• Water for future
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• v.26 no.3
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• pp.47-61
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• 1993

A menu-driven shell program DSFS (Daily Streamflow Simulation Model), that can process the input data, optimize the parameters, execute the program, and graphically display the results of a modified tank model, was developed and applied to simulating daily streamflow from small watersheds. The model defines daily watershed evapotranspiration losses from potential values multiplied by monthly landuse coefficients and correction factors for soil water storage levels. The parameters were calibrated using observed hydrologic data for fifteen watersheds, and the results were correlated with watershed parameters to define empirical relationships. The proposed model was tested with streamflow data of ungaged conditions, and the simulation results overestimated the annual runoff.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.4
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• pp.51-61
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• 2002

The objective of this study is to develop GLEANS-PADDY model to predict nutrients loading from paddy-field areas. This model is developed by modifying the GLEANS model which is used for uplands, and composed of hydrology and nutrient submodels. The optimal field size for CLEANS-PADDY model application is about up to 50 ha with mild slope, relatively homogeneous Soils and spatially rainfall, and a single crop farming. The CLEAMS model is modified to handle ponded soil surface condition and saturated soil profile in paddy field. In the hydrology submodel of the CLEAMS-PADDY model. the ponded depth routing method is used to handle the ponded water condition of paddy field. To compute potential evapotranspiration the FAO-24 Corrected Blaney-Criddle method is used for paddy field instead of Penman-Monteith method in the CLEAMS model. In the nutrients submodel of the CLEAMS-PADDY model, the soil was assumed saturated and soil profile in the root zone was divided into oxidized and reduced zones.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.428-428
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• 2017

In this study, three optimization techniques efficiency is assessed for calibration of the GR4J model for streamflow simulation in Selmacheon, Boryeong Dam and Kyeongancheon watersheds located in South Korea. The Penman-Monteith equation is applied to estimate the potential evapotranspiration, model calibration, and validation is carried out using the readily available daily hydro-meteorological data. The Shuffled Complex Evolution-University of Arizona(SCE-UA), Uniform Adaptive Monte Carlo (UAMC), and Coupled Latin Hypercube and Rosenbrock (CLHR) optimization techniques has been used to evaluate the robustness, performance and optimized parameters of the three catchments. The result of the three algorithms performances and optimized parameters are within the recommended ranges in the tested watersheds. The SCE-UA and CLHR outputs are found to be similar both in efficiency and model parameters. However, the UAMC algorithms performances differently in the three tested watersheds.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.326-326
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• 2018

The study will assess the seasonal effect of hydrological models on performance and parameters for streamflow simulation. TPHM, GR4J, CAT, and TANK-SM hydrological models will be applied for simulating streamflow in ten small and large watersheds located in South Korea. The readily available hydrometeorological data will be applied as an input to the four hydrological models and the potential evapotranspiration will be computed using the Penman-Monteith equation. The SCE-UA algorithm implemented in PEST will be used to calibrate the models considering similar objective functions bedside the calibration will be renewed to capture the seasonal effects on the model performance and parameters. The seasonal effects on the model performance and parameters will be presented after assessing the four hydrologic models results. The conventional approach and season-based results will be evaluated for each model in the tested watersheds and a conclusion will be made based on the finding of the results.

• Korean Journal of Agricultural and Forest Meteorology
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• v.5 no.3
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• pp.158-165
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• 2003

This study was conducted to reveal the role of meteorological elements on the habitat characteristics and vegetative structure for S. commixta natural populations at Ulleung Island. Potential Evapotranspiration(PET) by elevation of Ulleung Island was estimated using Thornthwaite's climatology estimating method. Also, Warm Index (WI), Coldness Index (CI) and vegetative composition by elevation were determined. The following results were obtained: The S. commixta trees wire mainly distributed from an elevation of 300 m to 900 m. The WI and CI were about 66.8∼95.0, -21.5∼-7.7, respectively. Water deficit by precipitation and Potential Evapotranspiration (PET) mainly occurred from March to October at all elevations. But wafer deficits diminished with increased elevation. The apparent species in S. commixta natural populations at Ulleung Island were: 10 tree layer species, 17 subtree layer species, and 25 species in the shrub layer. In the tree layer, S. commixta was dominant with the highest value of 46.85, then Fagus crenate 13.43, Acer mono and Tilia amurensis 12.41 and 12.03, respectively. In the subtree layer, A. mono was dominant with the highest value of 13.16, then F. crenata 12.68, Acer pseudo-sieboldianum and S. commixta 11.37 and 10.76, respectively. Dominant species and IV values in the shrub layer were Sasa borealis (22.09) and Rhododendron brachycarpum (10.51). The S. commixta natural forests were in a relatively stable rendition because of the even distribution of its various indexes: the species diversity index of Shannon, the evenness index and dominance were 0.6199∼1.1390, 0.6199∼0.8825 and 0.1852∼0.3801, respectively.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.35 no.6
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• pp.504-511
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• 1990

Weather data acquisition and potential evapotranspiration (PET) calculation procedure were investigated to support the agricultural development efforts in the mid-altitude mountainous region of Cheju Island. Automated weather stations (AWS) were installed at two points representing the east and the west of the study area. A personal computer was employed to collect the near-real time weather data from AWS through the public telephone line. Hourly data were available for solar radiation, air and soil temperature, relative humidity, wind speed and direction, and precipitation. Based on the data for the month of June 1989, daily climatic features were comparatively analyzed for the two areas and the Penman equation was used to calculate PET. Air temperature was higher by 1 to 2 degree C in the east due mainly to the higher solar radiation and partly to the Fohn effect caused by the daytime southwesterly blowing over Mt. Halla. Diurnal march of soil temperature lagged by 4 hours behind that of air temperature and the diurnal range for 10cm subsurface soil was 3 degree C. Wind was consistently stronger and a marked sea-land breeze circulation was detected in the west. Calculated PET values were higher in the east by 6% than in the west. Overall values from the east and the west of the mid-altitude mountainous region were higher by 30% than those of the coastal region, which were estimated from the Class A Pan evaporation measured by the Korea Meteorological Service Offices.

