• Journal of Korea Water Resources Association
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• v.37 no.8
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• pp.631-641
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• 2004

The objective of this study is to test the applicability of SLURP (Semi-distributed Land Use-based Runoff Process) on Soyanggang-dam watershed. SLURP model is a conceptual semi-distributed form model that can be used to examine irrigation plan and the effects of proposed changes in water management within a basin or to see what effects external factors such as climate change or changing land cover might have on various water users. Topographical parameters were derived from DEM using TOPAZ and SLURPAZ. Monthly NDVIs were calculated from multi-temporal NOAA/AVHRR images during four years (1998 ∼ 2001). Weather elements (dew-point temperature, solar radiation, maximum/minimum temperature and relative humidify) were obtained from five meteorological stations within and near the study area. To simulate daily hydrograph during 1998 ∼ 2001, the model parameters of each land cover class were optimized by sensitivity analysis and SCE-UA method. Test result of SLURP was summarized by various statistics method (WMO volume error, Nash-Sutcliffe efficiency, mean error and coefficient of variation).

• Journal of Korea Water Resources Association
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• v.51 no.spc
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• pp.1045-1056
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• 2018

During the last decades, considerable efforts have been spent for climate studies, in particular to better understand changing climate. In turn, several significant trends in climatic variables have been reported. Explaining such trends is challenging - some of them have been considered contradictory to another. Various hypotheses have also been suggested for general description of changing climate. At this point in time, it would be beneficial to look back and carefully recollect our knowledge about climate change. In this paper, we aim to provide a comprehensive review on our forefront knowledge in this context with focus on the trends in temperature, solar radiation, wind speed, evaporation, and precipitation. Major trends, namely warming, dimming, and stilling, are demonstrated together with evaporation paradox and increasing precipitation variability, using data at Seoul. On the basis of understanding these notions, we suggest four key implications to hydrologists and engineers.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.18-18
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• 2011

Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2020.12a
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• pp.62-62
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• 2020

Ginseng is a shade-plant cultivated using shading facilities. However, at too low light levels, root growth is poor, and at high light levels, the destruction of chlorophyll reduces the photosynthesis efficiency due to leaf burn and early fall leaves. The ginseng has a lightsaturation point of 12,000~15,000 lux when grown at 15 to 20℃ and 9,500 lux at 25℃. This study was conducted to select the optimal light intensity of 3-year-old ginseng grown in blue-white film plastic house. The seeds were planted in the blue-white film plastic house with different light receiving rate (March 17, 2020). Between April and September, the average air temperature in the house was 20.4-20.7℃. Average soil temperature was 18.3℃-18.5℃. The chemical properties of the test soil was as follows. The pH level was 7.0-7.4, EC was 0.5-0.6 dS/m, OM was at the levels of 33.6-37.7 g/kg, P₂O₅ was 513.0-590.8 mg/kg, slightly higher than the allowable 400 mg/kg. The amount of light intensity, illuminance, and solar radiation in the blue-white film house was increased as the light-receiving rate increased and the amount of light intensity was found to be 9-14% compared to the open field, 8-13% illuminance and 9-14% solar irradiation respectively. The photosynthesis rate was the lowest at 3.1 µmolCO²/m²/s in the 9% light blue-white plastic house and 4.2 and 4.0 µmolCO²/m²/s in the 12% and 14% light blue-white plastic house, respectively. These results generally indicate that the photosynthesis of plants increases with the amount of light, but the ginseng has a lower light saturation point at high temperatures, and the higher the amount of light, the lower the photosynthetic efficiency. The SPAD (chlorophyll content) value decreased as the increase of light-receiving rate, and was the highest at 32.7 in 9% light blue-white plastic house. Ginseng germination started on April 11 and took 13-15 days to germinate. The overall germination rate was 82.9-85.8%. The plant height and length of stem were long in the 9% light-receiving plastic house. The diameter of stem was thick in the 12-14% light-receiving plastic house. In the 12% and 14% light-receiving plastic house, the length and diameter of taproot was long and thick, so the fresh weight of root per plant was 20 g or more, which was heavier than 16.9 g of the 9% light-receiving plastic house. The disease incidence (Alternaria blight, Gray mold and Damping-off etc.) rate were 0.9-2.7%. The incidence of Sclerotinia rot disease was 7.5-8.4%, and root rot was 0-20.0%. The incidence ratio of rusty root ginseng was 34.4-38.7% level, which was an increase from the previous year's 15% level.

