• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.2
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• pp.143-156
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• 2014

We reviewed investigation status on turbidity plume in the statement of marine environmental survey(2008 to 2012) associated with marine sand extraction projects. The survey statement from seven marine sand extraction sites (extraction area of Southern EEZ, extraction area of Western EEZ, relocation zone in the Western EEZ, sea area under jurisdiction of Taean-gun, sea area under jurisdiction of Ansan City, and two discrete sea areas under jurisdiction of Ongjin-gun) in the nearshore and offshore of Korea showed that in situ observations were carried out for the dispersion and transport of suspended sediments on two areas (One is a extraction area in the EEZs, the other is an area of coastal sites). However, sampling station and range have not been selected considering physical, geographical factors (tide, wave, stratification, water depth, etc.) and weather conditions (wind direction and velocity, fetch, duration, etc). Especially turbidity plumes originating from three sources, which include suspended sediments in overflow(or overspill) discharged from spillways and reject chutes of dredging vessel, and resuspended sediments from draghead at the seabed, may be transported to a far greater distance outside the boundary of the extraction site and have undesirable impacts on the marine environment and ecosystem. We address that behaviour of environmental pollutants such as suspended solids, nutrients, and metals should be extensively monitored and diagnosed during the dispersion and transport of the plume. Finally we suggest the necessity to supplement the current system of the sea area utilization consultation and establish the combined guidelines on marine sand extraction to collect basic data, to monitor cumulative effects, and to minimize environmental damages incurred by the aftermath of sand extraction.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.501-512
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• 2015

Landfast sea ice (LFI) in Terra Nova Bay, East Antarctica where the Jangbogo Antarctic Research Station is located, has significant influences on marine ecosystem and the sailing of an icebreaker. Therefore, it is essential to analyze the spatio-temporal variation of the LFI in Terra Nova Bay. In this study, we chose interferometric pairs with the temporal baseline from 1 to 9 days out of a total of 62 COSMO-SkyMed synthetic aperture radar (SAR) images over Terra Nova Bay obtained from December 2010 to January 2012, and then constructed the coherence image of each pair. The LFI showed coherence values higher than 0.3 even in the interferometric SAR (InSAR) pairs of up to 9-days of temporal baseline. This was because the LFI was fixed at coastline and thus showed low temporal phase decorrelation. Based on the characteristics of the coherence on LFI, We defined the areas of LFI that show spatially homogeneous coherence values higher than 0.5. Pack ice (PI) and open water showed low coherence values due to large temporal phase decorreation caused by current and wind. Distinguishing PI from open water in the coherence images was difficult due to their similarly low coherence values. PI was identified in SAR amplitude images by investigating cracks on the ice. The extents of the LFI and PI were estimated from the coherence and SAR amplitude images and their temporal variations were analyzed. The extent of the LFI increased from March to July (maximum extent of $170.7km^2$) and decreased from October. The extent of the PI increased from February to May and decreased from May to July when the LFI increases dramatically. The extent of the LFI and air temperature showed an inverse correlation with a time lag of about 2 months, i.e., the extent of the LFI decreases after 2 months of the increase in the air temperature. Meanwhile the correlation between wind speed and the extent of the LFI was very low. This represents that the extent of LFI in Terra Nova Bay are influenced more by the air temperature than wind speed.

• Korean Journal of Environment and Ecology
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• v.33 no.5
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• pp.497-505
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• 2019

