The objective of this study is to derive the core habitat of the Kirengeshoma koreana Nakai utilizing Habitat Suitability Index (HSI) and Maximum Entropy (MaxEnt) models. Expert-based models have been criticized for their subjective criteria, while statistical models face difficulties in on-site validation and integration of expert opinions. To address these limitations, both models were employed, and their outcomes were overlaid to derive the core habitat. Five variables were identified through a comprehensive literature review and spatial analysis based on appearance coordinates. The environmental variables encompass vegetation zone, forest type, crown density, annual precipitation, and effective soil depth. Through surveys involving six experts, importance rankings and SI (Suitability Index) scores were established for each variable, subsequently facilitating the creation of an HSI map. Using the same variables, the MaxEnt model was also executed, resulting in a corresponding map, which was merged to construct the definitive core habitat map. Out of 16 observed locations of K. koreana, 15 were situated within the identified core habitat. Furthermore, an area historically known to host K. koreana but not verified in the present, Mt. Yeongchwi, was found to lack a core habitat. These findings suggest that the developed models exhibit a high degree of accuracy and effectively reflect the current ecological landscape.
Korea prepares for potential floods by designating June 21st to September 20th as the flood season. However, many dams in Korea have suffered from extreme floods caused by different climate patterns, as in the case of the longest consecutive rain of 54 days in the 2020's flood season. In this context, various studies have tried to develop novel methodologies to reduce flood damage, but no study has ever dealt with the validity of the current statutory flood season thus far. This study first checked the validity of the current flood season through the observation data in the 21st century and proved that the current flood season does not consider the effects of increasing precipitation trends and the changing regional rainfall characteristics. In order to deal with these limitations, this study suggested seven new alternative flood seasons in the research area. The rigid reservoir operation method (ROM) was used for reservoir simulation, and the long short-term memory (LSTM) model was used to derive predicted inflow. Finally, all alternatives were evaluated based on whether if they exceeded the design discharge of the dam and the design flood of the river. As a result, the floods in the shifted period were reduced by 0.068% and 0.33% in terms of frequency and duration, and the magnitude also decreased by 24.6%, respectively. During this period, the second evaluation method also demonstrated that flood decreased from four to two occurrences. As the result of this study, the authors expect a formal reassessment of the flood season to take place, which will ultimately lead to the preemptive flood response to changing precipitation patterns.
Hyeon-Seok Lee;Seo-Yeong Yang;Jae-kyeong Baek;Yeong-Seo Song;Ju-Hee Kim;So-Hye Cho;Ji-Young Shon;Jae-Ki Chnag;Junhwan Kim
KOREAN JOURNAL OF CROP SCIENCE
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v.69
no.2
/
pp.71-77
/
2024
After the strongest El Niño since 2015 occurred in 2023, there has been a growing interest in understanding its impacts on rice yield in South Korea. We investigated the impact of El Niño during the rice-growing season on rice yield by analyzing the correlation between detrended rice yield data and ONI (Oceanic Niño Index) values exceeding 0.5. The results show a positive correlation between ONI intensities and detrended rice yields. Furthermore, we found that variations in sunshine duration, precipitation, and typhoon activity affect detrended yield values positively and negatively. This pattern was similar to the classification of El Niño into Cold Tongue El Niño and non-Cold Tongue El Niño, which showed positive and negative detrended rice yield values, respectively. This observation suggests that predicting yield based on ONI intensity during Cold Tongue El Niño years may be feasible to some extent.
Lee, Dae Wung;Jung, Jaewon;Hong, Seung Jin;Han, Daegun;Joo, Hong Jun;Kim, Hung Soo
Journal of Wetlands Research
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v.19
no.3
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pp.345-352
/
2017
The average global temperature on Earth has increased by about $0.85^{\circ}C$ since 1880 due to the global warming. The temperature increase affects hydrologic phenomenon and so the world has been suffered from natural disasters such as floods and droughts. Therefore, especially, in the aspect of water deficit, we may require the accurate prediction of water demand considering the uncertainty of climate in order to establish water resources planning and to ensure safe water supply for the future. To do this, the study evaluated future water balance and water deficit under the climate change for Anseong river basin in Korea. The future rainfall was simulated using RCP 8.5 climate change scenario and the runoff was estimated through the SLURP model which is a semi-distributed rainfall-runoff model for the basin. Scenario and network for the water balance analysis in sub-basins of Anseong river basin were established through K-WEAP model. And the water demand for the future was estimated by the linear regression equation using amounts of water uses(domestic water use, industrial water use, and agricultural water use) calculated by historical data (1965 to 2011). As the result of water balance analysis, we confirmed that the domestic and industrial water uses will be increased in the future because of population growth, rapid urbanization, and climate change due to global warming. However, the agricultural water use will be gradually decreased. Totally, we had shown that the water deficit problem will be critical in the future in Anseong river basin. Therefore, as the case study, we suggested two alternatives of pumping station construction and restriction of water use for solving the water deficit problem in the basin.
