• Journal of Bio-Environment Control
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• v.14 no.2
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• pp.95-105
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• 2005

This study was carried out to file up using effect and requirement of energy for environmental design data of Pleurotus eryngii growing houses. Heating and cooling Degree-Hour (D-H) were calculated and compared for. some Pleurotus eryngii growing houses of sandwich-panel (permanent) o. arch-roofed(simple) type structures modified and suggested through field survey and analysis. Also thermal resistance (R-value) was calculated for the heat insulating and covering materials of the permanent and simple-type, which were made of polyurethane or polystyrene panel and $7\~8$ layers heat conservation cover wall. The variations of heating and cooling D-H simulated for Jinju area was nearly linearly proportional to the setting inside temperatures. The variations of cooling D-H was much more sensitive than those of heating D-H. Therefore, it was expected that the variations of required energy in accordance with setting temperature or actual temperature maintained inside of the cultivation house could be estimated and also the estimated results of heating and cooling D-H could be effectively used far the verification of environmental simulation as well as for the calculation of required energy amounts. When the cultivation floor areas are all equal, panel type houses to be constructed by various combinations of materials were found to by far more effective than simple type pipe house in the aspect of energy conservation maintenance except some additional cost invested initially. And also the energy effectiveness of multi-span house compared to single span together with the prediction of energy requirement depending on the level insulated for the wall and roof area could be estimated. Additionally, structural as well as environmental optimizations are expected to be possible by calculating periodical and/or seasonal energy requirements for those various combinations of insulation level and different climate conditions, etc.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.1
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• pp.1-10
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• 2012

Digital Forecast of the Korea Meteorological Administration (KMA) represents 5 km gridded weather forecast over the Korean Peninsula and the surrounding oceanic regions in Korean territory. Digital Forecast provides 12 weather forecast elements such as three-hour interval temperature, sky condition, wind direction, wind speed, relative humidity, wave height, probability of precipitation, 12 hour accumulated rain and snow, as well as daily minimum and maximum temperatures. These forecast elements are updated every three-hour for the next 48 hours regularly. The objective of this study was to construct Forest Fire Danger Rating Systems on the Korean Peninsula (FFDRS_KORP) based on the daily weather index (DWI) and to improve the accuracy using the digital forecast data. We produced the thematic maps of temperature, humidity, and wind speed over the Korean Peninsula to analyze DWI. To calculate DWI of the Korean Peninsula it was applied forest fire occurrence probability model by logistic regression analysis, i.e. $[1+{\exp}\{-(2.494+(0.004{\times}T_{max})-(0.008{\times}EF))\}]^{-1}$. The result of verification test among the real-time observatory data, digital forecast and RDAPS data showed that predicting values of the digital forecast advanced more than those of RDAPS data. The results of the comparison with the average forest fire danger rating index (sampled at 233 administrative districts) and those with the digital weather showed higher relative accuracy than those with the RDAPS data. The coefficient of determination of forest fire danger rating was shown as $R^2$=0.854. There was a difference of 0.5 between the national mean fire danger rating index (70) with the application of the real-time observatory data and that with the digital forecast (70.5).

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.1
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• pp.11-22
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• 2010

According to IPCC 4th Assessment Report, concentration of carbon dioxide has been increasing by 30% since Industrial Revolution. Most of IPCC $CO_2$ emission scenarios estimate that the concentration will reach up to double of its present level within 100-year if the current tendency continues. The global warming has resulted in the agro-climate change over the Korean Peninsula as well. Accordingly, it is necessary to understand the future agro-climate induced by the increase of greenhouse gases in terms of the agro-climatic indices in the Korean peninsula. In this study, the future climate is simulated by an atmosphere/ocean/land surface/sea ice coupled general circulation climate model, Pusan National University Coupled General Circulation Model(hereafter, PNU CGCM), and by a regional weather prediction model, Weather Research and Forecasting Model(hereafter, WRF) for the purpose of a dynamical downscaling. The changes of the vegetable period and the crop growth period, defined as the total number of days of a year exceeding daily mean temperature of 5 and 10, respectively, have been analyzed. Our results estimate that the beginning date of vegetable and crop growth periods get earlier by 3.7 and 17 days, respectively, in spring under the $CO_2$-doubled climate. In most of the Korean peninsula, the predicted frost days in spring decrease by 10 days. Climatic production index (CPI), which closely represent the productivity of rice, tends to increase in the double $CO_2$ climate. Thus, it is suggested that the future $CO_2$ doubled climate might be favorable for crops due to the decrease of frost days in spring, and increased temperature and insolation during the heading date as we expect from the increased CPI.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.55-67
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• 2021

