• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.277-283
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• 2018

The crop growth model has been widely used for climate change impact assessment. Crop growth model require genetic coefficients for simulating growth and yield. In order to determine the genetic coefficients, regional growth monitoring data or yield trial data of crops has been used to calibrate crop growth model. The aim of this study is to verify that yield trial data of corn is appropriate to calibrate genetic coefficients of CERES-MAIZE. Field experiment sites were Suwon, Jinju, Daegu and Changwon. The distance from the weather station to the experimental field were from 1.3km to 27km. Genetic coefficients calibrated by yield trial data showed good performance in silking day. The genetic coefficients associated with silking are determined only by temperature. In CERES-MAIZE model, precipitation or irrigation does not have a significant effect on phenology related genetic coefficients. Although the effective distance of the temperature could vary depending on the terrain, reliable genetic coefficients were obtained in this study even when a weather observation site was within a maximum of 27 km. Therefore, it is possible to estimate the genetic coefficients by yield trial data in study area. However, the yield-related genetic coefficients did not show good results. These results were caused by simulating the water stress without accurate information on irrigation or rainfall. The yield trial reports have not had accurate information on irrigation timing and volume. In order to obtain significant precipitation data, the distance between experimental field and weather station should be closer to that of the temperature measurement. However, the experimental fields in this study was not close enough to the weather station. Therefore, When determining the genetic coefficients of regional corn yield trial data, it may be appropriate to calibrate only genetic coefficients related to phenology.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.525-536
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• 2014

In this study, a method to assess and monitor hydrological drought using remote sensing was investigated for use in regions with limited observation data, and was applied to the Upper Namhangang basin in South Korea, which was seriously affected by the 2008-2009 drought. Drought information may be obtained more easily from meteorological data based on water balance than hydrological data that are hard to estimate. Air temperature data at 2 m above ground level (AGL) were estimated using remotely sensed data, evapotranspiration was estimated from the air temperature, and the correlations between precipitation minus evapotranspiration (P-PET) and streamflow percentiles were examined. Land Surface Temperature data with $1{\times}1km$ spatial resolution as well as Atmospheric Profile data with $5{\times}5km$ spatial resolution from MODIS sensor on board Aqua satellite were used to estimate monthly maximum and minimum air temperature in South Korea. Evapotranspiration was estimated from the maximum and minimum air temperature using the Hargreaves method and the estimates were compared to existing data of the University of Montana based on Penman-Monteith method showing smaller coefficient of determination values but smaller error values. Precipitation was obtained from TRMM monthly rainfall data, and the correlations of 1-, 3-, 6-, and 12-month P-PET percentiles with streamflow percentiles were analyzed for the Upper Namhan-gang basin in South Korea. The 1-month P-PET percentile during JJA (r = 0.89, tau = 0.71) and SON (r = 0.63, tau = 0.47) in the Upper Namhan-gang basin are highly correlated with the streamflow percentile with 95% confidence level. Since the effect of precipitation in the basin is especially high, the correlation between evapotranspiration percentile and streamflow percentile is positive. These results indicate that remote sensing-based P-PET estimates can be used for the assessment and monitoring of hydrological drought. The high spatial resolution estimates can be used in the decision-making process to minimize the adverse impacts of hydrological drought and to establish differentiated measures coping with drought.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.3
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• pp.262-276
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• 2018

Models to predict Leaf Wetness Duration (LWD) were evaluated using the observed meteorological and dew data at the 11 citrus orchards in Jeju, South Korea from 2016 to 2017. The sensitivity and the prediction accuracy were evaluated with four models (i.e., Number of Hours of Relative Humidity (NHRH), Classification And Regression Tree/Stepwise Linear Discriminant (CART/SLD), Penman-Monteith (PM), Deep-learning Neural Network (DNN)). The sensitivity of models was evaluated with rainfall and seasonal changes. When the data in rainy days were excluded from the whole data set, the LWD models had smaller average error (Root Mean Square Error (RMSE) about 1.5hours). The seasonal error of the DNN model had the similar magnitude (RMSE about 3 hours) among all seasons excluding winter. The other models had the greatest error in summer (RMSE about 9.6 hours) and the lowest error in winter (RMSE about 3.3 hours). These models were also evaluated by the statistical error analysis method and the regression analysis method of mean squared deviation. The DNN model had the best performance by statistical error whereas the CART/SLD model had the worst prediction accuracy. The Mean Square Deviation (MSD) is a method of analyzing the linearity of a model with three components: squared bias (SB), nonunity slope (NU), and lack of correlation (LC). Better model performance was determined by lower SB and LC and higher NU. The results of MSD analysis indicated that the DNN model would provide the best performance and followed by the PM, the NHRH and the CART/SLD in order. This result suggested that the machine learning model would be useful to improve the accuracy of agricultural information using meteorological data.

