• Korean Journal of Ecology and Environment
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• v.51 no.1
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• pp.105-123
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• 2018

Currently, satellite images act as essential and important data in water resources, environment, and ecology as well as information of geographic information system. In this paper, we will investigate basic characteristics of satellite images, especially application examples in water resources. In recent years, researches on spatial and temporal characteristics of large-scale regions utilizing the advantages of satellite imagery have been actively conducted for fundamental hydrological components such as evapotranspiration, soil moisture and natural disasters such as drought, flood, and heavy snow. Furthermore, it is possible to analyze temporal and spatial characteristics such as vegetation characteristics, plant production, net primary production, turbidity of water bodies, chlorophyll concentration, and water quality by using various image information utilizing various sensor information of satellites. Korea is planning to launch a satellite for water resources and environment in the near future, so various researches are expected to be activated on this field.

• Journal of The Korean Society of Grassland and Forage Science
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• v.38 no.1
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• pp.53-60
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• 2018

Yield prediction model for mixed pasture was developed with a shortage that the relationship between dry matter yield (DMY) and days of summer depression (DSD) was not properly reflected in the model in the previous research. Therefore, this study was designed to eliminate the data of the regions with distinctly different climatic conditions and then investigate their relationships DMY and DSD using the data in each region separately of regions with distinct climatic characteristics and classify the data based on regions for further analysis based on the previous mixed pasture prediction model. The data set used in the research kept 582 data points from 11 regions and 41 mixed pasture types. The relationship between DMY and DSD in each region were analyzed through scatter plot, correlation analysis and multiple regression analysis in each region separately. In the statistical analysis, DMY was taken as the response variable and 5 climatic variables including DSD were taken as explanatory variables. The results of scatter plot showed that negative correlations between DMY and DSD were observed in 7 out of 9 regions. Therefore, it was confirmed that analyzing the relationship between DMY and DSD based on each region is necessary and 5 regions were selected (Hwaseong, Suwon, Daejeon, Siheung and Gwangju) since the data size in these regions is large enough to perform the further statistical analysis based on large sample approximation theory. Correlation analysis showed that negative correlations were found between DMY and DSD in 3 (Hwaseong, Suwon and Siheung) out of the 5 regions, meanwhile the negative relationship in Hwaseong was confirmed through multiple regression analysis. Therefore, it was concluded that the interpretability of the yield prediction model for mixed pasture could be improved based on constructing the models using the data from each region separately instead of using the pooled data from different regions.

• 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.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1773-1784
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• 2021

In order to minimize damage to oil spill accidents in the ocean, it is essential to collect a spilled area as soon as possible. Thus satellite-based remote sensing is a powerful source to detect oil spills in the ocean. With the recent rapid increase in the number of available satellites, it has become possible to generate a status report of marine oil spills soon after the accident. In this study, the oil spill area was calculated using various satellite images for the Symphony oil spill accident that occurred off the coast of Qingdao Port, China, on April 27, 2021. In particular, improving the accuracy of oil spill area determination was applied using high-resolution commercial satellite images with a spatial resolution of 2m. Sentinel-1, Sentinel-2, LANDSAT-8, GEO-KOMPSAT-2B (GOCI-II) and Skysat satellite images were collected from April 27 to May 13, but five images were available considering the weather conditions. The spilled oil had spread northeastward, bound for coastal region of China. This trend was confirmed in the Skysat image and also similar to the movement prediction of oil particles from the accident location. From this result, the look-alike patch observed in the north area from the Sentinel-1A (2021.05.01) image was discriminated as a false alarm. Through the survey period, the spilled oil area tends to increase linearly after the accident. This study showed that high-resolution optical satellites can be used to calculate more accurately the distribution area of spilled oil and contribute to establishing efficient response strategies for oil spill accidents.

• Korean Chemical Engineering Research
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• v.57 no.1
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• pp.90-104
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• 2019

