• Journal of Environmental Impact Assessment
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• v.12 no.5
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• pp.383-393
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• 2003

IPCC(Intergovernmental Panel on Climate Change)는 향후 100년 동안 지구의 평균기온이 $1^{\circ}C$에서 $3.5^{\circ}C$ 상승할 경우, 각 기후대가 극방향으로 약 150~550km 이동할 것으로 예측하고 있으나, 과거 기후변동 연구결과들은 삼림의 이동속도를 100년간 4~200km로 추정하고 있어 식생이 기후대의 이동을 따라가지 못하여 사멸되는 지역이 발생할 것으로 예측되고 있다. 약 960km의 남북으로 긴 지형적 특성을 가진 한반도 역시 이러한 영향을 벗어나지 못할 것으로 예측되고 있어 기존의 기후변화 시나리오와 함께 삼림의 이동성을 고려한 영향연구가 요구된다. 본 연구는 IPCC의 새로운 기후변화 시나리오인 SRES 시나리오의 대기대순환모형(Global Climate Model, GCM) 결과와 AIM(Asia Integrated Model)/Impact[Korea] 모형을 이용하여 제작된 Holdridge 생물기후분류의 연구성과를 이용하여, CO2농도 배증시의 한반도지역의 자연식생 영향과 적응 가능성을 삼림의 이동성을 고려하여 평가하였다. 삼림의 이동속도를 0.25, 0.5, 1.0, 2.0(km/yr)로 변화시키며 2100년 한반도 자연식생의 기후 변화 영향을 평가한 결과, (1) 목본식물의 이동속도가 년간 1km 이상일 경우 삼림 피해가 미미하게 나타났으나 (2) 이동이 느린 0.25km/yr의 경우, 생육위험지역을 포함한 시나리오별 전체 피해규모는 A2(17.47%), A1(9.97%), B1(6.21%), B2(5.08%) 순으로 나타났으며, 삼림소멸의 경우는 A2, B2 시나리오에서 발생하며 A2 시나리오에서 한반도의 약 2.1%로 가장 크게 발생하였다. (3) 전반적인 생육위험 지역의 분포는 함흥만, 영흥만의 동해안지역에 집중되었으며, A2 시나리오의 극단적 소멸예상지역은 금오산, 가야산, 팔공산을 연결하는 지역에서 발생하는 것으로 나타났다.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.95-95
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• 2015

전 세계적으로 기후변화에 따른 영향을 전망하고 분석하는 연구가 활발히 진행되고 있으며, 우리나라 역시 기후변화 시나리오에 따른 영향평가를 실시하고 증가하는 위험에 대처하기 위한 다양한 연구가 진행되고 있다. 2013년부터 IPCC(Intergovernmental Panel on Climate Change)에서 배포하는 RCP(Representative Concentration Pathway) 시나리오에 의하면 우리나라의 연평균 강수량과 호우일수는 뚜렷하게 증가할 것으로 전망되고 있다. 하지만, 수공구조물을 설계하는데 있어서 기후변화의 영향을 고려한 설계기준은 미흡한 실정으로 본 연구에서는 우리나라 한강 유역을 대상으로 기후변화 시나리오에 따른 설계홍수량을 분석하였다. 유출량은 실무에서 널리 사용하고 있는 HEC-1을 이용하여 산정하였고, 입력매개변수 중 강수인자는 RCP 시나리오 기반의 확률강우량을 적용하였다. 또한, 한강유역종합치수계획(2008)을 참조하여 나머지 매개변수를 사용하였다. 본 연구를 통하여 RCP 기후변화 시나리오 기반의 확률홍수량을 산정하여 점차 증가하는 홍수위험도에 능동적으로 대처할 수 있도록 기존 하천시설물의 설계 기준의 타당성을 분석하고자 한다.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.4
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• pp.1-15
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• 2024

In recent years, climate change has been responsible for unusual weather patterns on a global scale. Droughts, natural disasters triggered by insufficient rainfall, can inflict significant social and economic consequences on the entire agricultural sector due to their widespread occurrence and the challenge in accurately predicting their onset. The frequency of drought occurrences in South Korea has been rapidly increasing since 2000, with notably severe droughts hitting regions such as Incheon, Gyeonggi, Gangwon, Chungbuk, and Gyeongbuk in 2015, resulting in significant agricultural and social damage. To prepare for future drought occurrences resulting from climate change, it is essential to develop long-term drought predictions and implement corresponding measures for areas prone to drought. The Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report outlines a climate change scenario under the Shared Socioeconomic Pathways (SSPs), which integrates projected future socio-economic changes and climate change mitigation efforts derived from the Coupled Model Intercomparison Project 6 (CMIP6). SSPs encompass a range of factors including demographics, economic development, ecosystems, institutions, technological advancements, and policy frameworks. In this study, various drought indices were calculated using SSP scenarios derived from 18 CMIP6 global climate models. The SSP5-8.5 scenario was employed as the climate change scenario, and meteorological drought indices such as the Standardized Precipitation Index (SPI), Self-Calibrating Effective Drought Index (scEDI), and Standardized Precipitation Evapotranspiration Index (SPEI) were utilized to analyze the prediction and variability of future drought occurrences in South Korea.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1505-1515
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• 2023