• Journal of Environmental Science International
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• v.16 no.4
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• pp.523-532
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• 2007

This study utilized the 1/25,000 topographic map of the upper area from the Geum-ho watermark located at the middle of Geum-ho river from the National Geographic Information Institute. For the analysis, first, the influence of the size of critical area to the hydro topographic factors was examined changing grid size to $10m{\times}10m,\;30m{\times}30m\;and\;50m{\times}50m$, and the critical area for the formation of a river to $0.01km^2{\sim}0.50km^2$. It is known from the examination result of watershed morphology according to the grid size that the smaller grid size, the better resolution and accuracy. And it is found, from the analysis result of the degree of the river according to the minimum critical area for each grid size, that the grid size does not affect on the degree of the river, and the number of rivers with 2nd and higher degree does not show remarkable difference while there is big difference in the number of 1st degree rivers. From the results above, it is thought that the critical area of $0.15km^2{\sim}0.20km^2$ is appropriate for formation of a river being irrelevant to the grid size in extraction of hydro topographic parameters that are used in the runoff analysis model using topographic maps. Therefore, the GIUH model applied analysis results by use of the river level difference law proposed in this study for the explanation on the outflow response-changing characters according to the decision of a critical value of a minimum level difference river, showed that, since an ogival occurrence time and an ogival flow volume are very significant in a flood occurrence in case of not undertow facilities, the researcher could obtain a good result for the forecast of river outflow when considering a convenient application of the model and an easy acquisition of data, so it's judged that this model is proper as an algorism for the decision of a critical value of a river basin.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.11
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• pp.1615-1634
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• 2004

A review was undertaken to obtain information on the sustainability of pig free-range production systems including the management, performance and health of pigs in the system. Modern outdoor rearing systems requires simple portable and flexible housing with low cost fencing. Local pig breeds and outdoor-adapted breeds for certain environment are generally more suitable for free-range systems. Free-range farms should be located in a low rainfall area and paddocks should be relatively flat, with light topsoil overlying free-draining subsoil with the absence of sharp stones that can cause foot damage. Huts or shelters are crucial for protecting pigs from direct sun burn and heat stress, especially when shade from trees and other facilities is not available. Pigs commonly graze on strip pastures and are rotated between paddocks. The zones of thermal comfort for the sow and piglet differ markedly; between 12-22$^{\circ}C$ for the sow and 30-37$^{\circ}C$ for piglets. Offering wallows for free-range pigs meets their behavioural requirements, and also overcomes the effects of high ambient temperatures on feed intake. Pigs can increase their evaporative heat loss via an increase in the proportion of wet skin by using a wallow, or through water drips and spray. Mud from wallows can also coat the skin of pigs, preventing sunburn. Under grazing conditions, it is difficult to control the fibre intake of pigs although a high energy, low fibre diet can be used. In some countries outdoor sows are fitted with nose rings to prevent them from uprooting the grass. This reduces nutrient leaching of the land due to less rooting. In general, free-range pigs have a higher mortality compared to intensively housed pigs. Many factors can contribute to the death of the piglet including crushing, disease, heat stress and poor nutrition. With successful management, free-range pigs can have similar production to door pigs, although the growth rate of the litters is affected by season. Piglets grow quicker indoors during the cold season compared to outdoor systems. Pigs reared outdoors show calmer behaviour. Aggressive interactions during feeding are lower compared to indoor pigs while outdoor sows are more active than indoor sows. Outdoor pigs have a higher parasite burden, which increases the nutrient requirement for maintenance and reduces their feed utilization efficiency. Parasite infections in free-range pigs also risks the image of free-range pork as a clean and safe product. Diseases can be controlled to a certain degree by grazing management. Frequent rotation is required although most farmers are keeping their pigs for a longer period before rotating. The concept of using pasture species to minimise nematode infections in grazing pigs looks promising. Plants that can be grown locally and used as part of the normal feeding regime are most likely to be acceptable to farmers, particularly organic farmers. However, one of the key concerns from the public for free-range pig production system is the impact on the environment. In the past, the pigs were held in the same paddock at a high stocking rate, which resulted in damage to the vegetation, nutrient loading in the soil, nitrate leaching and gas emission. To avoid this, outdoor pigs should be integrated in the cropping pasture system, the stock should be mobile and stocking rate related to the amount of feed given to the animals.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.183-193
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• 2020

