• 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 Wetlands Research
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• v.15 no.1
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• pp.105-114
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• 2013

Recently, Due to Climate change, extreme rainfall occurs frequently. In many preceding studies, Because of extreme hydrological events changes, it is expected that peak flood Magnitude and frequency of drainage infrastructures changes. However, at present, probability rainfall in the drainage facilities design is assumed to Stationary which are not effected from climate change and long-term fluctuation. In the future, flood control safety standard should be reconsidered about the valid viewpoint. In this paper, in order to assess impact of climate change on drainage system, Future climate change information has been extracted from RCP 8.5 Climate Change Scenario for IPCC AR5, then estimated the design rainfall for various durations at return periods. Finally, the design flood estimated through the HEC-HMS Model which is being widely used in the practices, estimated the effect of climate change on the Design Flood of Mihochen basin. The results suggested that the Design Flood increase by climate change. Due to this, the Flood risk of Mihochen basin can be identified to increase comparing the present status.

• Journal of The Geomorphological Association of Korea
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• v.20 no.4
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• pp.85-99
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• 2013

The objective of this paper is to analyze the spatial distribution of errors in the DEM generated using waterlines from multi-temporal remote sensing data and to assess flood vulnerability. Unlike conventional research in which only global statistics of errors have been generated, this paper tries to quantitatively analyze the spatial distribution of errors from a probabilistic viewpoint using geostatistical simulation. The initial DEM in Baramarae tidal flats was generated by corrected tidal level values and waterlines extracted from multi-temporal Landsat data in 2010s. When compared with the ground measurement height data, overall the waterline-based DEM underestimated the actual heights and local variations of the errors were observed. By applying sequential Gaussian simulation based on spatial autocorrelation of DEM errors, multiple alternative error distributions were generated. After correcting errors in the initial DEM with simulated error distributions, probabilities for flood vulnerability were estimated under the sea level rise scenarios of IPCC SERS. The error analysis methodology based on geostatistical simulation could model both uncertainties of the error assessment and error propagation problems in a probabilistic framework. Therefore, it is expected that the error analysis methodology applied in this paper will be effectively used for the probabilistic assessment of errors included in various thematic maps as well as the error assessment of waterline-based DEMs in tidal flats.

• Journal of Climate Change Research
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• v.3 no.1
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• pp.13-24
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• 2012

CCGIS (Climate Change Adaptation Toolkit based on GIS) was developed to use as a tool for the climate change assessment and any relevant tasks involving climate change adaptation policy over Korean peninsula. The main objective of CCGIS is to facilitate an efficient and relevant information for the estimation of climate change vulnerability index by providing key information in the climate change adaptation process. In particular, the atmospheric modeling system implemented in CCGIS, which is composed of climate and meteorological numerical model and the atmospheric environmental models, were used as a tool to generate the climate and environmental IPCC SRES (A2, B1, A1B, A1T, A1FI, and A1 scenarios) climate data for the year of 2000, 2020, 2050, and 2100. This article introduces the components of CCGIS and describes its application to the Korean peninsula. Some examples of the CCGIS and its use for both climate change adaptation and estimation of vulnerability index applied to Korean provinces are presented and discussed here.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.2
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• pp.108-125
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• 2015

The agro-climatic index is one of the ways to assess the climate resources of particular agricultural areas on the prospect of agricultural production; it can be a key indicator of agricultural productivity by providing the basic information required for the implementation of different and various farming techniques and practicalities to estimate the growth and yield of crops from the climate resources such as air temperature, solar radiation, and precipitation. However, the agro-climate index can always be changed since the index is not the absolute. Recently, many studies which consider uncertainty of future climate change have been actively conducted using multi-model ensemble (MME) approach by developing and improving dynamic and statistical downscaling of Global Climate Model (GCM) output. In this study, the agro-climatic index of Korean Peninsula, such as growing degree day based on $5^{\circ}C$, plant period based on $5^{\circ}C$, crop period based on $10^{\circ}C$, and frost free day were calculated for assessment of the spatio-temporal variations and uncertainties of the indices according to climate change; the downscaled historical (1976-2005) and near future (2011-2040) RCP climate sceneries of AR5 were applied to the calculation of the index. The result showed four agro-climatic indices calculated by nine individual GCMs as well as MME agreed with agro-climatic indices which were calculated by the observed data. It was confirmed that MME, as well as each individual GCM emulated well on past climate in the four major Rivers of South Korea (Han, Nakdong, Geum, and Seumjin and Yeoungsan). However, spatial downscaling still needs further improvement since the agro-climatic indices of some individual GCMs showed different variations with the observed indices at the change of spatial distribution of the four Rivers. The four agro-climatic indices of the Korean Peninsula were expected to increase in nine individual GCMs and MME in future climate scenarios. The differences and uncertainties of the agro-climatic indices have not been reduced on the unlimited coupling of multi-model ensembles. Further research is still required although the differences started to improve when combining of three or four individual GCMs in the study. The agro-climatic indices which were derived and evaluated in the study will be the baseline for the assessment of agro-climatic abnormal indices and agro-productivity indices of the next research work.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.1
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• pp.11-22
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• 2010