In this study, CALPUFF modeling was performed, using a real surface and upper air meterological data to predict trustworthy modeling-results. Pollutant-releases from windscreen chambers of enclosed poultry farms, P1 and P2, and from a open poultry farm, P3, and their diffusing behavior were modeled by CALPUFF modeling with volume sources as well as by finally-adjusted CALPUFF modeling where a linear velocity of upward-exit gas averaged with the weight of each directional-emitting area was applied as a model-linear velocity ($u^M_y$) at a stack, with point sources. In addition, based upon the scenario of poultry farm-releasing odor and particulate matter (PM) removal efficiencies of 0, 20, 50 and 80% or their corresponding emission rates of 100, 80, 50 and 20%, respectively, CALPUFF modeling was performed and concentrations of odor and PM were predicted at the region as a discrete receptor where civil complaints had been frequently filed. The predicted concentrations of ammonia, hydrogen sulfide, $PM_{2.5}$ and $PM_{10}$ were compared with those required to meet according to the offensive odor control law or the atmospheric environmental law. Subsequently their required removal efficiencies at poultry farms of P1, P2 and P3 were estimated. As a result, a priori assumption that pollutant concentrations at their discrete receptors are reduced by the same fraction as pollutant concentrations at P1, P2 and P3 as volume source or point source, were controlled and reduced, was proven applicable in this study. In case of volume source-adopted CALPUFF modeling, its required removal efficiencies of P1 compared with those of point source-adopted CALPUFF modeling, were predicted similar each other. However, In case of volume source-adopted CALPUFF modeling, its required removal efficiencies of both ammonia and $PM_{10}$ at not only P2 but also P3 were predicted higher than those of point source-adopted CALPUFF modeling. Nonetheless, the volume source-adopted CALPUFF modeling was preferred as a safe approach to resolve civil complaints. Accordingly, the required degrees of pollution prevention against ammonia, hydrogen sulfide, $PM_{2.5}$ and $PM_{10}$ at P1 and P2, were estimated in a proper manner.

• Journal of Climate Change Research
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• v.2 no.4
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• pp.317-331
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• 2011

The CERES-Barley crop simulation model of DSSAT package was used to assess the impacts of climate change on potential yield of winter covered barley in Korea. 56 sites over the southern part of Korean peninsula were selected to compare the climate change impacts in various climatic conditions. The climatological normals (1971~2000) and the three future climatological normals (2011~2040, 2041~2070, and 2071~2100), based on A1B climate change scenarios of Korea, were used in this study, and the three future climatological normals were simulated under three environmental conditions, where only temperature change, only carbon dioxide change, and both of temperature and carbon dioxide change with future A1B climate change scenarios, respectively. Results: The CERES-Barley model was suitable for predicting climate change impacts on the potential yield of winter covered barley, because of the agreement between observed and simulated outcomes (e.g., the coefficient of determination of grain yield equals 0.84). (1) The only increased temperature effect with the climate change scenarios was mostly negative to the potential yield of winter covered barley and its magnitude ranges from -21% to +1% for the three future normals. (2) The effect of the only elevated carbon dioxide on the potential yield of winter covered barley was positive and its magnitude ranged from 12% to 43% for the three future normals. (3) For increased temperature and elevated carbon dioxide change cases, potential yields increased by 13%, 21%, 19% increase for the 2011~2040, 2041~2070, 2071~2100 normals, respectively.

• Journal of Climate Change Research
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• v.1 no.2
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• pp.121-131
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• 2010

This study was carried out to evaluate spatial variations in rice production areas by simulating rice growth and yield with CERES-Rice growth model under GCM $2{\times}CO_2$ climate change scenarios. A modified window version(v4.0) of CERES-Rice was used to simulate the growth and development of three varieties, representing early, medium, and late maturity classes. Simulated growth and yield data of the three cultivars under the climate for 1971 to 2000 was set as a reference. Compared with the current normal(1971 to 2000), heading period from transplanting to heading date decreased by 7~8 days for the climate in $2^{\circ}C$ increase over normal, and 16~18 days for the climate in UKMO with all maturity classes, while change of ripening period from heading to harvesting date was different with maturity classes. That is, physical maturity was shortened by 1~3 days for early maturity class and 14~18 days for late maturity class under different climate change scenarios. Rice yield was in general reduced by 4.5%, 8.2%, 9.9%, and 14.9% under the climate in $2^{\circ}C$, $3^{\circ}C$, $4^{\circ}C$, and about $5^{\circ}C$ increase, respectively. The yield reduction was due to increased high temperature-induced spikelet sterility and decreased growth period. The results show that predicted climate changes are expected to bring negative effects in rice production in Korea. So, it is required for introduction of new agricultural technologies to adapt to climate change, which are, for example, developing new cultivars, alternations of planting dates and management practices, and introducing irrigation systems, etc.

• Korean Journal of Environmental Agriculture
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• v.38 no.1
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• pp.54-60
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• 2019

