• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.1
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• pp.37-45
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• 2015

Recent droughts in South Korea have had large economic and environmental impacts across the country. Changes in rainfall and hydrologic patterns due to climate change can potentially increase the occurrence of extreme droughts and affect the future availability of water resources. Therefore, it is necessary to evaluate drought vulnerability for water resources planning and management, and identify the appropriate mitigation actions to conduct a drought risk analysis in the context of climate change. The objective of this study is changes in the temporal trends of drought characteristics in South Korea to examine drought impacts under climate change. First, the changes of drought occurrence were analyzed by applying the Standardized Precipitation Evapotranspiration Index (SPEI) for meteorological data on 54 meteorological stations, and were analyzed for the past 30 years (1981-2010), and Representative Concentration Pathways (RCP) climate change scenarios (2011-2100). Second, the changes on the temporal trends of drought characteristics were performed using run theory, which was used to compare drought duration, severity, and magnitude to allow for quantitative evaluations under past and future climate conditions. These results show the high influence of climate change on drought phenomenon, and will contribute to water resources management and drought countermeasures to climate change.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.81-92
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• 2019

The objective of this study is to evaluate hydrologic impacts of climate change according to downscaling methods using the Soil and Water Assessment Tool (SWAT) model at watershed scale. We used the APCC Integrated Modeling Solution (AIMS) for assessing various General Circulation Models (GCMs) and downscaling methods. AIMS provides three downscaling methods: 1) BCSA (Bias-Correction & Stochastic Analogue), 2) Simple Quantile Mapping (SQM), 3) SDQDM (Spatial Disaggregation and Quantile Delta Mapping). To assess future hydrologic responses of climate change, we adopted three GCMs: CESM1-BGC for flood, MIROC-ESM for drought, and HadGEM2-AO for Korea Meteorological Administration (KMA) national standard scenario. Combined nine climate change scenarios were assessed by Expert Team on Climate Change Detection and Indices (ETCCDI). SWAT model was established at the Mankyung watershed and the applicability assessment was completed by performing calibration and validation from 2008 to 2017. Historical reproducibility results from BCSA, SQM, SDQDM of three GCMs show different patterns on annual precipitation, maximum temperature, and four selected ETCCDI. BCSA and SQM showed high historical reproducibility compared with the observed data, however SDQDM was underestimated, possibly due to the uncertainty of future climate data. Future hydrologic responses presented greater variability in SQM and relatively less variability in BCSA and SDQDM. This study implies that reasonable selection of GCMs and downscaling methods considering research objective is important and necessary to minimize uncertainty of climate change scenarios.

• 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 Climate Change Research
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• v.4 no.1
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• pp.11-26
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• 2013

This study examined the applicability of robust decision making (RDM) over standard decision making (SDM) by comparing each result of water supply planning under climate change uncertainties for a Korean dam case. RDM determines the rank of alternatives using the regret criterion which derives less fluctuating alternatives under the risk level regardless of scenarios. RDM and SDM methods were applied to assess hypothetic scenarios of water supply planning for the Andong dam and Imha dam basins. After generating various climate change scenarios and six assumed alternatives, the rank of alternatives was estimated by RDM and SDM respectively. As a result, the average difference in the rank of alternatives between RDM and SDM methods is 0.33~1.33 even though the same scenarios and alternatives were used to be ranked by both of RDM and SDM. This study has significance in terms of an attempt to assess a new approach to decision making for responding to climate change uncertainties in Korea. The effectiveness of RDM under more various conditions should be verified in the future.

• Journal of Korea Water Resources Association
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• v.31 no.4
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• pp.407-413
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• 1998

This study reviewed the recent studies for the climate change impact on water resource systems and applied one of the techniques to a real reservoir system - the Skagit hydropower system in U.S.A. The technique assumed that the climate change results in ±5% change in monthly average and/or standard deviation of the observed inflows for the Skagit system. For each case of the altered average and standard deviation, an optimal operating policy was derived using s SDP(Stochastic Dynamic Programming) model and compared with the operating policy for the non-climate change case. The results showed that the oparating policy of the Skagit system is more sensitive to the change in the streamflow average than that in the streamflow standard deviation. The derived operating policies were also simulated using the synthetic streamflow scenarios and their average annual gains were compared as a performance index. To choose the best operating policy among the derived policies, a Bayesian decision strategy was also presented with an example. Keywords : climate change, reservoir operating policy, stochastic dynamic programming, Bayesian decision theory.

• Ecology and Resilient Infrastructure
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• v.8 no.3
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• pp.154-163
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• 2021

This study was carried out to identify the factors affecting the distribution of suitable habitats for Geranium carolinianum, which was naturalized in South Korea, and to predict the changes of distribution in the future. We collected occurrence data of G. carolinianum at 68 sites in South Korea, and applied the MaxEnt model under climate change scenarios (SSP2-4.5, and SSP5-8.5). Precipitation seasonality (bio15), mean temperature of warmest quarter (bio10), and mean temperature of driest quarter (bio09) had high contribution for potential distribution of G. carolinianum. According to climate change scenarios, high suitable habitats of G. carolinianum occupied 6.43% of the land of South Korea in historical period (1981~2010), and 92.60% under SSP2-4.5, and 98.36% undr SSP5-8.5 in far future (2071~2100).

