• Korean Journal of Environmental Biology
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• v.33 no.3
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• pp.345-351
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• 2015

This study was conducted to find out the methodology of carbon budget assessment among soil, atmosphere and plant. Soil respiration, net ecosystem productivity of herbs and net ecosystem productivity of woody plants have been measured in 30 years old pear orchard at Naju. Closed Dynamic Chamber (CDC) method was used to measure soil respiration and net ecosystem productivity of herbs. Net ecosystem productivity of woody plant (pear) was determined by eddy covariance method using the EddyPro (5.2.1) program. As for soil respiration, $429.1mgCO_2m^{-2}h^{-1}$ was released to atmosphere and sensitivity of soil temperature ($Q_{10}$) was 2.3. In case of herbs, respiration was superior to photosynthesis during measurement period. From 20 to 24 Jun 2015, the sum of absorbed and released $CO_2$ by herb's photosynthesis and respiration was $156.1mgCO_2m^{-2}h^{-1}$. Woody plants showed the $680.1mgCO_2m^{-2}h^{-1}$ of absorption by photosynthesis. In a farm scale, the sum of soil respiration, and net ecosystem productivity of herbs and woody plants was $0.04tonCO_2ha^{-1}$ during the measurement period, and it showed that pear orchard act as a $CO_2$ sink. This study using various approaches is expected to present a methodology for evaluating the carbon budget of perennial woody crop plantations.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.979-989
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• 2022

In hydrological surveys, observation through representative location is essential due to temporal and spatial limitations and constraints. Regarding the use of hydrological data and the accuracy of the data, there are still insufficient observatories to be used in a specific watershed. In addition, since there is virtually no standard for the location of the current evapotranspiration, this study proposes a method for determining the location of the evapotranspiration. To determining the location of evapotranspiration, a grid is selected in consideration of the operating range of the Flux Tower using the eddy covariance measurement method, which is mainly used to measure evapotranspiration. The grid of representative location was calculated using the factors affecting evapotranspiration and satellite data of evapotranspiration. The grid of representative location was classified as good, fair, and poor. As a result, the number of good grids calculated was 54. It is judged that the classification of the grid has been achieved regarding topography and land use as a characteristic that appeared in the classification of the grid. In particular, in the case of elevation or city area, there was a large deviation, and the calculated good grid was judged to be a group between the two distributions.

• Journal of Korean Society of Forest Science
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• v.110 no.4
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• pp.554-568
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• 2021

Forests are the largest carbon (C) sinks in terrestrial ecosystems. Recently, as enhancing forest C sequestration capacity has been proposed as a basic direction of the Republic of Korea's "2050 Carbon Neutral Strategy," accurate estimation of forest C sequestration has been emphasized. According to the Intergovernmental Panel on Climate Change guidelines, sequestration quantity is calculated from changes in C stocks in forest C pools, such as biomass, deadwood, litter and soil layer, and harvested wood products. However, in Korea, only the overstory biomass increase is now considered the amount of sequestration quantity, so there can be a significant difference from the actual forest C sequestration. In this study, we quantified forest C exchange through C flux measurement using an eddy covariance system and an automated soil chamber system in a 57-year-old Korean pine plantation located in Mt. Taehwa, Gwangju-si, Gyeonggi-do. Then, the net amount of C sequestration was compared with the amount of the overstory biomass increase. We estimated the annual C stock change in the remaining C pools by comparing the net sequestration amount from the C flux measurement with the overstory biomass increase and C stock change in the litter layer. Therefore, the net C sequestration of the Korean pine plantation estimated from the flux measurement was 5.96 MgC ha^-1, which was about 2.2 times greater than 2.77 MgC ha^-1 of the overstory biomass increase. The annual C stock increase in the litter layer was estimated to be 0.75 MgC ha^-1, resulting in a total annual C stock increase of 2.45 MgC ha^-1 in the remaining C pools. Our results indicate that the domestic forest is a larger C sink than the current methods, implying that more accurate calculations of the C sequestration capacity are necessary to quantify C stock changes in C pools along with the C flux measurement.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.436-445
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• 2023