BACKGROUND: Hydrogen fluoride is one of the 97 accident preparedness substances regulated by the Ministry of Environment (Republic of Korea) and chemical accidents should be managed centrally due to continual occurrence. Especially, hydrogen fluoride has a characteristic of rapid diffusion and very toxic when leaking into the environment. Therefore, it is important to predict the impact range quickly and to evaluate the residual contamination immediately to minimize the human and environmental damages. METHODS AND RESULTS: In order to estimate the accident impact range, the off-site consequence analysis (OCA) was performed to the worst and alternative scenarios. Also, in order to evaluate the residual contamination of hydrogen fluoride in crop, the samples in accident site were collected from 15-divided regions (East direction from accident sites based on the main wind direction), and the concentration was measured by fluoride ($F^-$) ion-selective electrode potentiometer (ISE). As a result of the OCA, the affected distance by the worst scenario was estimated to be >10 km from the accident site and the range by the alternative scenario was estimated to be about 1.9 km. The residual contamination of hydrogen fluoride was highest in the samples near the site of the accident (E-1, 276.82 mg/kg) and tended to decrease as it moved eastward. Meanwhile, the concentrations from SE and NE (4.96~28.98 mg/kg) tended to be lower than the samples near the accident site. As a result, the concentration of hydrogen fluoride was reduced to a low concentration within 2 km from the accident site (<5 mg/kg), and the actual damage range was estimated to be around 2.2 km. Therefore, it is suggested that the results are similar to those of alternative accident scenarios calculated by OCA (about 1.9 km). CONCLUSION: It is difficult to estimate the chemical accident-affecting range/region by the OCA evaluation, because it is not possible to input all physicochemical parameters. However simultaneous measurement of the residual contamination in the environment will be very helpful in determining the diffusion range of actual chemical accident.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.1
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• pp.11-36
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• 2021

The solar annual (Sa) and semiannual (Ssa) tides account for much of the non-uniform annual and seasonal variability observed in sea levels. These non-equilibrium tides depend on atmospheric variations, forced by changes in the Sun's distance and declination, as well as on hydrographic conditions. Here we employ tidal harmonic analyses to calculate Sa and Ssa harmonic constants for 21 Korean coastal tidal stations (TS), operated by the Korea Hydrographic and Oceanographic Agency. We used 19 year-long (1999 to 2017) 1 hr-interval sea level records from each site, and used two conventional harmonic analysis (HA) programs (Task2K and UTide). The stability of Sa harmonic constants was estimated with respect to starting date and record length of the data, and we examined the spatial distribution of the calculated Sa and Ssa harmonic constants. HA was performed on Incheon TS (ITS) records using 369-day subsets; the first start date was January 1, 1999, the subsequent data subset starting 24 hours later, and so on up until the final start date was December 27, 2017. Variations in the Sa constants produced by the two HA packages had similar magnitudes and start date sensitivity. Results from the two HA packages had a large difference in phase lag (about 78°) but relatively small amplitude (<1 cm) difference. The phase lag difference occurred in large part since Task2K excludes the perihelion astronomical variable. Sensitivity of the ITS Sa constants to data record length (i.e., 1, 2, 3, 5, 9, and 19 years) was also tested to determine the data length needed to yield stable Sa results. HA results revealed that 5 to 9 year sea level records could estimate Sa harmonic constants with relatively small error, while the best results are produced using 19 year-long records. As noted earlier, Sa amplitudes vary with regional hydrographic and atmospheric conditions. Sa amplitudes at the twenty one TS ranged from 15.0 to 18.6 cm, 10.7 to 17.5 cm, and 10.5 to 13.0 cm, along the west coast, south coast including Jejudo, and east coast including Ulleungdo, respectively. Except at Ulleungdo, it was found that the Ssa constituent contributes to produce asymmetric seasonal sea level variation and it delays (hastens) the highest (lowest) sea levels. Comparisons between monthly mean, air-pressure adjusted, and steric sea level variations revealed that year-to-year and asymmetric seasonal variations in sea levels were largely produced by steric sea level variation and inverted barometer effect.

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.526-535
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• 2021

Spatial sampling design plays an important role in GIS-based modeling studies because it increases modeling efficiency while reducing the cost of sampling. In the field of agricultural systems, research demand for high-resolution spatial databased modeling to predict and evaluate climate change impacts is growing rapidly. Accordingly, the need and importance of spatial sampling design are increasing. The purpose of this study was to design spatial sampling of paddy fields (11,386 grids with 1 km spatial resolution) in Korea for use in agricultural spatial modeling. A stratified random sampling design was developed and applied in 2030s, 2050s, and 2080s under two RCP scenarios of 4.5 and 8.5. Twenty-five weather and four soil characteristics were used as stratification variables. Stratification and sample allocation were optimized to ensure minimum sample size under given precision constraints for 16 target variables such as crop yield, greenhouse gas emission, and pest distribution. Precision and accuracy of the sampling were evaluated through sampling simulations based on coefficient of variation (CV) and relative bias, respectively. As a result, the paddy field could be optimized in the range of 5 to 21 strata and 46 to 69 samples. Evaluation results showed that target variables were within precision constraints (CV<0.05 except for crop yield) with low bias values (below 3%). These results can contribute to reducing sampling cost and computation time while having high predictive power. It is expected to be widely used as a representative sample grid in various agriculture spatial modeling studies.