• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.1
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• pp.29-41
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• 2019

Terrestrial Gross Primary Production (GPP) is the largest global carbon flux, and forest ecosystems are important because of the ability to store much more significant amounts of carbon than other terrestrial ecosystems. There have been several attempts to estimate GPP using mechanism-based models. However, mechanism-based models including biological, chemical, and physical processes are limited due to a lack of flexibility in predicting non-stationary ecological processes, which are caused by a local and global change. Instead mechanism-free methods are strongly recommended to estimate nonlinear dynamics that occur in nature like GPP. Therefore, we used the mechanism-free machine learning techniques to estimate the daily GPP. In this study, support vector machine (SVM), random forest (RF) and artificial neural network (ANN) were used and compared with the traditional multiple linear regression model (LM). MODIS products and meteorological parameters from eddy covariance data were employed to train the machine learning and LM models from 2006 to 2013. GPP prediction models were compared with daily GPP from eddy covariance measurement in a deciduous forest in South Korea in 2014 and 2015. Statistical analysis including correlation coefficient (R), root mean square error (RMSE) and mean squared error (MSE) were used to evaluate the performance of models. In general, the models from machine-learning algorithms (R = 0.85 - 0.93, MSE = 1.00 - 2.05, p < 0.001) showed better performance than linear regression model (R = 0.82 - 0.92, MSE = 1.24 - 2.45, p < 0.001). These results provide insight into high predictability and the possibility of expansion through the use of the mechanism-free machine-learning models and remote sensing for predicting non-stationary ecological processes such as seasonal GPP.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.427-435
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• 2023

Changes in flowering time due to weather fluctuations impact plant growth and ecosystem dynamics. Accurate prediction of flowering timing is crucial for effective forest ecosystem management. This study uses a process-based model to predict flowering timing in 2023 for five major tree species in Korean forests. Models are developed based on nine years (2009-2017) of flowering data for Abeliophyllum distichum, Robinia pseudoacacia, Rhododendron schlippenbachii, Rhododendron yedoense f. poukhanense, and Sorbus commixta, distributed across 28 regions in the country, including mountains. Weather data from the Automatic Mountain Meteorology Observation System (AMOS) and the Korea Meteorological Administration (KMA) are utilized as inputs for the models. The Single Triangle Degree Days (STDD) and Growing Degree Days (GDD) models, known for their superior performance, are employed to predict flowering dates. Daily temperature readings at a 1 km spatial resolution are obtained by merging AMOS and KMA data. To improve prediction accuracy nationwide, random forest machine learning is used to generate region-specific correction coefficients. Applying these coefficients results in minimal prediction errors, particularly for Abeliophyllum distichum, Robinia pseudoacacia, and Rhododendron schlippenbachii, with root mean square errors (RMSEs) of 1.2, 0.6, and 1.2 days, respectively. Model performance is evaluated using ten random sampling tests per species, selecting the model with the highest R². The models with applied correction coefficients achieve R² values ranging from 0.07 to 0.7, except for Sorbus commixta, and exhibit a final explanatory power of 0.75-0.9. This study provides valuable insights into seasonal changes in plant phenology, aiding in identifying honey harvesting seasons affected by abnormal weather conditions, such as those of Robinia pseudoacacia. Detailed information on flowering timing for various plant species and regions enhances understanding of the climate-plant phenology relationship.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.57 no.4
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• pp.441-448
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• 2012

This study was carried out to evaluate the productivity of rice cultivation in extremely late season in Korea and to confirm the effects of pot-raising seedling culture in this case by assessing the growth and yield performance of rice cultivars that are well adapted to late culture. Suitable cultivars for extremely late culture should not have premature heading habit when transplanted around late July and also secure appropriate growth duration before heading. Geumobyeo 1 and Manjongbyeo showed small decrease in the emerged leaves in transplanting in late July or early August and heading occurred at the same time relatively without premature heading. At transplanting from late July to early August in extremely late rice cultivation, ripening was relatively good until transplanting on August 5. At transplanting on July 30, accumulated temperature from heading to the first frost was $853^{\circ}C$ and ripening was good enough. However, heading was delayed by low temperature at transplanting on August 10 and ripening was very poor due to low accumulated temperature of below $800^{\circ}C$, causing drastic decrease of rice yield. The rice yield increased in transplanting with pot seedling, especially the effects of pot seedling was higher in Geumobyeo 1, but panicle number was not enough to secure rice yield owing to short growth duration. In order to cultivate rice in extremely late season, we should select adaptive rice cultivars that have suitable growth duration and excellent ripening in low temperature. Here, pot-seedling did a great role to secure early growth and bigger growth amounts.