Methane (CH₄) emissions from rice paddies are mainly observed using the closed chamber method or the eddy covariance method. In this study, a new observation technique combining a portable gas analyzer (Model LI-7810, LI-COR, Inc., USA) and an automatic opening/closing chamber (Model Smart Chamber, LI-COR, Inc., USA) was introduced based on the strengths and weaknesses of the existing measurement methods. A cylindrical collar was manufactured according to the maximum growth height of rice and used as an auxiliary measurement tool. All types of measured data can be monitored in real time, and CH₄ flux is also calculated simultaneously during the measurement. After the measurement is completed, all the related data can be checked using the software called 'SoilFluxPro'. The biggest advantage of the new observation technique is that time-series changes in greenhouse gas concentrations can be immediately confirmed in the field. It can also be applied to small areas with various treatment conditions, and it is simpler to use and requires less effort for installation and maintenance than the eddy covariance system. However, there are also disadvantages in that the observation system is still expensive, requires specialized knowledge to operate, and requires a lot of manpower to install multiple collars in various observation areas and travel around them to take measurements. It is expected that the new observation technique can make a significant contribution to understanding the CH₄ emission pathways from rice paddies and quantifying the emissions from those pathways.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.1
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• pp.29-41
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• 2019

Terrestrial Gross Primary Production (GPP) is the largest global carbon flux, and forest ecosystems are important because of the ability to store much more significant amounts of carbon than other terrestrial ecosystems. There have been several attempts to estimate GPP using mechanism-based models. However, mechanism-based models including biological, chemical, and physical processes are limited due to a lack of flexibility in predicting non-stationary ecological processes, which are caused by a local and global change. Instead mechanism-free methods are strongly recommended to estimate nonlinear dynamics that occur in nature like GPP. Therefore, we used the mechanism-free machine learning techniques to estimate the daily GPP. In this study, support vector machine (SVM), random forest (RF) and artificial neural network (ANN) were used and compared with the traditional multiple linear regression model (LM). MODIS products and meteorological parameters from eddy covariance data were employed to train the machine learning and LM models from 2006 to 2013. GPP prediction models were compared with daily GPP from eddy covariance measurement in a deciduous forest in South Korea in 2014 and 2015. Statistical analysis including correlation coefficient (R), root mean square error (RMSE) and mean squared error (MSE) were used to evaluate the performance of models. In general, the models from machine-learning algorithms (R = 0.85 - 0.93, MSE = 1.00 - 2.05, p < 0.001) showed better performance than linear regression model (R = 0.82 - 0.92, MSE = 1.24 - 2.45, p < 0.001). These results provide insight into high predictability and the possibility of expansion through the use of the mechanism-free machine-learning models and remote sensing for predicting non-stationary ecological processes such as seasonal GPP.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.135-145
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• 2019

Analysis of a long cycle or a trend of time series data based on a long-term observation would require comparability between data observed in the past and the present. In the present study, we proposed an approach to ensure the compatibility among the instruments used for the long-term observation, which would allow to secure continuity of the data. An open-path gas analyzer (Model LI-7500, LI-COR, Inc., USA) has been used for eddy covariance flux measurement in the Gwangneung deciduous forest for more than 10 years. The open-path gas analyzer was replaced by an enclosed-path gas analyzer (Model EC155, Campbell Scientific, Inc., USA) in July 2015. Before completely replacing the gas analyzer, the carbon dioxide ($CO_2$) and latent heat fluxes were collected using both gas analyzers simultaneously during a five-month period from August to December in 2015. It was found that the $CO_2$ fluxes were not significantly different between the gas analyzers under the condition that the daily mean temperature was higher than $0^{\circ}C$. However, the $CO_2$ flux measured by the open-path gas analyzer was negatively biased (from positive sign, i.e., carbon source, to 0 or negative sign, i.e., carbon neutral or sink) due to the instrument surface heating under the condition that the daily mean temperature was lower than $0^{\circ}C$. Despite applying the frequency response correction associated with tube attenuation of water vapor, the latent heat flux measured by the enclosed-path gas analyzer was on average 9% smaller than that measured by the open-path gas analyzer, which resulted in >20% difference of the sums over the study period. These results indicated that application of the additional air density correction would be needed due to the instrument heat and analysis of the long-term observational flux data would be facilitated by understanding the underestimation tendency of latent heat flux measurements by an enclosed-path gas analyzer.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.4
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• pp.241-263
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• 2010

