• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.68-81
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• 2021

The agricultural ecosystem is one of the major sources of greenhouse gas (GHG) emissions. In order to search for climate change adaptation options which mitigate GHG emissions while maintaining crop yield, it is advantageous to integrate multiple models at a high spatial resolution. The objective of this study was to develop a tool to support integrated assessment of climate change impact b y coupling the DSSAT model and the DNDC model. DNDC Regional Input File Tool(DRIFT) was developed to prepare input data for the regional mode of DNDC model using input data and output data of the DSSAT model. In a case study, GHG emissions under the climate change conditions were simulated using the input data prepared b y the DRIFT. The time to prepare the input data was increased b y increasing the number of grid points. Most of the process took a relatively short time, while it took most of the time to convert the daily flood depth data of the DSSAT model to the flood period of the DNDC model. Still, processing a large amount of data would require a long time, which could be reduced by parallelizing some calculation processes. Expanding the DRIFT to other models would help reduce the time required to prepare input data for the models.

• Korean Journal of Environmental Biology
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• v.35 no.1
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• pp.37-46
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• 2017

Climate change is the biggest concern of the $21^{st}$ century. Greenhouse gas (GHG) emissions from various sectors are attracting attention as a cause of climate change. The DeNitrification-DeComposition (DNDC) model simulates GHG emissions from cropland. To study future GHG emissions using this simulation model, various factors that could change in future need to be considered. Because most problems are from the agricultural sector, DNDC would be unable to solve the factor-changing problem itself. Hence, it is necessary to link DNDC with separate models that simulate each element. Climate change is predicted to cause a variety of environmental disasters in the future, having a significant impact on the agricultural environment. In the process of human adaptation to environmental change, the distribution and management methods of farmland will also change greatly. In this study, we introduce some drawbacks of DNDC in considering future changes, and present other existing models that can rectify the same. We further propose some combinations with models and development sub-models.

• Korean Journal of Environmental Biology
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• v.35 no.1
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• pp.13-20
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• 2017

Greenhouse gas emission from agricultural land is recognized as an important factor influencing climatic change. In this study, the national $CO_2$ emission was estimated for paddy soils, using soil GHG emission model (DNDC) with $1km^2$ scale. To evaluate the applicability of the model in Korea, verification was carried out based on field measurement data using a closed chamber. The total national $CO_2$ emission in 2015 was estimated at $5,314kt\;CO_2-eq$, with the emission per unit area ranging from $2.2{\sim}10.0t\;CO_2-eq\;ha^{-1}$. Geographically, the emission of Jeju province was particularly high, and the emission from the southern region was generally high. The result of the model verification analysis with the field data collected in this study (n=16) indicates that the relation between the field measurement and the model prediction was statistically similar (RMSE=22.2, ME=0.28, and $r^2=0.53$). More field measurements under various climate conditions, and subsequent model verification with extended data sets, are further required.

• Journal of Environmental Impact Assessment
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• v.24 no.1
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• pp.1-15
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• 2015

To mitigate the impacts of climate change on agricultural ecosystems, development of agricultural management for enhanced soil carbon sequestration is required. In this study, the effects of fertilizer types (chemical fertilizer and manure compost), cropping systems, and crop residue management on SOC(Soil Organic Carbon) sequestration were investigated. Summer corn and winter barley were cultivated on experimental plots under natural rainfall conditions for two years with chemical fertilizer and manure compost. Soil samples were collected conducted and analyzed for SOC for soil. To estimate long-term variation patterns of SOC, DNDC was run with the experimental data and the weather input parameters from 1981 to 2010. DNDC simulation demonstrated SOC reduction by chemical fertilizer treatment unless plant residues are returned; whereas compost treatments increased SOC under the same conditions and SOC increment was proportional to compost application rate. In addition, SOC further increased under corn-barley cropping system over single corn cropping due to more compost application. Regardless of nutrient input type, residue return increased SOC; however, the magnitude of SOC increase by residue return was lower than by compost application.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.462-462
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• 2011

1994년에 발효된 기후변화협약에서 우리나라는 선발 개도국으로 분류되어 온실가스 의무감축 대상국에서 제외되었으나 제2차 공약기간 (2013~2017년)부터는 온실가스 감축 의무이행이 불가피할 것으로 예상되어 그 대응책 마련이 시급한 실정이다. 현재 국내에서는 국제기준에 부합하는 온실가스 배출량 통계자료 구축을 위한 기초연구가 다양하게 수행되고 있으나 온실가스 감축을 위한 시나리오 설정이나 모의실험 연구는 계획 중이거나 시작 단계에 있다. 이 중 농경지에서의 온실가스 배출은 환경조건에 따라 온실가스를 배출하거나 흡수할 수 있는 양면성을 갖기 때문에 미래의 온실가스 배출을 예측하고 국내 실정에 맞는 저감방안을 수립하기 위해서는 다양한 조건을 적용하여 온실가스 배출량을 모의할 필요가 있다. 따라서 본 연구에서는 작물생육과 토양환경의 상호작용을 고려하여 농업생태계 내에서의 온실가스 배출을 모의하는 DNDC (Denitrification-Decomposition)를 이용하여 다양한 물관리 방식을 적용하여 벼 재배시 논에서의 온실가스 배출량을 산정하고 그 결과를 비교하고자 하였다. 물관리 방식에 따른 온실가스 배출 모의를 위해 관개시기를 조정하여 상시담수와 간단관개시의 시나리오를 적용하고, 담수심의 깊이에 따라 심수관개시와 최소 담수심 시나리오를 적용하여 온실가스 배출량을 산정하였다. 이는 향후 농경지를 대상으로 관개 방식 개선을 통해 온실가스 배출량을 감축하고 지속가능한 토지이용방안을 모색하는데 기초자료로 활용할 수 있을 것이라 판단된다.

