• Journal of Environmental Science International
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• v.23 no.4
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• pp.707-713
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• 2014

The purpose of this article is analyzing the economic impacts of abnormal climate on total revenue of red pepper in Korea, with employing the equilibrium displacement model. Our simulation results show the rate of yield change, price change, and total revenue change according to the climate change scenarios. In th case of by RCP 8.5 Scenario, red pepper production volume would be expected to decrease by 77.2% compared to 2012 while price increasing by 29.6%. As a result, total revenue to be returned to farmers would be reduced by 47.6% than it was in 2012. In contrast, total revenue would be expected to decline by 29.6% according to RCP 4.5 scenario.

• Journal of Soil and Groundwater Environment
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• v.24 no.2
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• pp.23-37
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• 2019

To evaluate the available groundwater supply to the agricultural water demand in the future with the climate change scenarios for 40 sub-regions in Jeju Island, groundwater recharge and the available groundwater supply were estimated using water balance analysis method. Groundwater recharge was calculated by subtracting the actual evapotranspiration and direct runoff from the total amount of water resources and available groundwater supply was set at 43.6% from the ratio of the sustainable groundwater capacity to the groundwater recharge. According to the RCP 4.5 scenario, the available groundwater supply to the agricultural water demand is estimated to be insufficient in 2020 and 2025, especially in the western and eastern regions of the island. However, such a water shortage problem is alleviated in 2030. When applying the RCP 8.5 scenario, available groundwater supply can't meet the water demand over the entire decade.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.475-486
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• 2020

Climate change scenarios are the basis of research to cope with climate change, and consist of large-scale spatio-temporal data. From the data point of view, one scenario has a large capacity of about 83 gigabytes or more, and the data format is semi-structured, making it difficult to utilize the data through means such as search, extraction, archiving and analysis. In this study, a tool for analyzing extreme climate events based on spatial information is developed to improve the usability of large-scale, multi-period climate change scenarios. In addition, a pilot analysis is conducted on the time and space in which the heavy rain thresholds that occurred in the past can occur in the future, by applying the developed tool to the RCP8.5 climate change scenario. As a result, the days with a cumulative rainfall of more than 587.6 mm over three days would account for about 76 days in the 2080s, and localized heavy rains would occur. The developed analysis tool was designed to facilitate the entire process from the initial setting through to deriving analysis results on a single platform, and enabled the results of the analysis to be implemented in various formats without using specific commercial software: web document format (HTML), image (PNG), climate change scenario (ESR), statistics (XLS). Therefore, the utilization of this analysis tool is considered to be useful for determining future prospects for climate change or vulnerability assessment, etc., and it is expected to be used to develop an analysis tool for climate change scenarios based on climate change reports to be presented in the future.

• Journal of Ecology and Environment
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• v.43 no.4
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• pp.352-363
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• 2019

Background: Invasive plant species are considered a major threat to biodiversity, ecosystem functioning, and human wellbeing worldwide. Climatically suitable ranges for invasive plant species are expected to expand due to future climate change. The identification of current invasions and potential range expansion of invasive plant species is required to plan for the management of these species. Here, we predicted climatically suitable habitats for 11 invasive plant species and calculated the potential species richness and their range expansions in different provinces of the Republic of Korea (ROK) under current and future climate change scenarios (RCP 4.5 and RCP 8.5) using the maximum entropy (MaxEnt) modeling approach. Results: Based on the model predictions, areas of climatically suitable habitats for 90.9% of the invasive plant species are expected to retain current ecological niches and expand to include additional climatically suitable areas under future climate change scenarios. Species richness is predicted to be relatively high in the provinces of the western and southern regions (e.g., Jeollanam, Jeollabuk, and Chungcheongnam) under current climatic conditions. However, under future climates, richness in the provinces of the northern, eastern, and southeastern regions (e.g., Seoul, Incheon, Gyeonggi, Gyeongsangnam, Degue, Busan, and Ulsan) is estimated to increase up to 292%, 390.75%, and 468.06% by 2030, 2050, and 2080, respectively, compared with the current richness. Conclusions: Our study revealed that the rates of introduction and dispersion of invasive plant species from the western and southern coasts are relatively high and are expanding across the ROK through different modes of dispersion. The negative impacts on biodiversity, ecosystem dynamics, and economy caused by invasive plant species will be high if preventive and eradication measures are not employed immediately. Thus, this study will be helpful to policymakers for the management of invasive plant species and the conservation of biodiversity.

