• Korean Journal of Ecology and Environment
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• v.48 no.3
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• pp.176-187
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• 2015

In this study, we hypothesized that the size of wintering crane population would change due to the climate factors. We assumed that wintering population size would differ by climate values in January, which is the coldest period in year. Especially, White-naped cranes were able to choose wintering site between Cheorwon and other alternative place where snow coverage had low influence, differing from Red crowned cranes. For this reason, we predicted the population size of White-naped cranes would fluctuate according to the extent of snow coverage in Cheorwon. Therefore we used snow coverage data based on MODIS and climate data from KMA (Korea Meteorological Administration) that are generally used. We analyzed the crane's population size in Cheorwon in January from 2002 to 2014. The temperature in the Cheorwon increased from 2002 to wintering period in 2007~ 2008 and went down, showing the lowest temperature in 2011~ 2012. With this phenomenon, warmth index showed the similar pattern with temperature. Amount of newly accumulated snow (the amount of snow that fallen from 0:01 am to 11:29 pm in a day) was low after 2002, but rapidly increased in 2010~ 2011 and 2011~ 2012. The area of snow coverage rapidly declined from 2002 to 2005~ 2006 but suddenly expanded in wintering period in 2009~ 2010 and 2010~ 2011. Wintering population size of the White-naped cranes decreased as snow coverage area increased in January and the highest correlation was found between them, compared to the other climatic factors. However, the number of individuals of Red crowned cranes had little relationship with general climate factors including snow cover range. Therefore it seems that population size of the Red crowned crane varied by factors related with habitat selection such as secure roosting site and area of foraging place, not by climatic factors. In multiple regression analysis, wintering population of White-naped cranes showed significant relationship with logarithmic value of snow cover range and its period. Therefore, it suggests that the population size of the White-naped crane was affected by snow cover range n wintering period and this was because it was hard for them to find out rice grains which are their main food items, buried in snow cover. The population size variation in White-naped cranes was caused by some individuals which left Cheorwon for Izumi where snow cover had little influence on them. The wintering population in Izumi and Cheorwon had negative correlation, implying they were mutually related.

• 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.

• Journal of Korea Water Resources Association
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• v.54 no.6
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• pp.419-431
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• 2021

In Seoul, it has been confirmed that the duration of rainfall is shortened and the frequency and intensity of heavy rains are increasing with a changing climate. In addition, due to high population density and urbanization in most areas, floods frequently occur in flood-prone areas for the increase in impermeable areas. Furthermore, the Seoul City is pursuing various projects such as structural and non-structural measures to resolve flood-prone areas. A disaster prevention performance target was set in consideration of the climate change impact of future precipitation, and this study conducted to reduce the overall flood damage in Seoul for the long-term. In this study, 29 GCMs with RCP4.5 and RCP8.5 scenarios were used for spatial and temporal disaggregation, and we also considered for 3 research periods, which is short-term (2006-2040, P1), mid-term (2041-2070, P2), and long-term (2071-2100, P3), respectively. For spatial downscaling, daily data of GCM was processed through Quantile Mapping based on the rainfall of the Seoul station managed by the Korea Meteorological Administration and for temporal downscaling, daily data were downscaled to hourly data through k-nearest neighbor resampling and nonparametric temporal detailing techniques using genetic algorithms. Through temporal downscaling, 100 detailed scenarios were calculated for each GCM scenario, and the IDF curve was calculated based on a total of 2,900 detailed scenarios, and by averaging this, the change in the future extreme rainfall was calculated. As a result, it was confirmed that the probability of rainfall for a duration of 100 years and a duration of 1 hour increased by 8 to 16% in the RCP4.5 scenario, and increased by 7 to 26% in the RCP8.5 scenario. Based on the results of this study, the amount of rainfall designed to prepare for future climate change in Seoul was estimated and if can be used to establish purpose-wise water related disaster prevention policies.

• 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.

