• Ecology and Resilient Infrastructure
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• v.7 no.4
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• pp.238-247
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• 2020

This study aims to examine the causes of the rapid expansion of riparian vegetation in river channels in recent years. Accordingly, the changes in the monthly rainfall were analyzed at 19 locations over the period of 1984 to 2018. Moreover, the changes in the water levels of the target river sections of Seom River, Cheongmi River, and Naeseong River were analyzed. The results showed that rainfall increased by 30% in April and decreased by up to 49% in the May-September period since 2012. Between 2012 and 2018, when rainfall decreased, the inundation time of the floodplains of the target rivers decreased considerably. The floodplains of Seom River and Cheongmi River were not inundated since 2012 and 2013, respectively. In the case of Naeseong River, the inundation time of the low-water channel drastically decreased since 2013, and there was no inundation in 2015. Consequently, riparian vegetation settled rapidly on the floodplain without any disturbance and continued to expand. The settling and expansion of riparian vegetation reduce the flood capacity of the river channel and can also lead to the loss of the water ecosystem due to terrestrialization.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1047-1056
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• 2022

Sea ice, frozen sea water, in the Artic is a primary indicator of global warming. Due to its importance to the climate system, shipping-route navigation, and fisheries, Arctic sea ice prediction has gained increased attention in various disciplines. Recent advances in artificial intelligence (AI), motivated by a desire to develop more autonomous and efficient future predictions, have led to the development of new sea ice prediction models as alternatives to conventional numerical and statistical prediction models. This study aims to evaluate the performance of the two-stream convolutional long-and short-term memory (TS-ConvLSTM) AI model, which is designed for learning both global and local characteristics of the Arctic sea ice changes, for the minimum September Arctic sea ice from 2001 to 2021, and to show the possibility for an operational prediction system. Although the TS-ConvLSTM model generally increased the prediction performance as training data increased, predictability for the marginal ice zone, 5-50% concentration, showed a negative trend due to increasing first-year sea ice and warming. Additionally, a comparison of sea ice extent predicted by the TS-ConvLSTM with the median Sea Ice Outlooks (SIOs) submitted to the Sea Ice Prediction Network has been carried out. Unlike the TS-ConvLSTM, the median SIOs did not show notable improvements as time passed (i.e., the amount of training data increased). Although the TS-ConvLSTM model has shown the potential for the operational sea ice prediction system, learning more spatio-temporal patterns in the difficult-to-predict natural environment for the robust prediction system should be considered in future work.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.17-27
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• 2021

Streamflow prediction is a very vital disaster mitigation approach for effective flood management and water resources planning. Lately, torrential rainfall caused by climate change has been reported to have increased globally, thereby causing enormous infrastructural loss, properties and lives. This study evaluates the contribution of rainfall to streamflow prediction in normal and peak rainfall scenarios, typical of the recent flood at Piney Resort in Vernon, Hickman County, Tennessee, United States. Daily streamflow, water level, and rainfall data for 20 years (2000-2019) from two USGS gage stations (03602500 upstream and 03599500 downstream) of the Piney River watershed were obtained, preprocesssed and fitted with Long short term memory (LSTM) model. Tensorflow and Keras machine learning frameworks were used with Python to predict streamflow values with a sequence size of 14 days, to determine whether the model could have predicted the flooding event in August 21, 2021. Model skill analysis showed that LSTM model with full data (water level, streamflow and rainfall) performed better than the Naive Model except some rainfall models, indicating that only rainfall is insufficient for streamflow prediction. The final LSTM model recorded optimal NSE and RMSE values of 0.68 and 13.84 m³/s and predicted peak flow with the lowest prediction error of 11.6%, indicating that the final model could have predicted the flood on August 24, 2021 given a peak rainfall scenario. Adequate knowledge of rainfall patterns will guide hydrologists and disaster prevention managers in designing efficient early warning systems and policies aimed at mitigating flood risks.

