analyzed through simple input data such as daily rainfall, land uses, and hydrologic soil group.

• Proceedings of the Korea Water Resources Association Conference
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• 1989.07a
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• pp.17-30
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• 1989

In this study, more exact runoff phenomina of the watersheds were comprehened and the relationships between geographical factors of the selected watershed and the unit hydrograph characteristic variables representing runoff processes, were also established. Moreover, the estimation of the adequate design flood was presented, which is needed for the design of the hydrologic structures in the ungauged watersheds. And owing to these results, it is considered to be possible to execute the effective flood control projects of the river and the efficient water resources management.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.24-27
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• 1996

The storage function method(SFM) is one of hydrologic flood routings which has been used most widely in Korea and Japan. This paper presents a storage function method using multiple model adaptive estimation(MMAE), in which a model set is generated by partitioning storage parameters over feasible range, and each storage function model is estimated, and then the weighted average of them is calculated. Finally, the future runoff is predicted in real time by means of observed data of water level at dam and rainfall. Simulation results applied to actual data show that the proposed method has much better performance than that of conventional SFM.