• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.107-116
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• 2013

This study is intended to predict variations in future land use/land cover(LULC) based on the representation concentration pathway(RCP) storyline that is a new climate change scenario and to analyze how future climate and LULC changes under RCP scenario affects streamflow in the basin. This study used climate data under RCP 4.5 and 8.5 and LULC change scenario is created by a model that is developed using storyline of RCP 4.5 and 8.5 and logistic regression(LR). Two scenarios(climate change only and LULC change only) were established. The streamflow in future periods under these scenarios was simulated by the Soil and Water Assessment Tool(SWAT) model. Each scenario showed a significant seasonal variations in streamflow. Climate change showed that it reduced streamflow in summer and autumn while it increased streamflow in spring and winter. Although LULC change little affected streamflow in the basin, the pattern for increasing and decreasing streamflow during wet and dry climate condition was significant. Therefore, it's believed that sustainable water resource policies for flood and drought depending on future LULC are required.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.5
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• pp.27-43
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• 2019

This study applied the LANDIS-II model to the forest vegetation of the study area in Yeongdong-gun, Korea to identify climate effects on ecosystems of forest vegetation. The main purpose of the study is to examine the long-term changes in forest aboveground biomass(AGB) under three different climate change scenarios; The baseline climate scenario is to maintain the current climate condition; the RCP 4.5 scenario is a stabilization scenario to employ of technologies and strategies for reducing greenhouse gas emissions; the RCP 8.5 scenario is increasing greenhouse gas emissions over time representative with 936ppm of $CO_2$ concentration by 2100. The vegetation survey and tree-ring analysis were conducted to work out the initial vegetation maps and data for operation of the LANDIS model. Six types of forest vegetation communities were found including Quercus mongolica - Pinus densiflora community, Quercus mongolica community, Pinus densiflora community, Quercus variabilis-Quercus acutissima community, Larix leptolepis afforestation and Pinus koraiensis afforestation. As for changes in total AGB under three climate change scenarios, it was found that RCP 4.5 scenario featured the highest rate of increase in AGB whereas RCP 8.5 scenario yielded the lowest rate of increase. These results suggest that moderately elevated temperatures and $CO_2$ concentrations helped the biomass flourish as photosynthesis and water use efficiency increased, but huge increase in temperature ($above+4.0^{\circ}C$) has resulted in the increased respiration with increasing temperature. Consequently, Species productivity(Biomass) of trees decrease as the temperature is elevated drastically. It has been confirmed that the dominant species in all scenarios was Quercus mongolica. Like the trends shown in the changes of total AGB, it revealed the biggest increase in the AGB of Quercus mongolica under the RCP 4.5 scenario. AGB of Quercus mongolica and Quercus variabilis decreased in the RCP 4.5 and RCP 8.5 scenarios after 2050 but have much higher growth rates of the AGB starting from 2050 under the baseline scenario. Under all scenarios, the AGB of coniferous species was eventually perished in 2100. In particular they were extinguished in early stages of the RCP 4.5 and RCP 8.5 scenarios. This is because of natural selection of communities by successions and the failure to adapt to climate change. The results of the study could be expected to be effectively utilized to predict changes of the forest ecosystems due to climate change and to be used as basic data for establishing strategies for adaptation climate changes and the management plans for forest vegetation restoration in ecological restoration fields.

• Journal of Climate Change Research
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• v.4 no.2
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• pp.77-93
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• 2013

Global warming accelerates both carbon (C) input through increased forest productivity and heterotrophic C emission in forest soils, and a future trend in soil C dynamics is uncertain. In this study, the Korean forest soil carbon model (KFSC model) was applied to 1,467,458 ha of Pinus densiflora forests in Korea to predict future C dynamics under RCP 8.5 climate change scenario (RCP scenario). Korea was divided into 16 administrative regions, and P. densiflora forests in each region were classified into six classes by their stand ages : 1 to 10 (I), 11 to 20 (II), 21 to 30 (III), 31 to 40 (IV), 41 to 50 (V), and 51 to 80-year-old (VI+). The forest of each stand age class in a region was treated as a simulation unit, then future net primary production (NPP), soil respiration (SR) and forest soil C stock of each simulation unit were predicted from the 2012 to 2100 under RCP scenario and constant temperature scenario (CT scenario). As a result, NPP decreased in the initial stage of simulation then increased while SR increased in the initial stage of simulation then decreased in both scenarios. The mean NPP and SR under RCP scenario was 20.2% and 20.0% higher than that under CT scenario, respectively. When the initial age class was I, IV, V or VI+, predicted soil C stock under CT scenario was higher than that under RCP scenario, however, the countertrend was observed when the initial age class was II or III. Also, forests having a lower site index showed a lower soil C stock. It suggested that the impact of temperature on NPP was higher when the forests grow faster. Soil C stock under RCP scenario decreased at the end of simulation, and it might be derived from exponentially increased SR under the higher temperature condition. Thus, the difference in soil C stock under two scenarios will be much larger in the further future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.3
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• pp.175-190
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• 2024