• Geophysics and Geophysical Exploration
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• v.26 no.1
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• pp.8-17
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• 2023

Various sources, such as wind, waves, ships, and gas leaks from the seafloor, forms bubbles in the ocean. Underwater bubbles cause signal scattering, considerably affecting acoustic measurements. This characteristic of bubbles is used to block underwater noise by attenuating the intensity of the propagated signal. Recently, researchers have been studying the large-scale release of methane gas as bubble plumes from the seabed. Understanding the physical properties and distribution of bubble plumes is crucial for studying the relation between leaked methane gas and climate change. Therefore, a water tank experiment was conducted to estimate the distribution of bubble plumes using seismic imaging techniques and acoustic signals obtained from artificially generated bubbles using a bubble generator. Reverse time migration was applied to image the bubble plumes while the acquired acoustic envelope signal was used to effectively estimate bubble distribution. Imaging results were compared with optical camera images to verify the estimated bubble distribution. The water tank experiment confirmed that the proposed system could successfully image the distribution of bubble plumes using reverse time migration and the envelope signal. The experiment showed that the scattering signal of artificial bubble plumes can be used for seismic imaging.

• Economic and Environmental Geology
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• v.56 no.4
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• pp.409-419
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• 2023

Acid mine drainage(AMD) treatment is classified as both passive and active treatment. During the treatment, about 5,000 tons of neutralization sludge is generated as a by-product per year in Korea. This study was conducted to evaluate the characteristics of sludge generated from physico·chemical treatment processes as an active treatment from 5 different sources (D, H, S, T, Y) and the possibility of the sludges being recycled. The sludges have a pH range of 5.86 ~ pH 7.89, and a water content range of 51% ~ 82%. Most of particle sizes were less than 25 ㎛. In analysis of inorganic elements, the concentration of Al, Fe, and Mn were between 1,189 mg/kg ~ 129,344 mg/kg, 106,132 mg/kg ~ 338,011 mg/kg, and 3,472 mg/kg ~ 11,743 mg/kg, respectively. The concentration of As and Zn in sludge-T, Cd in sludge-D, Ni in sludge-H, Zn in sludge-S, and Cd in sludge-Y exceeded the soil contamination standards of Korea. The results from 2 separate kinds of leaching test, the Korea Standard Leaching Test(KSLT) and Toxicity Characteristic Leaching Procedure(TCLP), showed that all the sludges met the Korea groundwater standards. From the XRD and SEM-EDS analysis, the peaks of calcite and quartz were found in the sludges. The sludge also had a high proportion of Fe and O, and the majority of the composition was amorphous iron hydroxide.

• Journal of Korean Society of Forest Science
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• v.111 no.1
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• pp.50-60
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• 2022

In this study, habitat suitability was analyzed for three major honey tree species, namely Kalopanax septemlobus, Tilia amurensis, and Styrax obassis, in the Baekdudaegan Mountains using MaxEnt models. The AUC values indicating the prediction accuracies of the models were 0.747, 0.790, and 0.755 for K. septemlobus, T. amurensis, and S. obassis, respectively. The most important variables for K. septemlobus and T. amurensis were elevation, mean annual temperature, and slope, whereas mean annual temperature, elevation, and mean annual precipitation were the most important predictors for S. obassis. For all three studied species, elevation and mean annual temperature were the most important topographic and climatic factors, respectively, indicating that such variables are crucial for explaining species distribution. Honey tree species are essential resources in forest beekeeping, a high value-added process for improving forest income, and this study identified sites with the potential for management of such species in the Baekdudaegan Mountains, where it may be possible to establish a honey forest. However, the accuracy of the models should be improved through comprehensive analysis with abiotic variables, such as soil properties and aridity, which affect the distribution of honey tree species, as well as biotic variables, such as interspecific competition.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.311-325
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• 2023

This study was conducted to analyze the habitat suitability of the major honey trees including Kalopanax septemlobus Koidz., Prunus spp., Tilia spp., and Styrax obassia Siebold & Zucc. indigenous to mountain Gariwang and Yumeong using the machine learning approach (i.e., MaxEnt model). The AUC values of the model predictions were mostly above 0.7, and the results of the response curves showed that the environmental drivers that had effects on the habitat suitability of the major honey trees were elevation, mean annual precipitation, and mean annual temperature. These results indicate that climatic drivers along the elevation gradient are the main environmental drivers in explaining the distribution patterns of the major honey trees. In addition, the results of the response curves of Prunus spp. and Styrax obassia Siebold & Zucc. differed slightly in terms of slope and mean annual solar radiation as the main environmental drivers. The results of this study will be valuable for the establishment of honey tree forests and management plans for the natural and artificial forests in South Korea, as well as for the mapping the distribution of honey trees. Further studies at different regional levels, reflecting biotic drivers, will be needed to expand the production of honey and pollen at different strata and to produce honey annually.