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.99-99
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• 2022

Jeju island has a humid subtropical climate and this climate zone is expected to migrate northward toward the main land, Korea Peninsula, as temperature increases are accelerated. Vegetation type has been inevitably shifted along with the climatic change, having more subtropical species native in southeast Asia or even in Africa. With the forest composition shift, it becomes more important than ever to analyze the water balance of the forest wihth the ongoing as well as upcoming climate change. Here, we implemented the Ecosystem Demography Biosphere Model (ED2) by initializing the key variables using forest inventory data (diameter at breast height in 2012). Out of 10,000 parameter sets randomly generated from prior distribution distributions of each parameter (i.e., Monte-Carlo Method), we selected four behavioral parameter sets using remote-sensing data (LAI-MOD15A2H, GPP-MOD17A2H, and ET-MOD16A2, 8-days at 500-m during 2001-2005), and evaluated the performances using eddy-covariance carbon flux data (2012 Mar.-Sep. 30-min) and remote sensing data between 2006-2020. We simulated each of the four RCP scenarios (2.6, 4.5, 6.0, and 8.5) from four climate forcings (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, and MIROC5 from ISIMIP2b). Based on those 64 simulation sets, we estimate the changes in water balance resulting from the forest composition shift, and also uncertainty in the estimates and the sensitivity of the estimates to the parameters, climate forcings, and RCP scenarios.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.203-203
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• 2016

The linkage between climate change and water security, i.e., the response of water resource to the future climate change, have been of great concern to both scientific community and policy makers. In this study, the impact of future climate on water resources in Yellow River Basin in North of China has been investigated using the Coupled Land surface and Hydrology Model System (CLHMS) and IPCC AR5 projected future climate change in the basin. Firstly, the performances of 14 IPCC AR5 models in reproducing the observed precipitation and temperature in China, especially in North of China, have been evaluated, and it's suggested most climate models do show systematic bias compared with the observation, however, CNRM-CM5、HadCM5 and IPSL-CM5 model are generally the best models among those 14 models. Taking the daily projection results from the CNRM-CM5, along with the bias-correction technique, the response of water resources in Yellow river basin to the future climate change in different emission scenarios have been investigated. All the simulation results indicate a reduction in water resources. The current situation of water shortage since 1980s will keep continue, the water resources reduction varies between 28 and 23% for RCP 2.6 and 4.5 scenarios. RCP 8.5 scenario simulation shows a decrease of water resources in the early and mid 21th century, but after 2080, with the increase of rainfall, the extreme flood events tends to increase.

• Journal of Climate Change Research
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• v.7 no.3
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• pp.257-268
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• 2016

Both economic growth and industrial structure have great influence on energy consumption and GHG emissions. This study analyzed long-term scenarios for GHG emissions projections considering economic growth and industry value added change. In consideration of 3 GDP and 3 industry value added outlook, total 9 scenarios were set; 'Assembly Industry Baseline(AI)', 'Assembly KEIT industry(AK)', 'Assembly Advanced Country industry(AA)', 'KDI Industry Baseline(KI)', 'KDI KEIT industry(KK)', 'KDI Advanced Country industry(KA)', 'OECD Industry Baseline(OI)', 'OECD KEIT industry(OK)', and 'OECD Advanced Country industry(OA)' scenarios. In consideration of the GDP increase rate and industry value added outlook, it is estimated that AI scenario's GHG emissions would be 777 million tons of $CO_2eq$ in 2030. On the other hand, in the case of OA scenario, GHG emissions would be 560.2 million tons of $CO_2eq$ in 2030. Differences between AI scenario's and OA scenario's were 216.8 million tons of $CO_2eq$. It can be identified by that GDP and industry value added change have great influence on GHG emissions. In view of the fact that Korea's amount of GHG emission reduction targets in 2030 were 218.6 million tons of $CO_2eq$ that the result of this research could give us valuable insight.

• International Journal of Contents
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• v.17 no.1
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• pp.61-70
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• 2021

As the resolution of climate change scenario data applied with regional models increased, Earth System Grid Federation (ESGF) was established around major climate-related organizations to jointly operated and manage large-scale climate data. ESGF developed standard software to provide model output, observation data management, dissemination, and analysis using Peer to Peer (P2P) computing technology. Roles of each institution were divided into index and data nodes. Therefore, ESGF data node was established at APEC Climate Center in Korea on behalf of Asia to share data on climate change scenarios of CORDEX-East Asia (CORDEX-EA) to study climate changes in Eastern Asia. Climate researchers are expected to play a large role in researching causes of global warming and responding to climate change by providing CORDEX-EA regional model data to the world through ESGF data node.