• Journal of Korean Society of Forest Science
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• v.105 no.3
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• pp.351-359
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• 2016

This study was conducted to analyze the effect of climate change on the tree-ring growth of Pinus koraiensis in Korea. Annual tree-ring growth data of P. koraiensis collected by the $5^{th}$ National Forest Inventory were first organized to analyze yearly growth patterns of the species. When tree-ring growth data were analyzed through cluster analysis based on similarity of climatic conditions, five clusters were identified. Yearly growing degree days and standard precipitation index based on daily mean temperature and precipitation data from 1951 to 2010 were calculated by cluster. Using the information, yearly temperature effect index(TEI) and precipitation effect index(PEI) by cluster were estimated to analyze the effect of climatic conditions on the growth of the species. Tree-ring growth estimation equations by cluster were developed by using the product of yearly TEI and PEI as independent variable. The tree-ring growth estimation equations were applied to the climate change scenarios of RCP 4.5 and RCP 8.5 for predicting the changes in tree-ring growth by cluster of P. koraiensis from 2011 to 2100. The results of this study are expected to provide valuable information necessary for estimating local growth characteristics of P. koraiensis and for predicting changes in tree-ring growth patterns caused by climate change.

• Korean Journal of Construction Engineering and Management
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• v.19 no.1
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• pp.103-113
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• 2018

In this study, Construction work is mainly done outdoors, so earth works, reinforced concrete works, etc. are Non-Working Days to rainfall. In particular, changes in rainfall due to global warming have made air calculation more difficult. Therefore, when establishing the process plan, the change of the rainfall in the area should be identified and Non-Working Days should be calculated. In this study, the time of rainfall change point was identified using the meteorological 'observation' data from 1960 to 2016 in Incheon and RCP 4.5, 'weather forecast' data from 2018 to 2074, Year rainfall and seasonal rainfall. The results showed that rainfall changed point in 1972, 1988, 2013, 2038, 2050 and 2069. In particular, it has been found that non-working days due to rainfall has big changed point as of 2013, 2038 and 2069.

• Journal of Korean Society of Forest Science
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• v.99 no.6
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• pp.908-913
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• 2010

This study analyzed the impact of climatic and topographic factors on tree radial growth of Pinus densiflora and Quercus spp. in central regions of Korea. To find the relationship between annual tree radial growth and climatic factors, we took the core samples from individual trees and measured the tree radial width. On the assumption that the tree radial growth is related to the tree age, we estimated the radial growth by the tree age as an independent variable. Also, we estimated the standard growth, defined as the radial growth of trees aged 30. As results, we found the spatial auto-correlation in the radial growth of the red pine. Moreover, we also found the relationships between climatic and topographic and the standard growth using the GAM (Generalized Additive Model). Increase of temperature has negative impacts on the radial growth of Pinus densiflora, while it has positive impacts on the radial growth of Quercus spp.. On the other hands, increase of precipitation has negative impacts on the radial growth of both species. Lastly, we predicted the spatial distribution changes of Pinus densiflora and Quercus spp. using the temperature increase scenario and the Geographic Information System (GIS) based forest type map. We could predict that Pinus densiflora is more vulnerable than Quercus spp. to climate change so that the habitats of Pinus densiflora will be gradually changed to the habitats of Quercus spp. in eastern coastal and southern regions of Korea after 60 years.

• Korean Journal of Ecology and Environment
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• v.51 no.3
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• pp.221-233
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• 2018

This study was carried out to predict the current and future potential distribution and to identify the factors affecting potential distribution of 7 plants(Lamium amplexicaule L., Trigonotis peduncularis(Trevir.) Benth. ex Hemsl, Capsella bursa-pastoris (L.) L. W. Medicus, Taraxacum officinale Weber, Veronica persica Poir., Conyza sumatrensis E. Walker, Hypochaeris radicata L.) selected as indicators for climate change in agricultural ecosystem. We collected presence/absence data of 7 indicator plants at 108 sites in South Korea and applied the Maxent model. According to future climate scenario, the distribution area of C. bursa-pastoris(L.) L. W. Medicus, T. officinale Weber, and V. persica Poir. was expected to be reduced, but the distribution range was to be maintained. The distribution areas and range of the C. sumatrensis E. Walker and H. radicata L. were expected to be increased. The distribution area and range of T. peduncularis (Trevir.) Benth. Ex Hemsl. and L. amplexicalue L. were rapidly decreased. Non-climatic factors such as land cover and altitude were the most important environmental variable for T. officinale Weber, C. bursa-pastoris(L.) L.W.Medicus, V. persica Poir., T. peduncularis (Trevir.) Benth. Ex Hemsl., and L. amplexicalue L.. Climatic factors were the most important environmental variable for C. sumatrensis E. Walker and H. radicata L.. It is expected that the future potential distribution of 7 indicator plants response to climate change will be used to monitor and to establish the management plan.