• Journal of Climate Change Research
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• v.9 no.2
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• pp.143-156
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• 2018

Evapotranspiration is a key element in designing and operating agricultural hydraulic structures. The profound effect of climate change to local agro-hydrological systems makes it inevitable to study the potential variability in evapotranspiration rate in order to develop policies on future agricultural water management as well as to evaluate changes in agricultural environment. The APEX-Paddy model was used to simulate local evapotranspiration responses to climate change scenarios. Nine Global Climate Models(GCMs) downscaled using a non-parametric quantile mapping method and a Multi?Model Ensemble method(MME) were used for an uncertainty analysis in the climate scenarios. Results indicate that APEX-Paddy and the downscaled 9 GCMs reproduce evapotranspiration accurately for historical period(1976~2005). For future periods, simulated evapotranspiration rate under the RCP 4.5 scenario showed increasing trends by -1.31%, 2.21% and 4.32% for 2025s(2011~2040), 2055s(2041~2070) and 2085s(2071~2100), respectively, compared with historical(441.6 mm). Similar trends were found under the RCP 8.5 scenario with the rates of increase by 0.00%, 4.67%, and 7.41% for the near?term, mid?term, and long?term periods. Monthly evapotranspiration was predicted to be the highest in August, July was the month having a strong upward trend while. September and October were the months showing downward trends in evapotranspiration are mainly resulted from the shortening of the growth period of paddy rice due to temperature increase and stomatal closer as ambient $CO_2$ concentration increases in the future.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.314-314
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• 2023

Extreme climate events can have a large impact on human life by hampering social, environmental, and economic development. Global circulation models (GCMs) are the widely used numerical models to understand the anticipated future climate change. However, different GCMs can project different future climates due to structural differences, varying initial boundary conditions and assumptions about the physical phenomena. The multi-model ensemble (MME) approach can improve the uncertainties associated with the different GCM outcomes. In this study, a comprehensive rating metric was used to select the best-performing GCMs out of 11 CMIP5 and 13 CMIP6 GCMs, according to their skills in terms of four temporal and five spatial performance indices, in replicating the 21 extreme climate indices during the baseline (1975-2017) in South Korea. The MME data were derived by averaging the simulations from all selected GCMs and three top-ranked GCMs. The random forest (RF) algorithm was also used to derive the MME data from the three top-ranked GCMs. The RF-derived MME data of the three top-ranked GCMs showed the highest performance in simulating the baseline extreme climate which was subsequently used to project the future extreme climate indices under both the representative concentration pathway (RCP) and the socioeconomic concentration pathway scenarios (SSP). The extreme cold and warming indices had declining and increasing trends, respectively, and most extreme precipitation indices had increasing trends over the period 2031-2100. Compared to all scenarios, RCP8.5 showed drastic changes in future extreme climate indices. The coasts in the east, south and west had stronger warming than the rest of the country, while mountain areas in the north experienced more extreme cold. While extreme cold climatology gradually declined from north to south, extreme warming climatology continuously grew from coastal to inland and northern mountainous regions. The results showed that the socially, environmentally and agriculturally important regions of South Korea were at increased risk of facing the detrimental impacts of extreme climatology.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.143-143
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• 2021

