• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.4
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• pp.59-68
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• 2014

Climate change influences multiple environmental aspects, certain of which are specifically related to agricultural water resources such as water supply, water management, droughts and floods. Understanding the impact of climate change on reservoirs in relation to the passage of time is an important component of water resource management for stable water supply maintenance. Changes on rainfall and hydrologic patterns due to climate change can increases the occurrence of reservoir water shortage and affect the future availability of agricultural water resources. It is a main concern for sustainable development in agricultural water resources management to evaluate adaptation capability of water supply under the future climate conditions. The purpose of this study is to predict the sustainability of agricultural water demand and supply under future climate change by applying an irrigation vulnerability assessment model to investigate evidence of climate change occurrences at a local scale with respect to potential water supply capacity and irrigation water requirement. Thus, it is a recommended practice in the development of water supply management strategies on reservoir operation under climate change.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.295-305
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• 2021

In this study, we constructed using Random Forest(RF) by selecting the meteorological factors related to the occurrence of frost. As a result, when constructing a classification model for frost occurrence, even if the amount of data set is large, the imbalance in the data set for development of model has been analyzed to have a bad effect on the predictive power of the model. It was found that building a single integrated model by grouping meteorological factors related to frost occurrence by region is more efficient than building each model reflecting high-importance meteorological factors. Based on our results, it is expected that a high-accuracy frost occurrence prediction model will be able to be constructed as further studies meteorological factors for frost prediction.

• Journal of Climate Change Research
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• v.4 no.4
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• pp.331-348
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• 2013

The frequency and intensity of abnormal climate caused by climate change is increasing in Korea. Also, the amount of damage from disaster is increasing rapidly. The research on vulnerability assessment analyzes environmentally, socially and economically vulnerable indicators and is ongoing to reduce the intensity of damage and establish adaptation policies for climate change. Therefore, in this study, we assessed vulnerability using weighting value derived by the regression equation. There are 3 evaluation items : vulnerability assessment for farmland erosion to flood, vulnerability assessment for health to heat wave, vulnerability assessment for forest fire to drought. For this study, indicators for each sectors were selected and spatial data for each sectors were established using GIS program. Results showed that vulnerability to heat wave was more affected by climate factors. On the other hand, vulnerability to flood and drought was more affected by social-economic factors. Then, to analysis efficiency of the regression analysis, vulnerability result was compared between the existing vulnerability research with no weighting applied and the vulnerability research with the influence of weighting value derived by the regression. This study showed that the regression analysis is efficient to provide practical and feasible alternatives in terms of planning climate change adaptation policies and it is expected to be utilized for vulnerability assessment in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.3
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• pp.209-218
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• 2024

The National Institute of Agricultural Sciences (NAS) operates in-house long-range climate forecasting system to support the agricultural use of climate forecast data. This system, developed through collaborative research with Pusan National University, is based on the PNU/RDA Coupled General Circulation Model (CGCM) and includes the regional climate model WRF (Weather Research and Forecasting). It generates detailed climate forecast data for periods ranging from 1 to 6 months, covering 20 key variables such as daily maximum, minimum, and average temperatures, precipitation, and agricultural meteorological elements like solar radiation, soil moisture, and ground temperature-factors essential for agricultural forecasting. The data are provided at a daily temporal resolution with a spatial resolution of a 5km grid, which can be used in point form (interpolated) or averaged across administrative regions. The system's seasonal temperature and precipitation forecasts align closely with observed climatological data, accurately reflecting spatial and topographical influences, confirming its reliability. These long-range forecasts from NAS are expected to offer valuable insights for agricultural planning and decision-making. The detailed forecast data can be accessed through the Climate Change Assessment Division of NAS.

• Journal of Environmental Impact Assessment
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• v.22 no.1
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• pp.109-116
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• 2013

By IPCC climate change scenario, the socioeconomic actions such as the land use change are closely associated with the climate change as an up zoning action of urban development to increase green gas emission to atmosphere. Prediction of the land use change with rational quality can provide better data for understanding of the climate change in future. This study aims to predict land use change of Cheongju in future and SLEUTH model is used to anticipate with the status quo condition, in which the pattern of land use change in future follows the chronical tendency of land use change during last 25 years. From 40 years prediction since 2000 year, the area urbanized compared with 2000 year increases up to 87.8% in 2040 year. The ratios of the area urbanized from agricultural area and natural area in 2040 are decreased to 53.1% and 15.3%, respectively.