This study was conducted to evaluate the effect of environment factors on the growth of autumn season cultivation of Kimchi cabbage using the big data in terms of public open data(weather, soil information, and growth of crop, etc.). The growth data and the environment data such as temperature, daylength, and rainfall from 2010 to 2019 were collected. As a result of composing the correlation matrix, the height and leaf number showed high correlation in growing degree days(GDDs) and daylength, and the yield showed negative correlation in growing degree days and the concentration of clay. GDDs and daylength explained about 89% and 84% of variation in height, respectively. These two environmental factors also explained about 85% and 79% of variation in leaf numbers, respectively. In contrast, the coefficient of determination was low for yield when GDDs and concentration of clay was used. The outcome of regional statistical analysis indicated that relationship between yield and sum of sand and silt were high in Haenam and Jindo areas. Hierarchical cluster analysis, which was performed to verify the association of yield, GDDs, and concentration of clay, showed that Haenam and Jindo were clustered together. Although GDDs and yield vary by year and region, and there are regions with similar concentration of clays, observation data are grouped as the result. These suggests that GDDs and soil texture are expected to be related to yield. The cluster analysis results can be used for further data analysis and agricultural policy establishment.

• Korean Journal of Environmental Biology
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• v.31 no.4
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• pp.429-439
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• 2013

This study was conducted to identify the relationship between environmental factors and algal bloom, and provide information for efficient management based on the results of monitoring the environmental parameters and algal diversity in the Jundai reservoir from March 2011 to October 2013. Little change in the weather conditions was observed during the study period except for a slight decrease in rainfall. Concentration of TN and TP in the reservoir exceeded water quality standards for agriculture and significant correlation between algal growth and environmental factors was observed. Phytoplankton in Jundai reservoir included 6 classes, 40 genus, 62 species, and the phytoplankton abundance was in the range of $1.3{\times}10^4{\sim}2.8{\times}10^6$ cells $mL^{-1}$. The annual average of phytoplankton abundance and Chl-a gradually decreased as TN and TP concentrations decreased. Overall Anabaena sp., Oscillatoria sp., and Microcystis sp. were the dominant species in Jundai reservoir. As the water temperature increased, the dominant species were Anabaena sp., Microcystis sp. and Oscillatoria sp., in that order. Anabaena sp. was dominant from spring to early summer with increase in water temperature and pollutant concentrations, and high correlation with environmental factors was observed. Microcystis sp. was dominant depending on changes in the nutrient levels. In the case of Oscillatoria sp., there was no significant correlation between phytoplankton biomess and Chl-a. However, efficient management of water environment and practical control of algal bloom in small scale reservoir polluted by livestock and farm irrigation should be achieved by identification of the relationship between algal growth and environmental factors.