In order to project changes in climate zones across the Korean Peninsula, the Trewartha's climate classification was applied to the SSP-RCP scenario data with a 1km resolution produced by the National Institute of Agricultural Sciences of the Rural Development Administration. Currently, most of the Korean Peninsula (92.3%) belongs to the temperate climate type (D), whereas only some areas (4.9%), such as Jeju Island, belongs to the subtropical climate type (C). According to SSP-RCP scenarios, the temperature is expected to gradually increase due to the influence of global warming during the 21st century, and the subtropical climate type is expected to expand to 14.1 to 48.6% of the total area of the Korean Peninsula in the far future. On the other hand, the temperate zone, which is currently most dominant on the Korean Peninsula, is expected to shrink by 85.8 to 51.4% in the late 21st century. If carbon dioxide emissions continue at the current rate, the entire Korean Peninsula will likely be dominated by subtropical and temperate regions in the distant future. In particular, the subtropical climate type is expected to dominate most of South Korea in the high-carbon scenario, except for highlands.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.53-62
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• 2013

Land-use/cover changes not only amplify or alleviate influence of climate changes but also they are representative factors to affect environmental change along with climate changes. Thus, the use of land-use/cover changes scenario, consistent climate change scenario is very important to evaluate reliable influences by climate change. The purpose for this study is to predict and analyze the future urban growth considering social and economic scenario from RCP scenario suggested by the 5th evaluation report of IPCC. This study sets land-use/cover changes scenario based on storyline from RCP 4.5 and 8.5 scenario. Urban growth rate for each scenario is calculated by urban area per person and GDP for the last 25 years and regression formula based on double logarithmic model. In addition, the urban demand is predicted by the future population and GDP suggested by the government. This predicted demand is spatially distributed by the urban growth probability map made by logistic regression. As a result, the accuracy of urban growth probability map is appeared to be 89.3~90.3% high and the prediction accuracy for RCP 4.5 showed higher value than that of RCP 8.5. Urban areas from 2020 to 2050 showed consistent growth while the rate of increasing urban areas for RCP 8.5 scenario showed higher value than that of RCP 4.5 scenario. Increase of urban areas is predicted by the fact that famlands are damaged. Especially RCP 8.5 scenario indicated more increase not only farmland but also forest than RCP 4.5 scenario. In addition, the decrease of farmland and forest showed higher level from metropolitan cities than province cities. The results of this study is believed to be used for basic data to clarify complex two-way effects quantitatively for future climate change, land-use/cover changes.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.2
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• pp.65-73
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• 2016

We estimated the averaged maximum incidences of bacterial canker at suitable sites for kiwifruit cultivation in 2020s and 2050s using D-PSA-K model with RCP4.5 and RCP8.5 climate change scenarios. Though there was a little difference between the estimation using RCP4.5 and that using RCP8.5, the estimated maximum disease incidences were more than 75% at all the suitable sites in Korea except for some southern coastal areas and Jeju island under the assumption that there are a plenty of infections to cause the symptoms. We also analyzed the intermediate and final outputs of D-PSA-K model to find out the trends on the change in disease incidence affected by climate change. Whereas increase of damage to kiwifruit canes in a non-frozen environment caused by bacterial canker was estimated at almost all the suitable sites in both the climate change scenarios, rate of necrosis increase caused by the bacterial canker pathogen in a frozen environment during the last overwintering season was predicted to be reduced at almost all the suitable sites in both the climate change scenarios. Directions of change in estimated maximum incidence varied with sites and scenarios. Whereas the maximum disease incidence at 3.14% of suitable sites for kiwifruit cultivation in 2020s under RCP4.5 scenario was estimated to increase by 10% or more in 2050s, the maximum disease incidence at 25.41% of the suitable sites under RCP8.5 scenario was estimated so.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.1
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• pp.35-44
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• 2015