• Weed & Turfgrass Science
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• v.6 no.4
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• pp.333-344
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• 2017

This study was conducted to examine the effect of cool-season grass overseeding on the green period, turf quality and density in zoysiagrass lawn. Treatments were perennial ryegrass (PR) overseeding ($60g\;m^{-2}$) on medium-leaf type zoysiagrass, Kentucky bluegrass (KB) overseeding ($20g\;m^{-2}$) on medium-leaf type zoysiagrass and narrow-leaf type zoysiagrass, and no overseeding on medium-leaf type zoysiagrass. Overseeding of KB or PR effectively provided quality improvement of zoysiagrass lawn by extending green-period about one month in spring and two months in fall season. PR overseeding showed quick green cover within 2-3 weeks but decreased the quality of overseeded zoysiagrass lawn during the summer season. Whereas, KB overseeding showed slow green cover taking two to three month after seeding but provided stable and good turf quality throughout the years. KB or PR overseeding significantly increased the turf density of zoysiagrass lawn except the period of summer depression of PR. The ground coverage of cool-season grasses ranged from 30 to 80% with considerable seasonal variation. As a result, KB and PR have their strengths and weaknesses as an overseeding material. Thus, the use of KB and PR as a mixture would provide better overseeding performance in zoysiagrass lawn.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.3
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• pp.334-342
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• 2015

The present study was designed to evaluate how environmental factors in a dry-summer subtropical climate in Terceira-Azores (situated in the North Atlantic Ocean: $38^{\circ}43^{\prime}N27^{\circ}12^{\prime}W$) can affect dairy cow (Holstein) fertility, as well as seasonal influence on in vitro oocytes maturation and embryos development. Impact of heat shock (HS) effects on in vitro oocyte's maturation and further embryo development after in vitro fertilization (IVF) was also evaluated. For such purpose the result of the first artificial insemination (AI) performed 60 to 90 days after calving of 6,300 cows were recorded for one year. In parallel, climatic data was obtained at different elevation points (n = 5) from 0 to 1,000 m and grazing points from 0 to 500 m, in Terceira island, and the temperature humidity index (THI) was calculated. For in vitro experiments, oocytes (n = 706) were collected weekly during all year, for meiotic maturation and IVF. Further, to evaluate HS effect, 891 oocytes were collected in the cold moths (December, January, February and March) and divided in three groups treated to HS for 24 h during in vitro maturation at: C (Control = $38.5^{\circ}C$), HS1 ($39.5^{\circ}C$) and HS2 ($40.5^{\circ}C$). Oocytes from each group were used for meiotic assessment and IVF. Cleavage, morula and blastocyst development were evaluated respectively on day 2, 6, and 9 after IVF. A negative correlation between cow's conception rate (CR) and THI in grazing points (-91.3%; p<0.001) was observed. Mean THI in warmer months (June, July, August and September) was $71.7{\pm}0.7$ and the CR ($40.2{\pm}1.5%$) while in cold months THI was $62.8{\pm}0.2$ and CR was $63.8{\pm}0.4%$. A similar impact was obtained with in vitro results in which nuclear maturation rate (NMR) ranged from 78.4% (${\pm}8.0$) to 44.3% (${\pm}8.1$), while embryos development ranged from 53.8% (${\pm}5.8$) to 36.3% (${\pm}3.3$) in cold and warmer months respectively. In vitro HS results showed a significant decline (p<0.05) on NMR of oocytes for every $1^{\circ}C$ rising temperature ($78.4{\pm}8.0$, $21.7{\pm}3.1$ and $8.9{\pm}2.2$, respectively for C, HS1, and HS2). Similar results were observed in cleavage rate and embryo development, showing a clear correlation (96.9 p<0.05) between NMR and embryo development with respect to temperatures. Results clearly demonstrated that, up to a THI of 70.6, a decrease in the CR occurs in first AI after calving; this impairment was confirmed with in vitro results.