• Journal of Wetlands Research
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• v.19 no.1
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• pp.164-171
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• 2017

This study analysed 7 distribution features of dominant natural vegetation, such as elevation, slope, aspect, topographic index, annual mean temperature, warmth index and potential evapotranspiration using geographic information system(GIS) in Gayasan national park. The Gayasan national park has total 128 communities in which Pinus densiflora community occupies with 29.42%, Quercus mongolica community 27.66% relatively. These two communities comprise 80.58% out of total area, considering Q. mongolica & P. densiflora dominantly mixed communities. The Q. mongolica communities range around 575~1,065m(80.4%) in elevation, and the P. densiflora communities range around 465~965m(84.1%), respectively. The slopes of those two communities areas showed over $21^{\circ}$(78.0%) and (71.3%) respectively. In terms of slope aspect occurrence, Q. mongolica communities occur mostly on northern slope, and the P. densiflora communities on southern slope. The topographic indices of both communities occur around 5~6 most frequently. The Annual mean temperature distributions of Q. mongolica and P. densiflora range $7{\sim}8^{\circ}C$(83%), $8{\sim}9^{\circ}C$(84%), respectively, And the warmth index range of Q. mongolica is $59{\sim}70^{\circ}C{\cdot}month$ and the P. densiflora community, $58{\sim}88^{\circ}C{\cdot}month$. The potential evapotranspiration ranges mostly from 560 to 590mm/yr, in Q. mongolica communities, and from 580 to 610mm/yr in P. densiflora communities.

• Journal of Korea Water Resources Association
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• v.44 no.5
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• pp.389-406
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• 2011

The objective of this study is to examine the climate change impact assessment on Korean water resources considering the uncertainties of Global Climate Models (GCMs) and hydrological models. The 3 different emission scenarios (A2, A1B, B1) and 13 GCMs' results are used to consider the uncertainties of the emission scenario and GCM, while PRMS, SWAT, and SLURP models are employed to consider the effects of hydrological model structures and potential evapotranspiration (PET) computation methods. The 312 ensemble results are provided to 109 mid-size sub-basins over South Korean and Gaussian kernel density functions obtained from their ensemble results are suggested with the ensemble mean and their variabilities of the results. It shows that the summer and winter runoffs are expected to be increased and spring runoff to be decreased for the future 3 periods relative to past 30-year reference period. It also provides that annual average runoff increased over all sub-basins, but the increases in the northern basins including Han River basin are greater than those in the southern basins. Due to the reason that the increase in annual average runoff is mainly caused by the increase in summer runoff and consequently the seasonal runoff variations according to climate change would be severe, the climate change impact on Korean water resources could intensify the difficulties to water resources conservation and management. On the other hand, as regards to the uncertainties, the highest and lowest ones are in winter and summer seasons, respectively.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1803-1818
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• 2021

As the frequency of drought increases due to climate change, it is very important to have a monitoring system that can accurately determine the situation of widespread drought. However, while ground-based meteorological data has limitations in identifying all the complex droughts in Korea, satellite remote sensing data can be effectively used to identify the spatial characteristics of drought in a wide range of regions and to detect drought. This study attempted to analyze the possibility of using remote sensing data for drought identification in South Korea. In order to monitor various aspects of drought, remote sensing and ground observation data of precipitation and potential evapotranspiration, which are major variables affecting drought, were collected. The evaluation of the applicability of remote sensing data was conducted focusing on the comparison with the observation data. First, to evaluate the applicability and accuracy of remote sensing data, the correlations with observation data were analyzed, and drought indices of various aspects were calculated using precipitation and potential evapotranspiration for meteorological drought monitoring. Then, to evaluate the drought monitoring ability of remote sensing data, the drought reproducibility of the past was confirmed using the drought index. Finally, a high-resolution drought map using remote sensing data was prepared to evaluate the possibility of using remote sensing data for actual drought in South Korea. Through the application of remote sensing data, it was judged that it would be possible to identify and understand various drought conditions occurring in all regions of South Korea, including unmeasured watersheds in the future.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.127-137
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• 2024

Physical models, which are often used for water resource management, are difficult to build and operate with input data and may involve the subjective views of users. In recent years, research using data-driven models such as machine learning has been actively conducted to compensate for these problems in the field of water resources, and in this study, an artificial neural network was used to simulate long-term rainfall runoff in the Osipcheon watershed in Samcheok-si, Gangwon-do. For this purpose, three input data groups (meteorological observations, daily precipitation and potential evapotranspiration, and daily precipitation - potential evapotranspiration) were constructed from meteorological data, and the results of training the LSTM (Long Short-term Memory) artificial neural network model were compared and analyzed. As a result, the performance of LSTM-Model 1 using only meteorological observations was the highest, and six LSTM-MLP ensemble models with MLP artificial neural networks were built to simulate long-term runoff in the Fifty Thousand Watershed. The comparison between the LSTM and LSTM-MLP models showed that both models had generally similar results, but the MAE, MSE, and RMSE of LSTM-MLP were reduced compared to LSTM, especially in the low-flow part. As the results of LSTM-MLP show an improvement in the low-flow part, it is judged that in the future, in addition to the LSTM-MLP model, various ensemble models such as CNN can be used to build physical models and create sulfur curves in large basins that take a long time to run and unmeasured basins that lack input data.