Hornbeams (Carpinus spp.), which are widely distributed in South Korea, are recognized as one of the most abundant species at climax stage in the temperate forests. Although the distribution and vegetation structure of the C. laxiflora community have been reported, little ecological information of C. tschonoskii is available. Little effort was made to examine the distribution shift of these species under the future climate conditions. This study was conducted to predict potential shifts in the distribution of C. laxiflora and C. tschonoskii in 2050s and 2090s under the two sets of climate change scenarios, RCP4.5 and RCP8.5. The MaxEnt model was used to predict the spatial distribution of two species using the occurrence data derived from the 6th National Forest Inventory data as well as climate and topography data. It was found that the main factors for the distribution of C. laxiflora were elevation, temperature seasonality, and mean annual precipitation. The distribution of C. tschonoskii, was influenced by temperature seasonality, mean annual precipitation, and mean diurnal rang. It was projected that the total habitat area of the C. laxiflora could increase by 1.05% and 1.11% under RCP 4.5 and RCP 8.5 scenarios, respectively. It was also predicted that the distributional area of C. tschonoskii could expand under the future climate conditions. These results highlighted that the climate change would have considerable impact on the spatial distribution of C. laxiflora and C. tschonoskii. These also suggested that ecological information derived from climate change impact assessment study can be used to develop proper forest management practices in response to climate change.

• Journal of The Korean Society of Grassland and Forage Science
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• v.42 no.2
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• pp.127-136
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• 2022

This study was conducted to estimate the damage of Whole Crop Maize (WCM) according to abnormal climate using machine learning and present the damage through mapping. The collected WCM data was 3,232. The climate data was collected from the Korea Meteorological Administration's meteorological data open portal. Deep Crossing is used for the machine learning model. The damage was calculated using climate data from the Automated Synoptic Observing System (95 sites) by machine learning. The damage was calculated by difference between the Dry matter yield (DMY)_normal and DMY_abnormal. The normal climate was set as the 40-year of climate data according to the year of WCM data (1978~2017). The level of abnormal climate was set as a multiple of the standard deviation applying the World Meteorological Organization(WMO) standard. The DMY_normal was ranged from 13,845~19,347 kg/ha. The damage of WCM was differed according to region and level of abnormal climate and ranged from -305 to 310, -54 to 89, and -610 to 813 kg/ha bnormal temperature, precipitation, and wind speed, respectively. The maximum damage was 310 kg/ha when the abnormal temperature was +2 level (+1.42 ℃), 89 kg/ha when the abnormal precipitation was -2 level (-0.12 mm) and 813 kg/ha when the abnormal wind speed was -2 level (-1.60 m/s). The damage calculated through the WMO method was presented as an mapping using QGIS. When calculating the damage of WCM due to abnormal climate, there was some blank area because there was no data. In order to calculate the damage of blank area, it would be possible to use the automatic weather system (AWS), which provides data from more sites than the automated synoptic observing system (ASOS).

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.396-402
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• 2014