Seasons in Korea have very distinguishable features. Due to continental high pressure, spring in Korea is dry and has low precipitation. Due to climate change derived from the increase of greenhouse gases, climate variability had increased and it became harder to predict. This caused the spring drought harsher than usual. Since 1990s, numbers of chronic drought from winter to spring increased in southern regions of Korea. Such drought in the spring damages the growth and development of the crops sown in the spring and decreases its quantity. For stable agricultural production in the future, it is necessary to assess vulnerability of the relationship between spring drought and agricultural production as well as to establish appropriate measures accordingly. This research used CCGIS program to perform vulnerability assessment on spring drought based on climate change scenario SRES A1B, A1FI, A1T, A2, B1, B2 and RCP 8.5 in 232 regions in Korea. As a result, Every scenario showed that vulnerability of spring drought decreased from 2000s to 2050s. Ratio of decrease was 37% under SRES scenario but, 3% under RCP 8.5 scenario. Also, for 2050 prediction, every scenario predicted the highest vulnerability in Chungcheongnam-do. However, RCP-8.5 predicted higher vulnerability in Gyeonggi-do than SRES scenario. The reason for overall decrease in vulnerability of agriculture for future spring drought is because the increase of precipitation was predicted. The assessment of vulnerability by different regions showed that choosing suitable scenario is very important factor.
Kim, Ji Yung;Choi, Jae Seong;Jo, Hyun Wook;Kim, Moon Ju;Kim, Byong Wan;Sung, Kyung Il
Journal of The Korean Society of Grassland and Forage Science
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v.42
no.2
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pp.127-136
/
2022
This study was conducted to estimate the damage of Whole Crop Maize (WCM) according to abnormal climate using machine learning and present the damage through mapping. The collected WCM data was 3,232. The climate data was collected from the Korea Meteorological Administration's meteorological data open portal. Deep Crossing is used for the machine learning model. The damage was calculated using climate data from the Automated Synoptic Observing System (95 sites) by machine learning. The damage was calculated by difference between the Dry matter yield (DMY)normal and DMYabnormal. The normal climate was set as the 40-year of climate data according to the year of WCM data (1978~2017). The level of abnormal climate was set as a multiple of the standard deviation applying the World Meteorological Organization(WMO) standard. The DMYnormal was ranged from 13,845~19,347 kg/ha. The damage of WCM was differed according to region and level of abnormal climate and ranged from -305 to 310, -54 to 89, and -610 to 813 kg/ha bnormal temperature, precipitation, and wind speed, respectively. The maximum damage was 310 kg/ha when the abnormal temperature was +2 level (+1.42 ℃), 89 kg/ha when the abnormal precipitation was -2 level (-0.12 mm) and 813 kg/ha when the abnormal wind speed was -2 level (-1.60 m/s). The damage calculated through the WMO method was presented as an mapping using QGIS. When calculating the damage of WCM due to abnormal climate, there was some blank area because there was no data. In order to calculate the damage of blank area, it would be possible to use the automatic weather system (AWS), which provides data from more sites than the automated synoptic observing system (ASOS).
Natural and anthropogenic factors cause forest types to continuously change. Since the ratio of forest area by forest type is important information for identifying the characteristics of national forest resources, an accurate understanding of the prospect of forest type change is required. The study aim was to use National Forest Inventory (NFI) time-series data to understand the characteristics of forest type change and to estimate future prospects of nationwide forest type change. We used forest type change information from the fifth and seventh NFI datasets, climate, topography, forest stand, and disturbance variables related to forest type change to analyze trends and characteristics of forest type change. The results showed that the forests in Korea are changing in the direction of decreasing coniferous forests and increasing mixed and broadleaf forests. The forest sites that were changing from coniferous to mixed forests or from mixed to broadleaf forests were mainly located in wet topographic environments and climatic conditions. The forest type changes occurred more frequently in sites with high disturbance potential (high temperature, young or sparse forest stands, and non-forest areas). We used a climate change scenario (RCP 8.5) to establish a forest type change model (SVM) to predict future changes. During the 40-year period from 2015 to 2055, the SVM predicted that coniferous forests will decrease from 38.1% to 28.5%, broadleaf forests will increase from 34.2% to 38.8%, and mixed forests will increase from 27.7% to 32.7%. These results can be used as basic data for establishing future forest management strategies.