• Journal of Korea Water Resources Association
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• v.42 no.6
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• pp.433-443
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• 2009

For the better understanding of the temporal characteristics of soil water, this study is to suggest a stochastic soil water model and to apply it for impact assessment of climate change. The loss function is divided into 3 stages for more specified comprehension of the probabilistic behavior of soil water, and especially, the soil water model considering the stochastic characteristics of precipitation is developed in order to consider the variation of climatic factors. The simulation result of soil water model confirms that the proposed soil water model can re-generate the observation properly, and it also proves that the soil water behaves with consistent cycle based on the precipitation pattern. Moreover, with the simulation results with a climate change scenario, it can be predicted that the future soil water will have higher variations than present soil water.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.4
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• pp.192-203
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• 2011

The CERES-Barley crop simulation model was used to assess the impacts of climate change on the potential yield of winter naked barley in Korea. Fifty six sites over the southern part of the Korean Peninsula were selected to compare the climate change impacts in various climatic conditions. Based on the A1B climate change scenarios of Korea, the present climatological normal (1971-2000) and the three future ones (2011-2040, 2041-2070, and 2071-2100) were considered in this study. The three future normals were divided by three environmental conditions with changes in: (1) temperature only, (2) carbon dioxide concentration only, and (3) both temperature and carbon dioxide concentration. The agreement between the observed and simulated outcomes was reasonable with the coefficient of determination of grain yield to be 0.78. We concluded that the CERES-Barley model was suitable for predicting climate change impacts on the potential yield of winter naked barley. The effect of the increased temperature only with the climate change scenario was negative to the potential yield of winter naked barley, which ranges from -34 to -9% for the three future normals. However, the effect of the elevated carbon dioxide concentration only on the potential yield of winter naked barley was positive, ranging from 6 to 31% for the three future normals. For the elevated conditions of both temperature and carbon dioxide concentration, the potential yields increased by 8, 15, and 13% for the 2011-2040, 2041-2070, and 2071-2100 normals, respectively.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.136-149
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• 2011

The aim of this study is to develop future climate scenario by downscaling the regional climate model (RCM) from global climate model (GCM) based on IPCC A1B scenario. To this end, the study first resampled the KMA-RCM(Korea meteorological administration-regional climate model) from spatial resolution of 27km to 1km. Second, observed climatic data of temperature and rainfall through 1971-2000 were processed to reflect the temperature lapse rate with respect to the altitude of each meteorological observation station. To optimize the downscaled results, Co-kriging was used to calculate temperature lapse-rate; and IDW was used to calculate rainfall lapse rate. Fourth, to verify results of the study we performed correlation analysis between future climate change projection data and observation data through the years 2001-2010. In this study the past climate data (1971-2000), future climate change scenarios(A1B), KMA-RCM(Korea meteorological administration-regional climate model) results and the 1km DEM were used. The research area is entire South Korea and the study period is from 1971 to 2100. Monthly mean temperatures and rainfall with spatial resolution of 1km * 1km were produced as a result of research. Annual average temperature and precipitation had increased by $1.39^{\circ}C$ and 271.23mm during 1971 to 2100. The development of downscaling method using GIS and verification with observed data could reduce the uncertainty of future climate change projection.