• Journal of Bio-Environment Control
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• v.26 no.3
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• pp.181-187
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• 2017

The purpose of this study was to provide basic data for development of environmental design technology for greenhouses constructed in reclaimed lands. The climatic conditions around seven major reclaimed land areas with a plan to install advanced horticultural complexes in Korea were analyzed. The characteristics of natural ventilation and temperature rise through the thermal environment measurement of the greenhouse in Saemangeum were analyzed. The part to be applied to the environmental design of the greenhouses in reclaimed lands were reviewed. Results of comparing the ventilation rate of the greenhouse according to the presence or absence of plants showed the greenhouse with plants had the lower ventilation rate, but the smaller rise of indoor temperature due to the evapotranspiration of plants. In the greenhouse with plants, the number of air changes was in the range of 0.3 to 0.9 volumes/min and the average was 0.7 volumes/min. The rise of indoor temperature relative to outdoor temperature was in the range of 1 to $5^{\circ}C$ and the average $2.5^{\circ}C$. The natural ventilation performance of the experimental greenhouse constructed in the reclaimed land almost satisfied the recommended ventilation rate in summer and the rise of indoor temperature relative to outdoor temperature did not deviate considerably from the cultivation environment of plants. Therefore, it was determined that the greenhouse cultivation in Saemangeum reclaimed land is possible with only natural ventilation systems without cooling facilities. As the reclaimed land is located in the seaside, the wind is stronger than the inland area, and the fog is frequent. This strong wind speed increases the ventilation rate of greenhouses, which is considered to be a factor for reducing the cooling load. In addition, since the fog duration is remarkably longer than that of inland area, the seasonal cooling load is expected to decrease, which is considered to be advantageous in terms of the operation cost of cooling facilities.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.833-842
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• 2013

The quantile mapping is utilized to reproduce reliable GCM(Global Climate Model) data by correct systematic biases included in the original data set. This scheme, in general, projects the Cumulative Distribution Function (CDF) of the underlying data set into the target CDF assuming that parameters of target distribution function is stationary. Therefore, the application of stationary quantile mapping for nonstationary long-term time series data of future precipitation scenario computed by GCM can show biased projection. In this research the Nonstationary Quantile Mapping (NSQM) scheme was suggested for bias correction of nonstationary long-term time series data. The proposed scheme uses the statistical parameters with nonstationary long-term trends. The Gamma distribution was assumed for the object and target probability distribution. As the climate change scenario, the 20C3M(baseline scenario) and SRES A2 scenario (projection scenario) of CGCM3.1/T63 model from CCCma (Canadian Centre for Climate modeling and analysis) were utilized. The precipitation data were collected from 10 rain gauge stations in the Han-river basin. In order to consider seasonal characteristics, the study was performed separately for the flood (June~October) and nonflood (November~May) seasons. The periods for baseline and projection scenario were set as 1973~2000 and 2011~2100, respectively. This study evaluated the performance of NSQM by experimenting various ways of setting parameters of target distribution. The projection scenarios were shown for 3 different periods of FF scenario (Foreseeable Future Scenario, 2011~2040 yr), MF scenario (Mid-term Future Scenario, 2041~2070 yr), LF scenario (Long-term Future Scenario, 2071~2100 yr). The trend test for the annual precipitation projection using NSQM shows 330.1 mm (25.2%), 564.5 mm (43.1%), and 634.3 mm (48.5%) increase for FF, MF, and LF scenarios, respectively. The application of stationary scheme shows overestimated projection for FF scenario and underestimated projection for LF scenario. This problem could be improved by applying nonstationary quantile mapping.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.10
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• pp.1016-1023
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• 2006