• Journal of Climate Change Research
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• v.5 no.4
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• pp.359-366
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• 2014

This research was conducted to estimate methane emission from paddy field of 16 local government levels using the DNDC(DeNitrification-DeComposition) model from 1990 to 2010. Four treatments used in DNDC model for methane emission calculations were (1) midseason drainage with rice straw, (2) midseason drainage without rice straw, (3) continuous flooding with rice straw, and (4) continuous flooding without rice straw. Methane emissions at continuous flooding with rice straw were the highest ($471kg\;C\;ha^{-1}$) while were the lowest ($187kg\;C\;ha^{-1}$) at midseason drainage without rice straw. The average methane emission for 21 years was the highest ($1,406Gg\;CO_{2-eq}$.) in Jeonnam province because of its large cultivation area. Jeju province had the highest the average methane emission per unit area due to the organic content in soil.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.2
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• pp.47-57
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• 2014

This study was conducted to predict greenhouse gas (GHG) emission from paddy by future climate change scenario in Korea. Chuncheon city in Kangwon province were selected as study area. A1B Special Report on Emission Scenario (SRES) of the IPCC (Intergovernmental panel on climate change) was used to assess the future potential climate change. The rainfall and temperature was projected to increase by 8.4 % and 1.9 % (2040s), 35.9 % and 27.0 % (2060s), 19.2 % and 30.8 % (2090s), respectively, compare to the 2010s value. Under the climate change, Denitrification-Decomposition (DNDC) predicted an increase in $N_2O$, $CO_2$ and $CH_4$ emissions from paddy. The simulations resulted in annual net emissions of 0.4~2.4, 500.5~734.5 and 29.4~160.4 kg/ha/year of $N_2O-N$, $CH_4-C$ and $CO_2-C$, respectively, with a cumulated global warming potential (GWP) of $14.5{\sim}21.7t{\cdot}CO_2/ha/year$ were affected by rainfall, temperature, manure amendment and fertilizer amount. The simulation results suggested that implementation of manure amendment or reduction of water consumption instead of increased fertilizer application rates would more efficiently mitigate GHG emissions.

• Journal of Korean Society of Forest Science
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• v.107 no.2
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• pp.140-150
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• 2018

For the estimation of greenhouse gas dynamics in forests, it is useful to use a model which simulates both carbon (C) and nitrogen (N) cycle simultaneously. A forest C model, called FBDC, was developed and validated in Korea. However, studies on development of forest N model are insufficient. This study aimed to suggest a development process of a forest C and N model. We analyzed the general features, structures, ecological processes, input data, output data, and methods of integrating C and N cycles of the VISIT, Biome-BGC, Forest-DNDC, and O-CN. The structure and features of the FBDC were also analyzed. The VISIT was developed by integrating forest C model with a N cycle module, and the new model also could be designed by combining the FBDC with a N cycle module. The VISIT and Forest-DNDC could estimate soil $N_2O$ emissions, and the integrated model should include the processes shared by these models. Especially, the overseas models linked C and N cycles based on N absorption, C absorption, and decomposition of dead organic matter. Therefore, the integration of the FBDC with N cycle module should apply this linkage of structures between C and N cycles. Climate, soil texture, and species distribution data, which are essential for the model development, were available in Korea. However, parameter data associated with N cycle and validation data for soil $N_2O$ emissions need to be obtained by field studies.

• Ecology and Resilient Infrastructure
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• v.5 no.3
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• pp.189-198
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• 2018

In 21th century, climate change is one of the fundamental issue. Greenhouses gases are pointed as the main cause of climate change. Soil play a vital role of carbon sink and also can be a huge source of greenhouse gases defense on the management. Flux of greenhouse gases is not the only factor can be changed by climate change. Climate change can alter proper management. Temperature change will modify crop planting and harvesting date. Other management skills like fertilizer, manure, irrigation, tillage can also be changed with climate change. In this study, greenhouse gases emission in rice paddy in South Korea is simulated with DNDC model from 2011 - 2100 years. Climate for future is simulated with RCP 8.5 scenario for understanding the effect of climate change to greenhouse gases emission. Various rice paddy flooding techniques were applied to find proper management for future management. With conventional flooding technique, climate change increase greenhouse gases emission highly. Marginal flooding can decrease large amount of greenhouse gases emission and even it still increases with climate change, it has the smallest increasing ratio. If we suppose the flooding technique will change for best grain yield, dominant flooding technique will be different from conventional flooding to marginal flooding. The management change will reduce greenhouse gases emission. The result of study shows the possibility to increase greenhouse gases emission with climate change and climate change adaptation can show apposite result compared without the adaptation.

• Ecology and Resilient Infrastructure
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• v.2 no.2
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• pp.185-190
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• 2015

Greenhouse gas (GHG) emission from agricultural lands is recognized as one of important factors of global warming. The objective of this short communication was to evaluate the applicability of different soil GHG emission prediction models on agricultural systems in Korea. Four models, namely, DNDC, DAYCENT, EXPERT-N and COUP, were selected and the basic structure (e.g., components and sub-model), input variables, and output variables were compared. In particular, the availability and compilation of essential input variables were assessed. Major input variables needed for operating these predictive models were found to be available through database systems established by national organizations such as the Korea Meteorological Administration, the Korean Soil Information System, and the Rural Development Administration. However, in order to apply these models in Korea, it was necessary to calibrate and validate each of the models for the domestic landscape settings and climate conditions. In addition, field data of long-term monitoring of GHG emission from agricultural lands are limited and therefore should be measured.