As extreme weather events caused by climate change are occurring around the world, blue carbon has recently been gaining attention as a carbon sink. Blue carbon has been officially recognized by the Intergovernmental Panel on Climate Change (IPCC) as a means of reducing greenhouse gases, and various studies are underway to discover new blue carbon sources both domestically and internationally. Domestic blue carbon research is centered on carbon absorption and storage in tidal flats, which account for most of the coastal wetlands, but there is a lack of research on spatial information. This study utilized the carbon storage of tidal flats from previous studies and converted it into location and spatial information for each basin of the Geumgang and Nakdong rivers. In addition, a proxy value of carbon storage per area by basin was calculated to compare and analyze the total carbon storage of various tidal flats in Korea and abroad. As a result of the analysis, both the Geumgang and Nakdong River basins showed different amounts of carbon storage depending on the tidal flats data, with the highest amount in the Geumgang basin coming from the National Ocean Survey (469,810.1 Mg C) and the highest amount in the Nakdong River basin coming from the Ministry of Environment (217,145.01 Mg C). The results of this study can be used as a basis for future research on the establishment of domestic blue carbon spatial information.

• Journal of Environmental Science International
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• v.16 no.3
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• pp.287-297
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• 2007

Increasing carbon dioxide emissions from fossil fuel use and land-use change has been perturbing the balanced global carbon cycle and changing the carbon distribution among the atmosphere, the terrestrial biosphere, the soil, and the ocean. SGCM(Simple Global Carbon Model) was used to simulate global carbon cycle for the IPCC emissions scenarios, which was six future carbon dioxide emissions from fossil fuel use and land-use change set by IPCC(Intergovernmental Panel on Climate Change). Atmospheric $CO_2$ concentrations for four scenarios were simulated to continuously increase to $600{\sim}1050ppm$ by the year 2100, while those for the other two scenarios to stabilize at $400{\sim}600ppm$. The characteristics of these two $CO_2$-stabilized scenarios are to suppress emissions below $12{\sim}13$ Gt C/yr by tile year 2050 and then to decrease emissions up to 5 Gt C/yr by the year 2100, which is lower than the current emissions of $6.3{\pm}0.4$ Gt C/yr. The amount of carbon in the atmosphere was simulated to continuously increase for four scenarios, while to increase by the year $2050{\sim}2070$ and then decrease by the year 2100 for the other two scenarios which were $CO_2$-stabilized scenarios. Even though the six emission scenarios showed different simulation results, overall patterns were such similar that the amount of carbon was in the terrestrial biosphere to decrease first several decades and then increase, while in the soil and the ocean to continuously increase. The ratio of carbon partitioning to tile atmosphere for the accumulated total emissions was higher for tile emission scenario having higher atmospheric $CO_2$, however that was decreasing as time elapsed. The terrestrial biosphere and the soil showed reverse pattern to the atmosphere.

• Journal of the Korean association of regional geographers
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• v.19 no.4
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• pp.615-626
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• 2013

In this study, spatial patterns of the urban flood vulnerability index in Seoul are examined by considering climate exposure, sensitivity, and adaptability associated with floodings for recent 5 year (2006~2010) period by the smallest administrative unit called Dong. According to the results of correlation analyses based on the IPCC(Intergovernmental Panel on Climate Change)'s vulnerability model, among many variables associated with urban flooding, rainwater tank capacity, 1-day maximum precipitation and flood pumping station capacity have statistically-significant, and relatively-high correlations with the number of flood damage in Seoul. The flood vulnerability map demonstrates that the extensive areas along Anyang and Joongnang streams show relatively high flood vulnerability in Seoul due to high sensitivity. Especially in case of Joongnang stream areas, climatic factors also contribute to the increase of flood vulnerability. At local scales, several Dong areas in Gangdong-gu and Songpa-gu also show high flood vulnerability due to low adaptability, while those in Gangnam-gu do due to high sensibility and climate factor such as extreme rainfall events. These results derived from the flood vulnerability map by Dong unit can be utilized as primary data in establishing the adaptation, management and proactive policies for flooding prevention within the urban areas in more detail.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.4
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• pp.101-112
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• 2015

This study was conducted to predict greenhouse gas (GHG) emission from a radish field by future climate change scenario. A radish field located at Chuncheon-si Gangwon-do was selected, and A1B Special Report on Emission Scenario (SRES) of the IPCC (Intergovernmental panel on climate change) was applied to simulate the future potential climate change. Rainfall and temperature data were predicted to be increased by 8.4 % and 1.9 % in 2040s, 35.9 % and 27.0 % in 2060s, 19.2 % and 30.8 % in 2090s, respectively, compared to the climate data in 2010s. The $N_2O$, $CO_2$, and $CH_4$ emission were estimated to be increased by 0.4 up to 2.4 kg/ha/yr, by 500.5 up to 734.5 kg/ha/year, and by 29.4 up to 160.4 kg/ha/yr, which were resulted from the global warming potential (GWP) of 14.5~21.7 $CO_2$/ha/year caused by the amount changes of rainfall, temperature, manure amendment, and fertilizer applied in fields. One distinct feature of the study result was that the changes of $N_2O-N$, $CH_4-C$ and $CO_2-C$ with future potential climate change simulation were varied by soil texture. Therefore it was concluded that there is a need to apply appropriate amount of manure amendment needs and to consider soil texture as well.