• Economic and Environmental Geology
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• v.39 no.3 s.178
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• pp.255-268
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• 2006

Recent 22-year (1981-2002) meteorological data of 58 Korea Meteorological Adminstration (KMA) station were analyzed to investigate spatial and temporal variation of surface air temperature (SAT) and ground surface temperature (GST) in Korea. Based on the KMA data, multiple linear regression (MLR) models, having two regression variables of latitude and altitude, were presented to predict mean surface air temperature (MSAT) and mean ground surface temperature (MGST). Both models showed a high accuracy of prediction with $R^2$ values of 0.92 and 0.94, respectively. The prediction of MGST is particularly important in the areas of geothermal energy utilization, since it is a critical parameter of input for designing the ground source heat pump system. Thus, due to a good performance of the MGST regression model, it is expected that the model can be a useful tool for preliminary evaluation of MGST in the area of interest with no reliable data. By a simple linear regression, temporal variation of SAT was analyzed to examine long-term increase of SAT due to the global warming and the urbanization effect. All of the KMA stations except one showed an increasing trend of SAT with a range between 0.005 and $0.088^{\circ}C/yr$ and a mean of $0.043^{\circ}C/yr$. In terms of meteorological factors controlling variation of GST, the effects of solar radiation, terrestrial radiation, precipitation, and snow cover were also discussed based on quantitative and qualitative analysis of the meteorological data.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.311-325
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• 2023

This study was conducted to analyze the habitat suitability of the major honey trees including Kalopanax septemlobus Koidz., Prunus spp., Tilia spp., and Styrax obassia Siebold & Zucc. indigenous to mountain Gariwang and Yumeong using the machine learning approach (i.e., MaxEnt model). The AUC values of the model predictions were mostly above 0.7, and the results of the response curves showed that the environmental drivers that had effects on the habitat suitability of the major honey trees were elevation, mean annual precipitation, and mean annual temperature. These results indicate that climatic drivers along the elevation gradient are the main environmental drivers in explaining the distribution patterns of the major honey trees. In addition, the results of the response curves of Prunus spp. and Styrax obassia Siebold & Zucc. differed slightly in terms of slope and mean annual solar radiation as the main environmental drivers. The results of this study will be valuable for the establishment of honey tree forests and management plans for the natural and artificial forests in South Korea, as well as for the mapping the distribution of honey trees. Further studies at different regional levels, reflecting biotic drivers, will be needed to expand the production of honey and pollen at different strata and to produce honey annually.

• Magazine of the Korean Society of Agricultural Engineers
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• v.32 no.3
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• pp.116-129
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• 1990

A rational management of water resources in estuary reservoirs necessiates the prediction of water quality. In this study, a multiple box model for the water quality prediction was developed as a tool for the purpose of examining an adequate way to improve and maintain the water quality. Some submodels that are suitable for simulating the mixing behavior of pollutant materials in a lake were considered in this model. The model was appiled for predicting water qualities of Haenam Esturay Reservoir. The result from this study can be summarized as follows : 1.A water quality simulation model that can predict the 10-day mean value of water qualities was developed by adding some submodels that simulate the concentrations of chlorophyll-a, BOD, T-P and T-N to the existing Multiple Box Model representing the mixing and circulating of materials by the hydarulic action. 2.As input data for the model developed, the climatic data including precipitation, solar radiation, temperature, cloudness, wind speed and relative humidity, and the water buget records including the pumping discharge and the releasing discharge by drainage gate were ollected. The hydrologic data for the inflow discharge from the watershed was obtained by simulation with the aid of USDAUL-74/SNUA watershed model. Also the water quality data were measured at streams and the reservoir. 3.As a result of calibration and verification test by using four comonents of water quality such as Chlorophyll-a, BOD, T-P and T-N, it was found that the correlation coefficeints between the observed and the simulated water qualities showed greater than 0.6, therefore the capability of the model to simulate the water quality was proved. 4.The result based on the model application showed that the water quality of the Haenam Estuary Reservoir varies seasonally with the harmonic trend, however the water quality is good in winter and get worse in summer. Also it may be concluded that the current grarde of water quality in the Heanam Esutary Reservoir is ranked as grade 4 suitable only for the agricultutal use.