The water content of dewatered cake produced from belt press dewatering equipment was about 75 wt% which was some high to handle it, so the equipment contained a limit at the economical and environmental aspect. The thermal dewatering equipment built as an alternative to overcome several problems was set up at the sludge treatment field and estimated some feasibility as comparison with the dewatering performance of belt press. First, dewatering properties of waterworks sludge was analyzed by monthly. The sludge of a water shortage season contained a high organic content which led to be difficult to dewater the cake, the other side the sludge of rainwater season was ease to dewater because of low organic content. According to the results to analysis the water content of dewatered cake produced from two equipments on the base of the seasonal dewatering properties, the water content of dewatered cake produced from thermal dewatering for sludge of water shortage season was $41.6{\sim}48.3$ wt% and $71{\sim}84$ wt% from belt press. In the case of rainwater season, the water content of dewatered cake produced from thermal dewatering was $34{\sim}37.7$ wt% and $57{\sim}70$ wt% from belt press. It was understood that thereduction of water content of cake by thermal dewatering was larger than belt press. The economical aspect for two equipments was evaluated on considering the reduction of cake treatment amount as the decrease of water content of cake. When putting the cost index of thermal dewatering into 100, belt press was 121. This meant that thermal dewater was more economical than belt press by about 20% in the side of construction and operation. In conclusion, thermal dewatering equipment was estimated by producing the low water content dewatered cake as well as being operated with low coat.

• Korean Journal of Ecology and Environment
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• v.37 no.3 s.108
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• pp.344-354
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• 2004

A pilot study was performed from September 2000 to April 2004 to examine the feasibility of the wetland-pond system for the agricultural reuse of reclaimed water. The wetland system was a subsurface flow type, with a hydraulic residence time of 3.5 days, and the subsequent pond was 8 $m^3$ in volume (2 m ${\times}$ 2 m ${\times}$ 2 m) and operated with intermittent-discharge and continuous flow types. The wetland system was effective in treating the sewage; median removal efficiencies of $BOD_5$ and TSS were above 70.0%, with mean effluent concentrations of 27.1 and 16.8 mg $L^{-1}$, respectively, for these constituents. However, they did often exceed the effluent water quality standards of 20 mg $L^{-1}$. Removal of T-N and T-P was relatively less effective and mean effluent concentrations were approximately 103.2 and 7.2 mg $L^{-1}$, respectively. The wetland system demonstrated high removal rate (92 ${\sim}$ 90%) of microorganisms, but effluent concentrations were in the range of 300 ${\sim}$ 16,000 MPN 100 $mL^{-1}$ which is still high for agricultural reuse. The subsequent pond system provided further treatment of the wetland effluent, and especially additional microorganisms removal in addition to wetland-pond system could reduce the mean concentration to 1,000 MPN 100 $mL^{-1}$ from about $10^5$ MPN 100 $mL^{-1}$ of wetland influent. Other parameters in the pond system showed seasonal variation, and the upper layer of the pond water column became remarkably clear immediately after ice melt. Overall, the wetland system was found to be adequate for treating sewage with stable removal efficiency, and the subsequent pond was effective for further polishing. This study concerned agricultural reuse of reclaimed water using natural systems. Considering stable performance and effective removal of bacterial indicators as well as other water quality parameters, low maintenance, and cost-effectiveness, wetland- pond system was thought to be an effective and feasible alternative for agricultural reuse of reclaimed water in rural area.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.543-557
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• 2021

Because aerosols have different spectral characteristics according to the size and composition of the particle and to the satellite sensors, a comparative analysis of aerosol products from various satellite sensors is required. In South Korea, however, a comprehensive study for the comparison of various official satellite AOD (Aerosol Optical Depth) products for a long period is not easily found. In this paper, we aimed to assess the performance of the AOD products from MODIS (Moderate Resolution Imaging Spectroradiometer), VIIRS (Visible Infrared Imaging Radiometer Suite), Himawari-8, and Sentinel-3 by referring to the AERONET (Aerosol Robotic Network) sun photometer observations for the period between January 2015 and December 2019. Seasonal and geographical characteristics of the accuracy of satellite AOD were also analyzed. The MODIS products, which were accumulated for a long time and optimized by the new MAIAC (Multiangle Implementation of Atmospheric Correction) algorithm, showed the best accuracy (CC=0.836) and were followed by the products from VIIRS and Himawari-8. On the other hand, Sentinel-3 AOD did not appear to have a good quality because it was recently launched and not sufficiently optimized yet, according to ESA (European Space Agency). The AOD of MODIS, VIIRS, and Himawari-8 did not show a significant difference in accuracy according to season and to urban vs. non-urban regions, but the mixed pixel problem was partly found in a few coastal regions. Because AOD is an essential component for atmospheric correction, the result of this study can be a reference to the future work for the atmospheric correction for the Korean CAS (Compact Advanced Satellite) series.