Winter hibernation in wildlife is a unique physiological mechanism for survival. For Asiatic black bears (ABBs, Ursus thibetanus ussuricus), hibernation is a very important but dangerous time for the cubs to be born. This study surveyed ABBs living in Mt. Jiri To examine the relationship between the temperature during hibernation and the hibernation days. The survey found that the average start and end dates of hibernation was December 7 and April 20, respectively. The average day of hibernation for females who gave birth was $167.8{\pm}22.6$ days. The average temperature of 5 days before hibernation was $0.6{\pm}4.1^{\circ}C$, the average temperature during hibernation was $1.3{\pm}2.43^{\circ}C$, and the average temperature of five days before the end of hibernation was $12.6{\pm}3.1^{\circ}C$. The hibernation days of the females that did not give birth to cubs and the males were $120.4{\pm}25.7$ days and $113.6{\pm}25.8$ days, respectively. The average temperatures of 5 days before hibernation was $2.1{\pm}4.2^{\circ}C$ and $-1.8{\pm}3.9^{\circ}C$, respectively. The average temperature during hibernation was $-0.2{\pm}1.6^{\circ}C$ and $-0.4{\pm}2.4^{\circ}C$. The average temperatures of five days before the end of hibernation were $7.8{\pm}3.6^{\circ}C$ and $7.8{\pm}4.4^{\circ}C$. These results indicate that females giving birth to cubs have higher hibernation days and average temperatures than the females that do not give birth and the males, which is due to the process of raising cubs during hibernation. The hibernating days and mean temperature for the groups in each lifecycle did not show any difference between the groups. This study is meaningful in that it disclosed the characteristics of hibernating intrinsic behaviors of ABBs. It observed the specific hibernation period and temperature of ABBs bears inhabiting in Mt. Jiri and examined the difference by sex, female(giving birth) and life cycle group according to temperature. The results of this study can be used to prevent the conflict between ABBs and humans in winter and spring and establish the preservation management plan.

• 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 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.

• 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 Remote Sensing
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• v.38 no.5_3
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• pp.925-938
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• 2022

Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.

• Korean Journal of Environment and Ecology
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• v.35 no.6
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• pp.594-600
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• 2021

The purpose of this study is to observe the period of mating calls of cicadas in South Korea to identify the emergence period and geographic distribution for each cicada species. The study sites were 19 protection areas nationwide. The mating calls of cicadas were collected over the 12 months of 2019. A bioacoustics measuring device was installed to record the mating calls of cicadas in WAV, 44,100Hz format for 1 minute every hour. The temperature was recorded once or twice every hour using a micro-meteorological measuring device. Nine species of Korean cicadinae were studied. The start and end periods of mating calls were recorded for each cicada species for the subsequent analysis. The analysis results showed that nine cicada species appeared in the 19 protection areas. The chronological order of mating call periods for each species was as follows: Cryptotympana atrata (7/12 - 9/30), Meimuna opalifera (7/27 - 10/20), Hyalessa fuscata (7/25 - 10/9), Graptopsaltria nigrofuscata (7/28 - 9/5), Platypleura kaempferi (7/3 - 9/29), Suisha coreana (9/14 - 10/30), Leptosemia takanonis (6/26 - 8/2), Auritibicen intermedius (7/27 - 9/28), and Meimuna mongolica (8/8 - 9/11). The mating call period was between 35 (Meimuna mongolica) and 89 (Platypleura kaempferi) days, with the average being 62 days. The elevation above sea level for the habitats of each species was as follows: 5 - 386 m for Cryptotympana atrata, 7 - 759 m for Meimuna opalifera, 7 - 967 m for Hyalessa fuscata, 42 - 700m for Graptopsaltria nigrofuscata, 7 - 700 m for Platypleura kaempferi, 5 - 759 m for Suisha coreana, 7 - 759 m for Leptosemia takanonis, 397 - 967 m for Auritibicen intermedius, and 7 - 42 m for Meimuna mongolica. The average temperature of the habitats of each species was as follows: 23.9℃ for Cryptotympana atrata, 21.8℃ for Meimuna opalifera, 22℃ for Hyalessa fuscata, 23℃ for Graptopsaltria nigrofuscata, 22.9℃ for Platypleura kaempferi, 14.6℃ for Suisha coreana, 20.6℃ for Leptosemia takanonis, 19.3℃ for Auritibicen intermedius, and 24.4℃ for Meimuna mongolica. In terms of the habitat distribution of species, Meimuna opalifera, Hyalessa fuscata, and Platypleura kaempferi were distributed in more than 15 protection sites. Cryptotympana atrata was distributed in the lowlands in the southwest. Graptopsaltria nigrofuscata was distributed in the western area of the Korean Peninsula. Suisha coreana was distributed in areas excluding high mountain areas and parts of the southeast area. Leptosemia takanonis was distributed in areas near the mountains. Auritibicen intermedius was distributed locally in the high mountain areas. Meimuna mongolica was distributed locally in flat wetlands.