• Journal of Korea Water Resources Association
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• v.53 no.8
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• pp.627-636
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• 2020

Debris flow disasters primarily occur in mountainous terrains far from cities. As such, they have been underestimated to cause relatively less damage compared with other natural disasters. However, owing to urbanization, several residential areas and major facilities have been built in mountainous regions, and the frequency of debris flow disasters is steadily increasing owing to the increase in rainfall with environmental and climate changes. Thus, the risk of debris flow is on the rise. However, only a few studies have explored the characteristics of flooding and reduction measures for debris flow in areas designated as steep slopes. In this regard, it is necessary to conduct research on securing independent disaster prevention technology, suitable for the environment in South Korea and reflective of the topographical characteristics thereof, and update and improve disaster prevention information. Accordingly, this study aimed to calculate the amount of debris flow, depending on disaster prevention performance targets for regions designated as steep slopes in South Korea, and develop an independent model to not only evaluate the impact of debris flow but also identify debris barriers that are optimal for mitigating damage. To validate the reliability of the two-dimensional debris flow model developed for the evaluation of debris barriers, the model's performance was compared with that of the hydraulic model. Furthermore, a 2-D debris model was constructed in consideration of the regional characteristics around the steep slopes to analyze the flow characteristics of the debris that directly reaches the damaged area. The flow characteristics of the debris delivered downstream were further analyzed, depending on the specifications (height) and installation locations of the debris barriers employed to reduce the damage. The experimental results showed that the reliability of the developed model is satisfactory; further, this study confirmed significant performance degradation of debris barriers in areas where the barriers were installed at a slope of 20° or more, which is the slope at which debris flows occur.

• Korean Journal of Environmental Biology
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• v.39 no.1
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• pp.100-107
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• 2021

Along with an increase in the frequency of high-concentration fine particulate matter in Korea, interest and research on ammonia (NH₃) are actively increasing. It is obvious that agriculture has contributed significantly to NH₃ emissions. However, studies on the long-term effect of fertilizer use on the ambient NH₃ concentration of agricultural land are insufficient. Therefore, in this study, NH₃ concentration in the atmosphere of agricultural land was monitored for 11 months using a passive sampler. The average ambient NH₃ concentration during the total study period was 2.02 ㎍ m^-3 and it was found that the effect of fertilizer application on the ambient NH₃ concentration was greatest in the month immediately following fertilizer application (highest ambient NH₃ concentration as 11.36㎍ m^-3). After that, it was expected that the NH₃ volatilization was promoted by increases in summer temperature and the concentration in the atmosphere was expected to increase. However, high NH₃ concentrations in the atmosphere were not observed due to strong rainfall that lasted for a long period. After that, the ambient NH₃ concentration gradually decreased through autumn and winter. In summary, when studying the contribution of fertilizer to the rate of domestic NH₃ emissions, it is necessary to look intensively for at least one month immediately after fertilizer application, and weather information such as precipitation and no-rain days should be considered in the field study.

• Korean Journal of Remote Sensing
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• v.38 no.2
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• pp.179-188
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• 2022

Global warming causes climate change and increases extreme weather events worldwide, and the occurrence of heatwaves and droughts is also increasing in Korea. For the monitoring of extreme weather, various satellite data such as LST (Land Surface Temperature), TCI (Temperature Condition Index), NDVI (Normalized Difference Vegetation Index), VCI (Vegetation Condition Index), and VHI (Vegetation Health Index) have been used. VHI, the combination of TCI and VCI, represents the vegetation stress affected by meteorological factors like precipitation and temperature and is frequently used to assess droughts under climate change. TCI and VCI require historical reference values for the LST and NDVI for each date and location. So, it is complicated to produce the VHI from the recent satellite GK2A (Geostationary Korea Multi-Purpose Satellite-2A). This study examined the retrieval of VHI using GK2A AMI (Advanced Meteorological Imager) by referencing the historical data from VIIRS (Visible Infrared Imaging Radiometer Suite) NDVI and LST as a proxy data. We found a close relationship between GK2A and VIIRS data needed for the retrieval of VHI. We produced the TCI, VCI, and VHI for GK2A during 2020-2021 at intervals of 8 days and carried out the interpretations of recent extreme weather events in Korea. GK2A VHI could express the changes in vegetation stress in 2020 due to various extreme weather events such as heatwaves (in March and June) and low temperatures (in April and July), and heavy rainfall (in August), while NOAA (National Oceanic and Atmospheric Administration) VHI could not well represent such characteristics. The GK2A VHI presented in this study can be utilized to monitor the vegetation stress due to heatwaves and droughts if the historical reference values of LST and NDVI can be adjusted in a more statistically significant way in the future work.