The spring season in Korea features a dynamic landscape with a variety of flowers such as magnolias, azaleas, forsythias, cherry blossoms and royal azaleas flowering sequentially one after another. However, the narrowing of south-north differences in flowering dates and those among the flower species was observed in 2014, taking a toll on economic and shared communal values of seasonal landscape. This study was carried out to determine whether the 2014 incidence is an outlier or a mega trend in spring phenology. Data on flowering dates of forsythias and cherry blossoms, two typical spring flower species, as observed for the recent 60 years in 6 weather stations of Korea Meteorological Administration (KMA) indicate that the difference spanning the flowering date of forsythias, the flower blooming earlier in spring, and that of cherry blossoms that flower later than forsythias was 30 days at the longest and 14 days on an average in the climatological normal year for the period 1951-1980, comparing with the period 1981-2010 when the difference narrowed to 21 days at the longest and 11 days on an average. The year 2014 in particular saw the gap further narrowing down to 7 days, making it possible to see forsythias and cherry blossoms blooming at the same time in the same location. 'Cherry blossom front' took 20 days in traveling from Busan, the earliest flowering station, to Incheon, the latest flowering station, in the case of the 1951-1980 normal year, while 16 days for the 1981-2010 and 6 days for 2014 were observed. The delay in flowering date of forsythias for each time period was 20, 17, and 12 days, respectively. It is presumed that the recent climate change pattern in the Korean Peninsula as indicated by rapid temperature hikes in late spring contrastive to slow temperature rise in early spring immediately after dormancy release brought forward the flowering date of cherry blossoms which comes later than forsythias which flowers early in spring. Thermal time based heating requirements for flowering of 2 species were estimated by analyzing the 60 year data at the 6 locations and used to predict flowering date in 2014. The root mean square error for the prediction was within 2 days from the observed flowering dates in both species at all 6 locations, showing a feasibility of thermal time as a prognostic tool.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1691-1707
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• 2022

Cheonji Lake, the caldera of Baekdu Mountain, located on the border of the Korean Peninsula and China, alternates between melting and freezing seasonally. There is a magma chamber beneath Cheonji, and variations in the magma chamber cause volcanic antecedents such as changes in the temperature and water pressure of hot spring water. Consequently, there is an abnormal region in Cheonji where ice melts quicker than in other areas, freezes late even during the freezing period, and has a high-temperature water surface. The abnormal area is a discharge region for hot spring water, and its ice gradient may be used to monitor volcanic activity. However, due to geographical, political and spatial issues, periodic observation of abnormal regions of Cheonji is limited. In this study, the degree of ice change in the optimal region was quantified using a Landsat -5/-7/-8 optical satellite image and a Modified U-Net regression model. From January 22, 1985 to December 8, 2020, the Visible and Near Infrared (VNIR) band of 83 Landsat images including anomalous regions was utilized. Using the relative spectral reflectance of water and ice in the VNIR band, unique data were generated for quantitative ice variability monitoring. To preserve as much information as possible from the visible and near-infrared bands, ice gradient was noticed by applying it to U-Net with two encoders, achieving good prediction accuracy with a Root Mean Square Error (RMSE) of 140 and a correlation value of 0.9968. Since the ice change value can be seen with high precision from Landsat images using Modified U-Net in the future may be utilized as one of the methods to monitor Baekdu Mountain's volcanic activity, and a more specific volcano monitoring system can be built.

• Journal of Korea Water Resources Association
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• v.49 no.6
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• pp.551-563
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• 2016

According to the 4th and 5th assessment of the Intergovernmental Panel on Climate Change (IPCC), global climate has been rapidly changing because of the human activities since Industrial Revolution. The perceived changes were appeared strongly in temperature and concentration of carbon dioxide ($CO_2$). Global average temperature has increased about $0.74^{\circ}C$ over last 100 years (IPCC, 2007) and concentration of $CO_2$ is unprecedented in at least the last 800,000 years (IPCC, 2014). These phenomena influence precipitation, evapotranspiration and soil moisture which have an important role in hydrology, and that is the reason why there is a necessity to study climate change. In this study, Asia region was selected to simulate primary energy index from 1951 to 2100. To predict future climate change effect, Common Land Model (CLM) which is used for various fields across the world was employed. The forcing data was Representative Concentration Pathway (RCP) data which is the newest greenhouse gas emission scenario published in IPCC 5th assessment. Validation of net radiation ($R_n$), sensible heat flux (H), latent heat flux (LE) for historical period was performed with 5 flux tower site-data in the region of AsiaFlux and the monthly trends of simulation results were almost equaled to observation data. The simulation results for 2006-2100 showed almost stable net radiation, slightly decreasing sensible heat flux and quite increasing latent heat flux. Especially the uptrend for RCP 8.5 has been about doubled compared to RCP 4.5 and since late 2060s, variations of net radiation and sensible heat flux would be significantly risen becoming an extreme climate condition. In a follow-up study, a simulation for energy index and hydrological index under the detailed condition will be conducted with various scenario established from this study.