• Journal of Environmental Impact Assessment
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• v.21 no.5
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• pp.757-765
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• 2012

The purpose of this study was to estimate the spatial-temporal NPP(Net Primary Productivity) and SCS(Soil Carbon Storage) of forest ecosystem under climate change in the capital area of South Korea using Mapss-Century1 (MC1), one of Dynamic Global Vegetation Models (DGVMs). The characteristics of the NPP and SCS changes were simulated based on a biogeochemical module in this model. As results of the simulation, the NPP varies from 2.02 to 7.43 tC $ha^{-1}\;yr^{-1}$ and the SCS varies from 34.55 to 84.81 tC $ha^{-1}$ during 1971~2000 respectively. Spatial mean NPP showed a little decreasing tendency in near future (2021~2050) and then increased in far future (2071~2100) under the condition of increasing air temperature and precipitation which were simulated by the A1B climate change scenario of Intergovernmental Panel on Climate Change (IPCC). But it was estimated that the temporal change of spatial mean NPP indicates 4.62% increasing tendency in which elevation is over 150m in this area. However, spatial mean SCS was decreased in the two future periods under same climate condition.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.5
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• pp.25-34
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• 2009

The objective of this study is to evaluate the future potential climate and vegetation canopy change impact on a dam watershed hydrology. A $6,661.5\;km^2$ dam watershed, the part of Han-river basin which has the watershed outlet at Chungju dam was selected. The SWAT model was calibrated and verified using 9 year and another 7 year daily dam inflow data. The Nash-Sutcliffe model efficiency ranged from 0.43 to 0.91. The Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model3 (CGCM3) data based on Intergovernmental Panel on Climate Change (IPCC) SRES (Special Report Emission Scenarios) B1 scenario was adopted for future climate condition and the data were downscaled by artificial neural network method. The future vegetation canopy condition was predicted by using nonlinear regression between monthly LAI (Leaf Area Index) of each land cover from MODIS satellite image and monthly mean temperature was accomplished. The future watershed mean temperatures of 2100 increased by $2.0^{\circ}C$, and the precipitation increased by 20.4 % based on 2001 data. The vegetation canopy prediction results showed that the 2100 year LAI of deciduous, evergreen and mixed on April increased 57.1 %, 15.5 %, and 62.5% respectively. The 2100 evapotranspiration, dam inflow, soil moisture content and groundwater recharge increased 10.2 %, 38.1 %, 16.6 %, and 118.9 % respectively. The consideration of future vegetation canopy affected up to 3.0%, 1.3%, 4.2%, and 3.6% respectively for each component.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.4
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• pp.55-63
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• 2013

This study investigates the trends and uncertainty of the impacts of climate change on paddy rice production in the Geumho river basin. The Long Ashton Research Station stochastic Weather Generator (LARS-WG) was used to derive future climate data for the Geumho river basin from 15 General Circulation models (GCMs) for 3 Special Report on Emissions Scenarios (SRES) (A2, A1B and B1) included in the Intergovernmental Panel on Climate Change (IPCC) 4th assessment report. The Food and Agricultural Organization (FAO) AquaCrop, a water-driven crop model, was statistically calibrated for the 1982 to 2010 climate. The index of agreement (IoA), prediction efficiency ($R^2$), percent bias (PBIAS), root mean square error (RMSE) and a visual technique were used to evaluate the adjusted AquaCrop simulated yield values. The adjusted simulated yields showed RMSE, NSE, IoA and PBIAS of 0.40, 0.26, 0.76 and 0.59 respectively. The 5, 9 and 15 year central moving averages showed $R^2$ of 0.78, 0.90 and 0.96 respectively after adjustment. AquaCrop was run for the 2020s (2011-2030), 2050s (2046-2065) and 2090s (2080-2099). Climate change projections for Geumho river basin generally indicate a hotter and wetter future climate with maximum increase in the annual temperature of $4.5^{\circ}C$ in the 2090s A1B, as well as maximum increase in the rainfall of 45 % in the 2090s A2. The means (and ranges) of paddy rice yields are projected to increase by 21 % (17-25 %), 34 % (27-42 %) and 43 % (31-54 %) for the 2020s, 2050s and 2090s, respectively. The A1B shows the largest rice yield uncertainty in all time slices with standard deviation of 0.148, 0.189 and $0.173t{\cdot}ha^{-1}$ for the 2020s, 2050s and 2090s, respectively.