KoFlux is a Korean network of micrometeorological tower sites that use eddy covariance methods to monitor the cycles of energy, water, and carbon dioxide between the atmosphere and the key terrestrial ecosystems in Korea. KoFlux embraces the mission of AsiaFlux, i.e. to bring Asia's key ecosystems under observation to ensure quality and sustainability of life on earth. The main purposes of KoFlux are to provide (1) an infrastructure to monitor, compile, archive and distribute data for the science community and (2) a forum and short courses for the application and distribution of knowledge and data between scientists including practitioners. The KoFlux community pursues the vision of AsiaFlux, i.e., "thinking community, learning frontiers" by creating information and knowledge of ecosystem science on carbon, water and energy exchanges in key terrestrial ecosystems in Asia, by promoting multidisciplinary cooperations and integration of scientific researches and practices, and by providing the local communities with sustainable ecosystem services. Currently, KoFlux has seven sites in key terrestrial ecosystems (i.e., five sites in Korea and two sites in the Arctic and Antarctic). KoFlux has systemized a standardized data processing based on scrutiny of the data observed from these ecosystems and synthesized the processed data for constructing database for further uses with open access. Through publications, workshops, and training courses on a regular basis, KoFlux has provided an agora for building networks, exchanging information among flux measurement and modelling experts, and educating scientists in flux measurement and data analysis. Despite such persistent initiatives, the collaborative networking is still limited within the KoFlux community. In order to break the walls between different disciplines and boost up partnership and ownership of the network, KoFlux will be housed in the National Center for Agro-Meteorology (NCAM) at Seoul National University in 2011 and provide several core services of NCAM. Such concerted efforts will facilitate the augmentation of the current monitoring network, the education of the next-generation scientists, and the provision of sustainable ecosystem services to our society.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.235-250
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• 2021

The overarching question of this study is how a typical rice cultivation system in Gimje, Korea was keeping up with the triple-win challenge of climate-smart agriculture (CSA). To answer this question, we have employed (1) quantitative data from direct measurement of energy, water, carbon and information flows in and out of a rice cultivation system and (2) appropriate metrics to assess production, efficiency, GHG fluxes, and resilience. The study site was one of the Korean Network of Flux measurement (KoFlux) sites (i.e., GRK) located at Gimje, Korea, managed by National Academy of Agricultural Science, Rural Development Administration. Fluxes of energy, water, carbon dioxide (CO₂) and methane (CH₄) were directly measured using eddy-covariance technique during the growing seasons of 2011, 2012 and 2014. The production indicators include gross primary productivity (GPP), grain yield, light use efficiency (LUE), water use efficiency (WUE), and carbon uptake efficiency (CUE). The GHG mitigation was assessed with indicators such as fluxes of carbon dioxide (F_CO2), methane (F_CH4), and nitrous oxide (F_N2O). Resilience was assessed in terms of self-organization (S), using information-theoretic approach. Overall, the results demonstrated that the rice cultivation system at GRK was climate-smart in 2011 in a relative sense but failed to maintain in the following years. Resilience was high and changed little for three year. However, the apparent competing goals or trade-offs between productivity and GHG mitigation were found within individual years as well as between the years, causing difficulties in achieving the triple-win scenario. The pursuit of CSA requires for stakeholders to prioritize their goals (i.e., governance) and to practice opportune interventions (i.e., management) based on the feedback from real-time assessment of the CSA indicators (i.e., monitoring) - i.e., a purpose-driven visioneering.