Kim, Whee-Moon;Kim, Chaeyoung;Cho, Jaepil;Hur, Jina;Song, Wonkyong
Ecology and Resilient Infrastructure
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v.9
no.3
/
pp.163-173
/
2022
Climate change is a key factor that greatly influences changes in the biological seasons and geographical distribution of species. In the ecological field, the BioClimatic predictor (BioClim), which is most related to the physiological characteristics of organisms, is used for vulnerability assessment. However, BioClim values are not provided other than the future period climate average values for each GCM for the Shared Socio-economic Pathways (SSPs) scenario. In this study, BioClim data suitable for domestic conditions was produced using 1 km resolution SSPs scenario detailed data produced by Rural Development Administration, and based on the data, a species distribution model was applied to mainly grow in southern, Gyeongsangbuk-do, Gangwon-do and humid regions. Appropriate habitat distributions were predicted every 30 years for the base years (1981 - 2010) and future years (2011 - 2100) of the Acer pictum subsp. mono. Acer pictum subsp. mono appearance data were collected from a total of 819 points through the national natural environment survey data. In order to improve the performance of the MaxEnt model, the parameters of the model (LQH-1.5) were optimized, and 7 detailed biolicm indices and 5 topographical indices were applied to the MaxEnt model. Drainage, Annual Precipitation (Bio12), and Slope significantly contributed to the distribution of Acer pictum subsp. mono in Korea. As a result of reflecting the growth characteristics that favor moist and fertile soil, the influence of climatic factors was not significant. Accordingly, in the base year, the suitable habitat for a high level of Acer pictum subsp. mono is 3.41% of the area of Korea, and in the near future (2011 - 2040) and far future (2071 - 2100), SSP1-2.6 accounts for 0.01% and 0.02%, gradually decreasing. However, in SSP5-8.5, it was 0.01% and 0.72%, respectively, showing a tendency to decrease in the near future compared to the base year, but to gradually increase toward the far future. This study confirms the future distribution of vegetation that is more easily adapted to climate change, and has significance as a basic study that can be used for future forest restoration of climate change-adapted species.
This study built a model to predict the daily number of visitors to 18 trails in the Taebaeksan National Park using the auto-counter system data to analyze the factors affecting the daily number of visitors to each trail and classified the trails by visitors' behaviors. Results of the multiple regression models with the daily number of visitors of the 18 trails indicated that the events, such as the National Foundation Day celebration of Snow Festival, affected the number of visitors of all of the 18 trails and were the most critical factor that determined the daily number of visitors to the Taebaeksan National Park. The long-holidays of three days or longer and other national holidays also affected the daily number of visitors to the trails. Precipitation had a negative impact on the number of visitors of trails where the intention of most visitors was for sightseeing or camping instead of hiking, whereas had no significant impacts on the number of visitors of trails where many visitors intended for hiking. It indicated that visitors who intended for hiking went ahead hiking even if the weather was poor. The effects of temperature had a positive effect on the number of visitors who intended for hiking but a negative effect on the number of visitor to the trails near Danggol Plaza where the Snow Festival was held in each winter, suggesting that the impact of the Snow Festival was the deterministic factor for trail management. Results of K-mean clustering showed that the 18 trails of the Taekbaeksan National Park could be classified into three types: those affected by the Snow Festival (type 1), those that have sightseeing points and so were visited mostly by non-hikers (type 2), and those visited mostly by hikers (type 3). Since visitor behaviors and illegal actions differ according to the trail type, this study's results can be used to prepare a trail management plan based on the trail characteristics.
As climate change is expected to lead to a severe reduction of biodiversity, studies to investigate the reasons for habitat loss, growth decline, and death of Korean fir (Abies koreana Wilson), endangered alpine/subalpine species in Korea, have been conducted for years but found no clear answer yet. This study reviewed previous studies on Korean fir published in the journals in the past 40 years, 1980 through 2020, into 10-year units, examined the study trend by period, region, and subject with a focus on ecological studies, and analyzed the study results. The ecological studies were categorized into evolutionary ecology, physiological ecology, population ecology, and landscape ecology. Based on the results, we suggested the required research fields in the future. We found a total of 73 papers published in the past 40 years and 48 (65.8%) of them published in the past 10 years. In terms of region, Mt. Halla accounted for the most as 41 papers were on it. In terms of ecological subjects, the physiological ecology accounted for the most with 38, and the evolutionary ecology accounted for the least with 10. The review of the study results showed that many studies identified water stress caused by the water resource imbalance due to temperature increase and spring precipitation reduction following climate change as the main reason for the decline and habitat loss of Korean fir. However, recent studies suggested other factors, such as soil environment, disturbing organisms, and climatic events. The cause of the decline and death of the Korean fir not yet being clearly identified is that most of the studies dealt with the basic content, were carried out intermittently, and were concentrated in some regions. Therefore, we need long-term studies with advanced technology in each study subject at a local scale to find the cause of Korean fir decline and present sustainable management and conservation. Moreover, it is necessary to extend our study subjects to ecosystem ecology and systems ecology to integrate the results from various study subjects for a comprehensive understanding of the reason for Korean fir declines. The results of comprehensive studies could provide clearer answers for Korean fir's declines and the alternatives of conservation management and practices.
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