• Ocean and Polar Research
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• v.37 no.4
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• pp.327-332
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• 2015

Isotopic compositions of ice and meltwater play a very crucial role in paleoclimate studies based on ice cores and water resources research conducted in alpine hydrogeology. Better understanding of variations in the stable isotopic compositions of water is required since changes from ice to liquid water are gaining more attention due to recent climate change. In this work, a melting experiment was designed and conducted to investigate how the isotopic compositions of ice vary with time by heat sources, such as solar radiation. We conducted the melting experiment for 22 hours. The discharge rate rose to a maximum value after 258 minutes and gradually declined because we fixed the heat source. The isotopic compositions of meltwater increased linearly or to a second degree polynomial. The linear relationship between oxygen and hydrogen has a slope of 6.8, which is less than that of the Global Meteoric Water Line (8) and higher than a theoretical value (6.3). The deuterium excess decreased when ${\delta}D$ or ${\delta}^{18}O$ increases or vise versa since the slope of the relationship for ice-liquid exchange is less than 8. These findings and the apparatus of the melting experiments will make a helpful contribution to the studies of stable isotopes and the melting process in temperate and polar regions.

• Journal of Korea Water Resources Association
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• v.46 no.9
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• pp.933-946
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• 2013

The quantitative analysis of evapotranspiration (ET) is a key component in hydrological studies and the establishment of water resources planning. Generally, the quantitative analysis of ET is performed by the estimation method of potential or reference ET based on meteorological factors such as air temperature, wind speed, etc. Hargreaves equation is one of empirical methods for reference ET using air temperature data. In this study, in order to estimate more exact reference ET considering climatological characteristics in Korea, parameter regionalization of Hargreaves equation is carried out. Firstly, modified Hargreaves equation is presented after the analysis of the relationship between solar radiation and temperature. Secondly, parameter ($K_{ET}$) optimization of Hargreaves equation is performed using Penman-Monteith method and modified equation at 71 weather stations. Lastly, the equation for calculating $K_{ET}$ using temperature data is proposed and verified. As a result, reference ET from original Hargreaves equation is overestimated or underestimated compared with Penman-Monteith method. But modified equation in this study is more accurate in the climatic conditions of Korea. In addition, the applicability of the equation between $K_{ET}$ and temperature is confirmed.

• Journal of Bio-Environment Control
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• v.15 no.2
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• pp.162-166
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• 2006

The objectives of this study were to determine the effect of cultivation time on the incidence of brown fruit stem (BFS) in glasshouse sweet pepper (cv. Special) and to investigate environmental causes of this disorder. The plants transplanted on 31 August (T1) showed more incidence of BFS than those on 24 November (T2) (6.1% vs.2.9%; P<0.01). The BFS symptom began to appear after completion of fruit enlargement, more often around fruit coloring period. Comparing the environmental factors between T1 and T2, with their data collected for 3 weeks around fruit coloring period, the factor that was most likely responsible for BFS incidence was found to be the night-time humidity deficit (HD) ($1.9g{\cdot}m^{-3}\;vs\;2.9g{\cdot}m^{-3}HD$). These results were reconfirmed as T1 was compared to the plants (T3) that were transplanted at a similar time of the following year to T1, but designed to reduce BSF by increasing air HD via heating at night. That is,T3 had much higher night-time HD than T1 ($5.9g{\cdot}m^{-3}\;vs\;1.9g{\cdot}m^{-3}HD$), and showed no incidence of BFS. These results indicated that, to prevent BFS incidence in the winter-harvesting sweet pepper plants, air humidity at night should be controlled low, especially for the fruit coloring period after fruit enlargement period is completed.