• Journal of the Korean earth science society
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• v.43 no.5
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• pp.604-617
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• 2022

Sea surface temperature (SST) is a key variable that can be used to understand ocean-atmosphere phenomena and predict climate change. Satellite microwave remote sensing enables the measurement of SST despite the presence of clouds and precipitation in the sensor path. Therefore, considering the high utilization of microwave SST, it is necessary to continuously verify its accuracy and analyze its error characteristics. In this study, the validation of the microwave global precision measurement (GPM)/GPM microwave imager (GMI) SST around the Northwest Pacific and Korean Peninsula was conducted using surface drifter temperature data for approximately eight years from March 2014 to December 2021. The GMI SST showed a bias of 0.09K and an average root mean square error of 0.97K compared to the actual SST, which was slightly higher than that observed in previous studies. In addition, the error characteristics of the GMI SST were related to environmental factors, such as latitude, distance from the coast, sea wind, and water vapor volume. Errors tended to increase in areas close to coastal areas within 300 km of land and in high-latitude areas. In addition, relatively high errors were found in the range of weak wind speeds (<6 m s^-1) during the day and strong wind speeds (>10 m s^-1) at night. Atmospheric water vapor contributed to high SST differences in very low ranges of <30 mm and in very high ranges of >60 mm. These errors are consistent with those observed in previous studies, in which GMI data were less accurate at low SST and were estimated to be due to differences in land and ocean radiation, wind-induced changes in sea surface roughness, and absorption of water vapor into the microwave atmosphere. These results suggest that the characteristics of the GMI SST differences should be clarified for more extensive use of microwave satellite SST calculations in the seas around the Korean Peninsula, including a part of the Northwest Pacific.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.121-135
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• 2010

This study is to assess the effect of potential future climate change on the inflow of agricultural reservoir and its impact to downstream streamflow by reservoir operation for paddy irrigation water supply using the SLURP. Before the future analysis, the SLURP model was calibrated using the 6 years daily streamflow records (1998-200398 and validated using 3 years streamflow data (2004-200698 for a 366.5 $km^2$ watershed including two agricultural reservoirs (Geumgwang8 and Gosam98located in Anseongcheon watershed. The calibration and validation results showed that the model was able to simulate the daily streamflow well considering the reservoir operation for paddy irrigation and flood discharge, with a coefficient of determination and Nash-Sutcliffe efficiency ranging from s 7 to s 9 and 0.5 to s 8 respectively. Then, the future potential climate change impact was assessed using the future wthe fu data was downscaled by nge impFactor method throuih bias-correction, the future land uses wtre predicted by modified CA-Markov technique, and the future ve potentiacovfu information was predicted and considered by the linear regression bpowten mecthly NDVI from NOAA AVHRR ima ps and mecthly mean temperature. The future (2020s, 2050s and 2e 0s) reservoir inflow, the temporal changes of reservoir storaimpand its impact to downstream streamflow watershed wtre analyzed for the A2 and B2 climate change scenarios based on a base year (2005). At an annual temporal scale, the reservoir inflow and storaimpchange oue, anagricultural reservoir wtre projected to big decrease innautumnnunder all possiblmpcombinations of conditions. The future streamflow, soossmoosture and grounwater recharge decreased slightly, whtre as the evapotransporation was projected to increase largely for all possiblmpcombinations of the conditions. At last, this study was analysed contribution of weather, vegetation and land use change to assess which factor biggest impact on agricultural reservoir and stream watershed. As a result, weather change biggest impact on agricultural reservoir inflow, storage, streamflow, evapotranspiration, soil moisture and groundwater recharge.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1591-1604
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• 2023

In ocean color remote sensing, atmospheric correction is a vital process for ensuring the accuracy and reliability of ocean color products. Furthermore, in recent years, the remote sensing community has intensified its requirements for understanding errors in satellite data. Accordingly, research is currently addressing errors in remote sensing reflectance (R_rs) resulting from inaccuracies in meteorological variables (total ozone, pressure, wind field, and total precipitable water) used as auxiliary data for atmospheric correction. However, there has been no investigation into the error in R_rs caused by the variability of the water vapor profile, despite it being a recognized error source. In this study, we used the Second Simulation of a Satellite Signal Vector version 2.1 simulation to compute errors in water vapor transmittance arising from variations in the water vapor profile within the GOCI-II observation area. Subsequently, we conducted an analysis of the associated errors in ocean color products. The observed water vapor profile not only exhibited a complex shape but also showed significant variations near the surface, leading to differences of up to 0.007 compared to the US standard 62 water vapor profile used in the GOCI-II atmospheric correction. The resulting variation in water vapor transmittance led to a difference in aerosol reflectance estimation, consequently introducing errors in R_rs across all GOCI-II bands. However, the error of R_rs in the 412-555 nm due to the difference in the water vapor profile band was found to be below 2%, which is lower than the required accuracy. Also, similar errors were shown in other ocean color products such as chlorophyll-a concentration, colored dissolved organic matter, and total suspended matter concentration. The results of this study indicate that the variability in water vapor profiles has minimal impact on the accuracy of atmospheric correction and ocean color products. Therefore, improving the accuracy of the input data related to the water vapor column concentration is even more critical for enhancing the accuracy of ocean color products in terms of water vapor absorption correction.