• KCID journal
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• v.18 no.2
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• pp.33-42
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• 2011

Climate change has impacts on not only the average temperature rise but also the intensity and frequency of extreme events such as flood and drought. It is also expected that the damages on agricultural infrastructure will be increased resulting from increased rainfall intensity and frequency caused by climate change. To strengthen the climate change adaptation capacity, it is necessary to identify the vulnerability of a given society's physical infrastructures and to develop appropriate adaptation strategies with infrastructure management because generally facilities related to human settlements are vulnerable to climate changes and establishing an adaptive public infrastructure would reduce the damages and the repair cost. Therefore, development of mitigation strategies for agricultural infrastructure against climatic hazard is very important, but there are few studies on agricultural infrastructure vulnerability assessment and adaptation strategies. The concept of vulnerability, however, is difficult to functionally define due to the fact that vulnerability itself includes many aspects (biological, socioeconomic, etc.) in various sectors. As such, much research on vulnerability has used indicators which are useful for standardization and aggregation. In this study, for the vulnerability assessment for agricultural infrastructure, 3 categories of climate exposure, sensitivity, and adaptation capacity were defined which are composed of 16 sub-categories and 49 proxy variables. Database for each proxy variables was established based on local administrative province. Future studies are required to define the weighting factor and standardization method to calculate the vulnerability indicator for agricultural infrastructure against climate change.

• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.1
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• pp.31-38
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• 2013

The purpose of this study was to evaluate climate change vulnerability over the agricultural infrastructure in terms of flood and drought using principal component analysis. Vulnerability was assessed using vulnerability resilience index (VRI) which combines climate exposure, sensitivity, and adaptive capacity. Ten flood proxy variables and six drought proxy variables for the vulnerability assessment were selected by opinions of researchers and experts. The statistical data on 16 proxy variables for the local governments (Si, Do) were collected. To identify major variables and to explain the trend in whole data set, principal component analysis (PCA) was conducted. The result of PCA showed that the first 3 principal components explained approximately 83 % and 89 % of the total variance for the flood and drought, respectively. VRI assessment for the local governments based on the PCA results indicated that provinces where having the relatively large cultivation areas were categorized as vulnerable to climate change.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.250-257
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• 2020

It is difficult for farmers to select new crops for cultivation to increase income. So we conducted land suitability assessment of grapes with soil and climate information related to crop growth. At first, land suitabilities for grapes were classified into three categories (most suitable, suitable, low productive & not suitable areas) according to soil and climate conditions, respectively. In details, land suitability with respect to soil was assessed by soil morphological and physical properties including soil texture, drainage class, available soil depth, slope and gravel content, whereas one in accordance with climate was evaluated by average annual temperature, temperature during the growing season, temperature during maturation, the lowest temperature, chilling requirement and precipitation during the growing season. Secondly, we combined both soil and climate classification results using a most-limiting characteristic method. Maps showing the suitable land for grapes cultivation were drawn. The results indicate that the most suitable area of cultivation for grapes in south Korea was 3.43% and suitable (possible) area was 10.61%. This study may help to preserve land and increase the productivity through providing valuable information regarding where more suitable areas for grapes are located.

• 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).

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.1
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• pp.1-30
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• 2024

The international community adopts the SSP (Shared Socioeconomic Pathways) scenario as a new greenhouse gas emission pathway. As part of efforts to reflect these international trends and support for climate change adaptation measure in the agricultural sector, the National Institute of Agricultural Sciences (NAS) produced high-resolution (1 km) climate change scenarios for the Korean Peninsula based on SSP scenarios, certified as a "National Climate Change Standard Scenario" in 2022. This paper introduces SSP climate change scenario of the NAS and shows the results of the climate change projections. In order to produce future climate change scenarios, global climate data produced from 18 GCM models participating in CMIP6 were collected for the past (1985-2014) and future (2015-2100) periods, and were statistically downscaled for the Korean Peninsula using the digital climate maps with 1km resolution and the SQM method. In the end of the 21^st century (2071-2100), the average annual maximum/minimum temperature of the Korean Peninsula is projected to increase by 2.6~6.1℃/2.5~6.3℃ and annual precipitation by 21.5~38.7% depending on scenarios. The increases in temperature and precipitation under the low-carbon scenario were smaller than those under high-carbon scenario. It is projected that the average wind speed and solar radiation over the analysis region will not change significantly in the end of the 21st century compared to the present. This data is expected to contribute to understanding future uncertainties due to climate change and contributing to rational decision-making for climate change adaptation.