• Journal of Ecology and Environment
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• v.44 no.1
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• pp.33-40
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• 2020

Background: Understanding the geographical distribution of a species is a key component of studying its ecology, evolution, and conservation. Although Schlegel's Japanese gecko (Gekko japonicus) is widely distributed in Northeast Asia, its distribution has not been studied in detail. We predicted the present and future distribution of G. japonicus across China, Japan, and Korea based on 19 climatic and 5 environmental variables using the maximum entropy (MaxEnt) species distribution model. Results: Present time major suitable habitats for G. japonicus, having greater than 0.55 probability of presence (threshold based on the average predicted probability of the presence records), are located at coastal and inland cities of China; western, southern, and northern coasts of Kyushu and Honshu in Japan; and southern coastal cities of Korea. Japan contained 69.3% of the suitable habitats, followed by China (27.1%) and Korea (4.2%). Temperature seasonality (66.5% of permutation importance) was the most important predictor of the distribution. Future distributions according to two climate change scenarios predicted that by 2070, and overall suitable habitats would decrease compared to the present habitats by 18.4% (scenario RCP 4.5) and 10.4% (scenario RCP 8.5). In contrast to these overall trends, range expansions are expected in inland areas of China and southern parts of Korea. Conclusions: Suitable habitats predicted for G. japonicus are currently located in coastal cities of Japan, China, and Korea, as well as in isolated patches of inland China. Due to climate change, suitable habitats are expected to shrink along coastlines, particularly at the coastal-edge of climate change zones. Overall, our results provide essential distribution range information for future ecological studies of G. japonicus across its distribution range.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.199-199
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• 2017

Sustainable wheat production is of paramount importance for attaining/maintaining the food self-sufficiency status of the rapidly growing nation of Pakistan. However, the average wheat yield per unit area has been dwindling in recent years and the climate-induced variations in rainfall patterns and temperature regimes, during the wheat growth period, are believed to be the reason behind this decline. Crop growth simulation models are powerful tools capable of playing pivotal role in evaluating the climate change impacts on crop yield or productivity. This study was aimed to predict the plausible variations in the wheat yield for future climatic trends so that possible mitigation strategies could be explored. For this purpose, Aquacrop model v. 4.0 was employed to simulate the wheat yield under present and future climatology of the largest agricultural province of Punjab in Pakistan. The data related to crop phenology, management and yield were collected from the experimental plots to calibrate and validate the model. The future climate projections were statistically downscaled from five general circulation models (GCMs) and compared with the base line climate from 1980 to 2010. The model was fed with the projected climate to simulate the wheat yield based on the RCP (representative concentration pathways) 4.5 and 8.5. Under the worst, most likely future scenario of temperature rise and rainfall reduction, the crop yield decreased and water footprint, especially blue, increased, owing to the elevated irrigation demands due to accelerated evapotranspiration rates. The modeling results provided in this study are expected to provide a basic framework for devising policy responses to minimize the climate change impacts on wheat production in the area.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.486-486
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• 2018

During the post green revolution era, wheat and rice were the main crops of concern to cater the food security issues of Pakistan. The use of semi dwarf high yielding varieties along with extensive use of fertilizers and surface and ground water lead to substantial increase in crop production. However, the higher crop productivity came at the cost of over exploitation of the precious land and water resources, which ultimately has resulted in the dwindling production rates, loss of soil fertility, and qualitative and quantitative deterioration of both surface and ground water bodies. Recently, during the past two decades, severe climate changes are further pushing the Pakistan's wheat-rice system towards its limits. This necessitates a careful analysis of the current crop water requirements and water footprints (both green and blue) to project the future trends under the most likely climate change phenomenon. This was done by using the FAO developed CROPWAT model v 8.0, coupled with the statistically-downscaled climate projections from the 8 Global Circulation Models (GCMs), for the two future time slices, 2030s (2021-2050) and 2060s (2051-2080), under the two Representative Concentration Pathways (RCPs): 4.5 and 8.5. The wheat-rice production system of Punjab, Pakistan was considered as a case study in exploration of how the changing climate might influence the crop water requirements and water footprints of the two major crops. Under the worst, most likely future scenario of temperature rise and rainfall reduction, the crop water requirements and water footprints, especially blue, increased, owing to the elevated irrigation demands originating from the accelerated evapotranspiration rates. A probable increase in rainfall as envisaged by some GCMs may partly alleviate the adverse impacts of the temperature rise but the higher uncertainties associated with the predicated rainfall patterns is worth considering before reaching a final conclusion. The total water footprints were continuously increasing implying that future climate would profoundly influence the crop evapotranspiration demands. The results highlighted the significance of the irrigation water availability in order to sustain and improve the wheat-rice production system of Punjab, Pakistan.