• Korean Journal of Environment and Ecology
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• v.29 no.3
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• pp.333-343
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• 2015

This research aims at identifying the goshawk's possible and replaceable breeding ground by using the MaxEnt prediction model which has so far been insufficiently used in Korea, and providing evidence to expand possible protection areas for the goshawk's breeding for the future. The field research identified 10 goshawk's nests, and 23 appearance points confirmed during the 3rd round of environmental research were used for analysis. 4 geomorphic, 3 environmental, 7 distance, and 9 weather factors were used as model variables. The final environmental variables were selected through non-parametric verification between appearance and non-appearance coordinates identified by random sampling. The final predictive model (MaxEnt) was structured using 10 factors related to breeding ground and 7 factors related to appearance area selected by statistics verification. According to the results of the study, the factor that affected breeding point structure model the most was temperature seasonality, followed by distance from mixforest, density-class on the forest map and relief energy. The factor that affected appearance point structure model the most was temperature seasonality, followed by distance from rivers and ponds, distance from agricultural land and gradient. The nature of the goshawk's breeding environment and habit to breed inside forests were reflected in this modeling that targets breeding points. The northern central area which is about $189.5 km^2$(2.55 %) is expected to be suitable breeding ground. Large cities such as Cheongju and Chungju are located in the southern part of Chungcheongbuk-do whereas the northern part of Chungcheongbuk-do has evenly distributed forests and farmlands, which helps goshawks have a scope of influence and food source to breed. Appearance point modeling predicted an area of $3,071 km^2$(41.38 %) showing a wider ranging habitat than that of the breeding point modeling due to some limitations such as limited moving observation and non-consideration of seasonal changes. When targeting the breeding points, a specific predictive area can be deduced but it is difficult to check the points of nests and it is impossible to reflect the goshawk's behavioral area. On the other hand, when targeting appearance points, a wider ranging area can be covered but it is less accurate compared to predictive breeding point since simple movements and constant use status are not reflected. However, with these results, the goshawk's habitat can be predicted with reasonable accuracy. In particular, it is necessary to apply precise predictive breeding area data based on habitat modeling results when enforcing an environmental evaluation or establishing a development plan.

• Journal of Korea Water Resources Association
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• v.41 no.12
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• pp.1219-1230
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• 2008

Stream inflows induced by flood runoffs have a higher density than the ambient reservoir water because of a lower water temperature and elevated suspended sediment(SS) concentration. As the propagation of density currents that formed by density difference between inflow and ambient water affects reservoir water quality and ecosystem, an understanding of reservoir density current is essential for an optimization of filed monitoring, analysis and forecast of SS and nutrient transport, and their proper management and control. This study was aimed to quantify the characteristics of inflow density current including plunge depth($d_p$) and distance($X_p$), separation depth($d_s$), interflow thickness($h_i$), arrival time to dam($t_a$), reduction ratio(${\beta}$) of SS contained stream inflow for different flood magnitude in Daecheong Reservoir with a validated two-dimensional(2D) numerical model. 10 different flood scenarios corresponding to inflow densimetric Froude number($Fr_i$) range from 0.920 to 9.205 were set up based on the hydrograph obtained from June 13 to July 3, 2004. A fully developed stratification condition was assumed as an initial water temperature profile. Higher $Fr_i$(inertia-to-buoyancy ratio) resulted in a greater $d_p,\;X_p,\;d_s,\;h_i$, and faster propagation of interflow, while the effect of reservoir geometry on these characteristics was significant. The Hebbert equation that estimates $d_p$ assuming steady-state flow condition with triangular cross section substantially over-estimated the $d_p$ because it does not consider the spatial variation of reservoir geometry and water surface changes during flood events. The ${\beta}$ values between inflow and dam sites were decreased as $Fr_i$ increased, but reversed after $Fr_i$>9.0 because of turbulent mixing effect. The results provides a practical and effective prediction measures for reservoir operators to first capture the behavior of turbidity inflow.