Climate change indicators, mainly frequent drought which has happened since the drought of 1994, 1995, and 2012 causing the devastating effect to the agricultural sector, and could be more disruptive given the context of climate change indicators by increasing the temperature and more variable and extreme precipitation. Changes in frequency, duration, and severity of droughts will have enormous impacts on agriculture production and water management. Since both the possibility of drought manifestation and substantial yield losses, we are propositioning an integrated method for evaluating past and future agriculture drought hazards that depend on models' simulations in the Hung-up watershed. to discuss the question of how climate change might influence the impact of extreme agriculture drought by assessing the potential changes in temporal trends of agriculture drought. we will calculate the temporal trends of future drought through drought indices Standardized Precipitation Evapotranspiration Index, Standardized Precipitation Index, and Palmer drought severity index by using observed data of (1991-2020) from Wonju meteorological station and projected climate change scenarios (2021-2100) of the Representative Concentration Pathways models (RCPs). expected results confirmed the frequency of extreme agricultural drought in the future projected to increase under all studied RCPs. at present 100 years drought is anticipated to happen since the result showing under RCP2.6 will occur every 24 years, RCP4.5 every 17 years, and RCPs8.5 every 7 years, and it would be double in the largest warming scenarios. On another side, the result shows unsupportable water management, could cause devastating consequences in both food production and water supply in extreme events. Because significant increases in the drought magnitude and severity like to be initiate at different time scales for each drought indicator. Based on the expected result that the evaluating the impacts of extreme agricultural droughts and recession could be used for the development of proactive drought risk management, policies for future water balance, prioritize sustainable strengthening and mitigation strategies.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.3
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• pp.132-141
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• 2012

Climate change impact assessment of cereal crop production in South Korea was performed using land attributes and daily weather data at a farm scale as inputs to crop models. Farmlands in South Korea were grouped into 68 crop-simulation zone units (CZU) based on major mountains and rivers as well as existing land use information. Daily weather data at a 1-km grid spacing under the A1B- and RCP8.5 scenarios were generated stochastically to obtain decadal mean of daily data. These data were registered to the farmland grid cells and spatially averaged to represent climate conditions in each CZU. Monthly climate data for each decade in 2001~2100 were transformed to 30 sets of daily weather data for each CZU by using a stochastic weather generator. Soil data and crop management information for 68 CZU were used as inputs to the CERES-rice, CERE-barley and CROPGRO-soybean models calibrated to represent the genetic features of major domestic cultivars in South Korea. Results from the models suggested that the heading or flowering of rice, winter barley and soybean could be accelerated in the future. The grain-fill period of winter barley could be extended, resulting in much higher yield of winter barley in most CZUs than that of rice. Among the three major cereal grain crops in Korea, rice seems most vulnerable to negative impact of climate change, while little impact of climate change is expected on soybeans. Because a positive effect of climate change is projected for winter barley, policy in agricultural production should pay more attention to facilitate winter barley production as an adaptation strategy for the national food security.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.1
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• pp.42-54
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• 2016

It is highly anticipated that warming temperature resulting from global climate change will affect the phenological pattern of kiwifruit, which has been commercially grown in Korea since the early 1980s. Here, we present the potential impacts of climate change on the variations of flowering day of a gold kiwifruit cultivar, Haegeum, in the Jeonnam Province, Korea. By running six global climate models (GCM), the results from this study emphasize the uncertainty in climate change scenarios. To predict the flowering day of kiwifruit, we obtained three parameters of the 'Chill-day' model for the simulation of Haegeum: $6.3^{\circ}C$ for the base temperature (Tb), 102.5 for chill requirement (Rc), and 575 for heat requirement (Rh). Two separate validations of the resulting 'Chill-day' model were conducted. First, direct comparisons were made between the observed flowering days collected from 25 kiwifruit orchards for two years (2014-15) and the simulated flowering days from the 'Chill-day' model using weather data from four weather stations near the 25 orchards. The estimation error between the observed and simulated flowering days was 5.2 days. Second, the model was simulated using temperature data extracted, for the 25 orchards, from a high-resolution digital temperature map, resulting in the error of 3.4 days. Using the RCP 4.5 and 8.5 climate change scenarios from six GCMs for the period of 2021-40, the future flowering days were simulated with the 'Chill-day' model. The predicted flowering days of Haegeum in Jeonnam were advanced more than 10 days compared to the present ones from multi-model ensemble, while some individual models resulted in quite different magnitudes of impacts, indicating the multi-model ensemble accounts for uncertainty better than individual climate models. In addition, the current flowering period of Haegeum in Jeonnam Province was predicted to expand northward, reaching over Jeonbuk and Chungnam Provinces. This preliminary result will provide a basis for the local impact assessment of climate change as more phenology models are developed for other fruit trees.

• 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.