• Journal of Korea Water Resources Association
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• v.55 no.6
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• pp.447-459
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• 2022

This study estimated the grid-type precipitation quantile for the Korean Peninsula using PERSIANN-CCS-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System-Climate Data Record), a satellite based re-analysis precipitation data. The period considered is a total of 38 years from 1983 to 2020. The spatial resolution of the data is 0.04° and the temporal resolution is 3 hours. For the probability distribution, the Gumbel distribution which is generally used for frequency analysis was used, and the probability weighted moment method was applied to estimate parameters. The duration ranged from 3 hours to 144 hours, and the return period from 2 years to 500 years was considered. The results were compared and reviewed with the estimated precipitation quantile using precipitation data from the Automated Synoptic Observing System (ASOS) weather station. As a result, the parameter estimates of the Gumbel distribution from the PERSIANN-CCS-CDR showed a similar pattern to the results of the ASOS as the duration increased, and the estimates of precipitation quantiles showed a rather large difference when the duration was short. However, when the duration was 18 h or longer, the difference decreased to less than about 20%. In addition, the difference between results of the South and North Korea was examined, it was confirmed that the location parameters among parameters of the Gumbel distribution was markedly different. As the duration increased, the precipitation quantile in North Korea was relatively smaller than those in South Korea, and it was 84% of that of South Korea for a duration of 3 h, and 70-75% of that of South Korea for a duration of 144 h.

• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.543-551
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• 2023

Snow is an essential climate factor that affects the climate system and surface energy balance, and it also has a crucial role in water balance by providing solid water stored during the winter for spring runoff and groundwater recharge. In this study, statistical analysis of Local Data Assimilation and Prediction System (LDAPS), Modern.-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), and ERA5-Land snow depth data were used to evaluate the applicability in South Korea. The statistical analysis between the Automated Synoptic Observing System (ASOS) ground observation data provided by the Korea Meteorological Administration (KMA) and the reanalysis data showed that LDAPS and ERA5-Land were highly correlated with a correlation coefficient of more than 0.69, but LDAPS showed a large error with an RMSE of 0.79 m. In the case of MERRA-2, the correlation coefficient was lower at 0.17 because the constant value was estimated continuously for some periods, which did not adequately simulate the increase and decrease trend between data. The statistical analysis of LDAPS and ASOS showed high and low performance in the nearby Gangwon Province, where the average snowfall is relatively high, and in the southern region, where the average snowfall is low, respectively. Finally, the error variance between the four independent snow depth data used in this study was calculated through triple collocation (TC), and a merged snow depth data was produced through weighting factors. The reanalyzed data showed the highest error variance in the order of LDAPS, MERRA-2, and ERA5-Land, and LDAPS was given a lower weighting factor due to its higher error variance. In addition, the spatial distribution of ERA5-Land snow depth data showed less variability, so the TC-merged snow depth data showed a similar spatial distribution to MERRA-2, which has a low spatial resolution. Considering the correlation, error, and uncertainty of the data, the ERA5-Land data is suitable for snow-related analysis in South Korea. In addition, it is expected that LDAPS data, which is highly correlated with other data but tends to be overestimated, can be actively utilized for high-resolution representation of regional and climatic diversity if appropriate corrections are performed.