• Korean Journal of Agricultural and Forest Meteorology
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• v.5 no.2
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• pp.70-80
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• 2003

We report the first direct measurement of $CO_2$ flux over Kwangneung broadleaf deciduous forest, one of the tower flux sites in KoFlux network. Eddy covariance system was installed on a 30 m tower along with other meteorological instruments from June to August in 2002. Although the study site was non-ideal (with valley-like terrain), turbulence characteristics from limited wind directions (i.e., 90$\pm$45$^{\circ}$) was not significantly different from those obtained at simple, homogeneous terrains with an ideal fetch. Despite very low rate of data retrieval, preliminary results from our analysis are encouraging and worthy of further investigation. Ignoring the role of advection terms, the averaged net ecosystem exchange (NEE) of $CO_2$ ranged from -1.2 to 0.7 mg m$^{-2}$ s$^{-1}$ from June to August in 2002. The effect of weak turbulence on nocturnal NEE was examined in terms of friction velocity (u*) along with the estimation of storage term. The effect of low uf u* NEE was obvious with a threshold value of about 0.2 m s$^{-1}$ . The contribution of storage term to nocturnal NEE was insignificant; suggesting that the $CO_2$ stored within the forest canopy at night was probably removed by the drainage flow along the hilly terrain. This could be also an artifact of uncertainty in calculations of storage term based on a single-level concentration. The hyperbolic light response curves explained ＞80% of variation in the observed NEE, indicating that $CO_2$ exchange at the site was notably light-dependent. Such a relationship can be used effectively in filling up the missing gaps in NEE data through the season. Finally, a simple scaling analysis based on a linear flow model suggested that advection might play a significant role in NEE evaluation at this site.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.1
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• pp.57-72
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• 2018

Time series analysis of tower flux measurement can be used to build quantitative evidence for the achievement of climate-smart agriculture (CSA). In this study, we have assessed the first objective of CSA (regarding ecosystem productivity and efficiency) for rice paddy-dominated heterogeneous farmland. A set of quantitative indicators were evaluated by analysing the time series data of carbon, water and energy fluxes over the Haenam farmland site in Korea (HFK) during the rice growing seasons from 2003 to 2015. Four different varieties of rice were cultivated during the study period in chronological order of Dongjin No. 1 (2003-2008), Nampyung (2009), Onnuri (2010-2011), and Saenuri (2012-2015). Overall at HFK, gross primary productivity (GPP) ranged from 800 to $944g\;C\;m^{-2}$, water use efficiency (WUE) ranged from 1.91 to $2.80g\;C\;kg\;H_2O^{-1}$, carbon uptake efficiency (CUE) ranged from 1.06 to 1.34, and light use efficiency (LUE) ranged from 0.99 to $1.55g\;C\;MJ^{-1}$. Among the four rice varieties, Dongjin No. 1-dominated HFK showed the highest productivity with higher WUE and LUE, but comparable CUE. Considering the heterogeneous vegetation cover at HFK, a rule of thumb comparison suggested that the productivity of Dongjin No1-dominated HFK was comparable to those of monoculture rice paddies in Asia, whereas HFK was more efficient in water use and less efficient in carbon uptake. Saenuri-dominated HFK also produced high productivity but with the growing season length longer than Dongjin No.1. Although the latter showed better traits for CSA, farmers cultivate Saenuri because of higher pest resistance (associated with adaptability and resilience). This emphasizes the need for the evaluation of other two objectives of CSA (i.e. system resilience and greenhouse gas mitigation) for complete assessment at HFK, which is currently in progress.