• Korean Journal of Ecology and Environment
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• v.57 no.2
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• pp.75-82
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• 2024

This study examined the spatial morphological patterns of forest habitats and the characteristics of roadkill occurrences in the forests of Mungyeong, Yecheon, Yeongju, Andong, and Bonghwa in Gyeongsangbukdo. It involved building a resistance map between habitats and analyzing connectivity based on the least-cost distance. The analysis of the distance between the forest habitat Cores derived from MSPA and roadkill points showed that roadkill occurrences were concentrated approximately 74.11 m away from the Cores, with most roadkills happening within 360m from the habitats. The connectivity analysis between core habitats larger than 1 km² revealed 141 core habitats and 242 least-cost paths between them. The corridor distance value was found to be highest in Mungyeong city, indicating an urgent need for strategies to enhance habitat connectivity there. This research is expected to serve as foundational data for developing strategies to enhance ecosystem connectivity and restore habitats, by analyzing ecosystem connectivity and roadkill issues due to habitat fragmentation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.196-206
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• 2012

Studies of seasonal changes in $C_3/C_4$ mixed communities are rare, particularly in Asian summer monsoon climate zones. In our present study, seasonal changes in the profile and coverage of $C_3$ and $C_4$ plants were investigated in 2009 in Haenam, Yeongdong and Cheorwon regions of South Korea (all at different latitudes). The aim was to estimate the impacts of temperature and sunshine duration on species composition and transition timing of the $C_3$ and $C_4$ plants. From our results, the number of $C_3$ plants was found to increase from early spring to mid-May, and then decrease again until September in the Haenam and Yeongdong regions, but continuously increase from early spring to September in the Cheorwon region under relatively low summer temperatures. On the other hand, the number of $C_4$ plants increased from June or July to September in all three regions. These seasonal changes in species number and ratio have a direct impact upon species diversity which is highest when there are no dominant species. The relative coverage and relative summed dominance ratio (SDR') of the $C_3$ plants decreased from spring to autumn, but increased for the $C_4$ plants during this time in an exponential fashion with increasing accumulated temperature and sunshine duration. The transition timing from $C_3$ to $C_4$ plants occurred when the sum of sunshine duration for the days with daily mean temperature above $5^{\circ}C$ was 1017 hrs for the SDR'.

• Korean Journal of Environment and Ecology
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• v.33 no.4
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• pp.378-401
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• 2019

This study generated a list of plants in eight sections from the Baekdansa ticket office (874m) to Cheonjedan (1,560m) divided in the interval of 100m above sea level to examine the species diversity patterns and distribution changes of the vascular plants at different altitudes in Taebaeksan National Park. Four site surveys found a total of 385 taxa: 89 families, 240 genera, 345 species, 5 subspecies, 34 varieties, and 1 form. A result of analyzing the change of species diversity along elevational gradients showed that it decreased with increasing elevation and then increased from a certain section. A result of analyzing habitat affinity types showed that the proportion of forest species increased with increasing elevation. On the other hand, the ruderal species appeared at a high rate in the artificial interference section. A result of comparing the proportion of woody and herb plants showed that the woody plants gradually increased with elevation and rapidly decreased in the artificial interference section. On the other hand, the herb plants showed the opposite trend. A result of analyzing the change of distribution of species according to altitude with the DCA technique showed that the vascular plants were divided into three groups according to the elevation in order on the I axis with the boundaries at 900m and 1,300m above sea level. The arrangement of each stand from right to left along the altitude on the I axis with a significant correlation with warmth index (WI) confirmed that the temperature change along the altitude could affect the distribution of vascular plants, composition, and diversity. Therefore, the continuous monitoring is necessary to confirm ecological and environmental characteristics of vegetation, distribution ranges, changes of habitat. We expect that the results of this study will be used as the basic data for establishing the measurement measures related to the preservation of biodiversity and climate change.