According to IPCC 4th Assessment Report, concentration of carbon dioxide has been increasing by 30% since Industrial Revolution. Most of IPCC $CO_2$ emission scenarios estimate that the concentration will reach up to double of its present level within 100-year if the current tendency continues. The global warming has resulted in the agro-climate change over the Korean Peninsula as well. Accordingly, it is necessary to understand the future agro-climate induced by the increase of greenhouse gases in terms of the agro-climatic indices in the Korean peninsula. In this study, the future climate is simulated by an atmosphere/ocean/land surface/sea ice coupled general circulation climate model, Pusan National University Coupled General Circulation Model(hereafter, PNU CGCM), and by a regional weather prediction model, Weather Research and Forecasting Model(hereafter, WRF) for the purpose of a dynamical downscaling. The changes of the vegetable period and the crop growth period, defined as the total number of days of a year exceeding daily mean temperature of 5 and 10, respectively, have been analyzed. Our results estimate that the beginning date of vegetable and crop growth periods get earlier by 3.7 and 17 days, respectively, in spring under the $CO_2$-doubled climate. In most of the Korean peninsula, the predicted frost days in spring decrease by 10 days. Climatic production index (CPI), which closely represent the productivity of rice, tends to increase in the double $CO_2$ climate. Thus, it is suggested that the future $CO_2$ doubled climate might be favorable for crops due to the decrease of frost days in spring, and increased temperature and insolation during the heading date as we expect from the increased CPI.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.4B
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• pp.337-346
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• 2010

Climate change has a huge impact on various parts of the world. This study quantified and analyzed the effects on hydrological behavior caused by climate, vegetation canopy and land use change of Soyanggang dam watershed (2,694.4 $km^2$) using the semi-distributed model SWAT (Soil Water Assessment Tool). For the 1997-2006 daily dam inflow data, the model was calibrated with the Nash-Sutcliffe model efficiencies between the range of 0.45 and 0.91. For the future climate change projection, three GCMs of MIROC3.2hires, ECHAM5-OM, and HadCM3 were used. The A2, A1B and B1 emission scenarios of IPCC (Intergovernmental Panel on Climate Change) were adopted. The data was corrected for each bias and downscaled by Change Factor (CF) method using 30 years (1977-2006, baseline period) weather data and 20C3M (20th Century Climate Coupled Model). Three periods of data; 2010-2039 (2020s), 2040-2069 (2050s), 2070-2099 (2080s) were prepared for future evaluation. The future annual temperature and precipitation were predicted to change from +2.0 to $+6.3^{\circ}C$ and from -20.4 to 32.3% respectively. Seasonal temperature change increased in all scenarios except for winter period of HadCM3. The precipitation of winter and spring increased while it decreased for summer and fall for all GCMs. Future land use and vegetation canopy condition were predicted by CA-Markov technique and MODIS LAI versus temperature regression respectively. The future hydrological evaluation showed that the annual evapotranspiration increases up to 30.1%, and the groundwater recharge and soil moisture decreases up to 55.4% and 32.4% respectively compared to 2000 condition. Dam inflow was predicted to change from -38.6 to 29.5%. For all scenarios, the fall dam inflow, soil moisture and groundwater recharge were predicted to decrease. The seasonal vapotranspiration was predicted to increase up to 64.2% for all seasons except for HadCM3 winter.

• Journal of Environmental Impact Assessment
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• v.15 no.4
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• pp.249-258
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• 2006

Impacts of global warming have been identified in many areas including natural ecosystem. A good number of studies based on climate models forecasting future climate have been conducted in many countries worldwide. Due to its global coverage, GCM, which is a most frequently used climate model, has limits to apply to Korea with such a narrower and complicated terrain. Therefore, it is necessary to perform a study impact assessment of climate changes with a climate model fully reflecting characteristics of Korean climate. In this respect, this study was designed to compare and analyze the GCM and RCM in order to determine a suitable climate model for Korea. In this study, spatial scope was Korea for 10 years from 1981 to 1990. As a research method, current climate was estimated on the basis of the data obtained from observation at the GHCN. Future climate was forecast using 4 GCMs furnished by the IPCC among SRES A2 Scenario as well as the RCM received from the NIES of Japan. Pearson correlation analysis was conducted for the purpose of comparing data obtained from observation with GCM and RCM. As a result of this study, average annual temperature of Korea between 1981 and 1990 was found to be around $12.03^{\circ}C$, with average daily rainfall being 2.72mm. Under the GCM, average annual temperature was between 10.22 and $16.86^{\circ}C$, with average daily rainfall between 2.13 and 3.35mm. Average annual temperature in the RCM was identified $12.56^{\circ}C$, with average daily rainfall of 5.01mm. In the comparison of the data obtained from observation with GCM and RCM, RCMs of both temperature and rainfall were found to well reflect characteristics of Korea's climate. This study is important mainly in that as a preliminary study to examine impact of climate changes such as global warming it chose appropriate climate model for our country. These results of the study showed that future climate produced under similar conditions with actual ones may be applied for various areas in many ways.

• 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 Korean Society of Forest Science
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• v.101 no.1
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• pp.53-61
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• 2012

This study developed a growth model for Larix leptolepis based on the WLS model to examine the effects of climate change on them. The site index was chosen as the dependent variable and location, weather, and edaphic factor were chosen as independent variables. Simulations were performed under three A1B climate change scenarios with the temperature ranging from $-3.3^{\circ}C$ to $+3.3^{\circ}C$. The simulation results showed that the site index decreased with peak at $-0.8^{\circ}C$. The decrease level of the site index by region was also analyzed. Each scenario, site index has decreased mostly but some region was increased. When the temperature increased up to $3^{\circ}C$, site index was decreased to everywhere.