Forests contain a huge amount of carbon (C) and climate change could affect forest C dynamics. This study was conducted to predict the C dynamics of Pinus densiflora and Quercus variabilis forests, which are the most dominant needleleaf and broadleaf forests in Korea, using the Korean Forest Soil Carbon (KFSC) model under the two climate change scenarios (2012-2100; Constant Temperature (CT) scenario and Representative Concentration Pathway (RCP) 8.5 scenario). To construct simulation unit, the forest land areas for those two species in the 5th National Forest Inventory (NFI) data were sorted by administrative district and stand age class. The C pools were initialized at 2012, and any disturbance was not considered during the simulation period. Although the forest C stocks of two species generally increased over time, the forest C stocks under the RCP 8.5 scenario were less than those stocks under the CT scenario. The C stocks of P. densiflora forests increased from 260.4 Tg C in 2012 to 395.3 (CT scenario) or 384.1 Tg C (RCP 8.5 scenario) in 2100. For Q. variabilis forests, the C stocks increased from 124.4 Tg C in 2012 to 219.5 (CT scenario) or 204.7 (RCP 8.5 scenario) Tg C in 2100. Compared to 5th NFI data, the initial value of C stocks in dead organic matter C pools seemed valid. Accordingly, the annual C sequestration rates of the two species over the simulation period under the RCP 8.5 scenario (65.8 and $164.2g\;C\;m^{-2}\;yr^{-1}$ for P. densiflora and Q. variabilis) were lower than those values under the CT scenario (71.1 and $193.5g\;C\;m^{-2}\;yr^{-1}$ for P. densiflora and Q. variabilis). We concluded that the C sequestration potential of P. densiflora and Q. variabilis forests could be decreased by climate change. Although there were uncertainties from parameters and model structure, this study could contribute to elucidating the C dynamics of South Korean forests in future.

• Korean journal of applied entomology
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• v.52 no.4
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• pp.427-430
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• 2013

Recently, climate change scenarios were substituted by the Special Report on Emission Scenarios (SRES) for Representative Concentration Pathway (RCP). Using the RCP scenario, the World Meteorological Organization (WMO) produced new climate change scenarios. Further, the National Institute of Meteorological Research (NIMR) of Korea produced new climate change scenarios for the Korean Peninsula. In this study, emergence time of small brown planthopper (SBPH), Laodelphax striatellus and the number of generations a year were estimated during climatic normal year (1981-2010) with previous studies and they were predicted during 2050s (2045-2054) and 2090s (2085-2094) by means of RCP8.5 climate change scenario. In comparison with $176.0{\pm}0.97$ Julian data in the climatic normal year, the emergence time of overwintering SBPH was predicted to be $13.2{\pm}0.18$ days ($162.8{\pm}0.91$ Julian date) earlier in 2050s and $32.1{\pm}0.61$ days ($143.9{\pm}1.08$ Julian date) earlier in 2090s. The SBPH was expected to produce an additional $2.0{\pm}0.02$ generations in 2050s and $5.2{\pm}0.06$ generations in 2090s.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.5
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• pp.47-62
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• 2020

Rice paddy accounts for approximately 52.5% of all farmlands in South Korea, and it is closely related to the water environment. Climate change is expected to affect not only agricultural productivity also the water and the nutrient circulation. Therefore this study was aimed to evaluate changes of nitrogen load from rice paddy considering climate change scenario uncertainty. APEX-Paddy model which reflect rice paddy environment by modifying APEX (Agricultural Policy and Environmental eXtender) model was used. Using the AIMS (APCC Integrated Modeling Solution) offered by the APEC Climate Center, bias correction was conducted for 9 GCMs using non-parametric quantile mapping. Bias corrected climate change scenarios were applied to the APEX-Paddy model. The changes and uncertainty in runoff and nitrogen load were evaluated using multi-model ensemble. Paddy runoff showed a change of 23.1% for RCP4.5 scenario and 45.5% for RCP8.5 scenario compared the 2085s (2071 to 2100) against the base period (1976 to 2005). The nitrogen load was found to be increased as 43.9% for RCP4.5 scenario and 76.0% for RCP8.5 scenario. The uncertainty analysis showed that the annual standard deviation of nitrogen loads increased in the future, and the maximum entropy indicated an increasing tendency. And Duncan's analysis showed significant differences among GCMs as the future progressed. The result of this study seems to be used as a basis for mid- and long-term policies for water resources and water system environment considering climate change.

• Korean Journal of Agricultural Science
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• v.46 no.3
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• pp.661-670
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• 2019

In this study, we constructed a model of an area where the production and production amount of wild vegetables which are designated as short term income forest products for the whole country are self-sufficient for the representative Eastern Braken fern(Pteridium aquilinum)and Edible aster(Aster scaber). The difference between the existing cultivation site and the model result was examined, and the distribution of the cultivable area was simulated according to the near future climate change by the 2050s. The degree of agreement between the cultivated area and the actual native area was very low at 14.5% for Eastern Braken fern and 12.9% for Edible aster. Using the Maxent model, which has already been proven by many research examples, the cultivation maps through the model can guarantee statistical accuracy by considering many variables. To analyze future location changes, the RCP 4.5 scenario and the RCP 8.5 scenario were applie Edible aster d to predict potential future cultivable areas and compare them to the present. There was no decrease in the cultivable area due to climate change nationwide. However, in the RCP 8.5 scenario for Eastern Braken fern and the RCP 4.5 scenario for Edible aster, declining areas such as Gangwon-do, Jeollabuk-do and Gyeongsangbuk-do showed prominence according to the scenarios. The result of this study suggests that various models can be used for the production of short-term forest productivity maps and it will be used as a climate change impact assessment data for competitive forest products considering the influence of future climate change.