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.6
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• pp.52-61
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• 2013

This study was conducted to investigate the effects of pergola's shading on the thermal comfort index in the summer. The 3 type of pergolas($4m{\times}4m{\times}h2.7m$) which were screened overhead(I)/overhead west(II)/overhead west north(III) plane with reed blind for summer shading and winter wind break, were constructed on the 4th floor rooftop. Thereafter the meteorological variables(air temperature, humidity, radiation, and wind speed) of pergola I, III and rooftop were measured from 14 to 16 August 2013(1st experiment), those of pergola I, II and rooftop were measured from 26 to 28 August 2013(2nd experiment). The effects of pergola's shading on the radiation environment and mean radiant temperature($T_{mrt}$), standard effective temperature($SET^*$) were as follows. The maximum 1 h mean values of differences ${\Delta}$ of the sums of shortwave radiant flux densities absorbed by the human body (${\Delta}K_{abs,max}$) between pergola I, III and nearby sunny rooftop were $-119W/m^2$, $-158W/m^2$, those between pergola I, II and rooftop were $-145W/m^2$, $-159W/m^2$. The maximum 1 h mean values of differences ${\Delta}$ of the sums of long wave radiant flux densities absorbed by the human body (${\Delta}L_{abs,max}$) between pergola I, III and nearby sunny rooftop, were $-15W/m^2$, $-17W/m^2$, those between pergola I, II and nearby rooftop, were $-8W/m^2$, $-7W/m^2$. The response of the direction dependent long wave radiant flux densities $L_1$ on the pergola's shading turned out to be distinctly weaker as compared to shortwave radiant flux densities $K_1$. The pergola's shading leads to a lowering of $T_{mrt}$ and $SET^*$. The peak values of $T_{mrt}$ absorbed by the human body were decreased $16^{\circ}C$ and $21.4^{\circ}C$ under pergola I and III as compared to that of nearby rooftop in the 1st experiment. Those were decreased $18.8^{\circ}C$ and $20.8^{\circ}C$ under pergola I and II as compared to that of nearby rooftop in the 2nd experiment. The peak values of $SET^*$ absorbed by the human body were decreased $2.9^{\circ}C$ and $2.6^{\circ}C$ under pergola I and III as compared to that of nearby rooftop in the 1st experiment. Those were decreased $3.5^{\circ}C$ and $2.6^{\circ}C$ under pergola I and II as compared to that of nearby rooftop in the 2nd experiment. The relative $SET^*$ decrease in pergola II, III compared to nearby sunny rooftop $SET^*$ were lower than that in pergola I, revealing the influence of the wind speed. Therefore it is essential to design pergola to maximize wind speed and minimize solar radiation to achieve comfort in the hot summer. The $SET^*$ under pergola I, III were exceeded $28.7^{\circ}C$ and $30.4^{\circ}C$ which were the upper limit of thermal comfort and tolerable zone during all most daytimes in the 1st experiment(maximum air temperature $37.5^{\circ}C$). The $SET^*$ under pergola I was exceeded $28.7^{\circ}C$ which was the upper limit of thermal comfort zone at 13h, that under pergola II was exceeded $28.7^{\circ}C$ from 8h to 14h, meanwhile the $SET^*$ under pergola I, II were within thermal tolerable zone during most daytimes in the 2nd experiment(maximum air temperature $34.4^{\circ}C$). Therefore to ensure the thermal comfort of pergola for summer hottest days, pergola should be shaded with not only reed blind but also climbing and shade plants. $T_{mrt}$ and $SET^*$ were suitable index for the evaluation of pergola's shading effects and outdoors.