• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.198-221
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• 2021

After large-scale reforestation in the 1960s and 1970s, forests in Korea have gradually been aging. Net ecosystem CO₂ exchange of old-growth forests is theoretically near zero; however, it can be a CO₂ sink or source depending on the intervention of disturbance or management. In this study, we report the CO₂ budget dynamics of the Gwangneung deciduous old-growth forest (GDK) in Korea and examined the following two questions: (1) is the preserved GDK indeed CO₂ neutral as theoretically known? and (2) can we explain the dynamics of CO₂ budget by the common mechanisms reported in the literature? To answer, we analyzed the 15-year long CO₂ flux data measured by eddy covariance technique along with other biometeorological data at the KoFlux GDK site from 2006 to 2020. The results showed that (1) GDK switched back-and-forth between sink and source of CO₂ but averaged to be a week CO₂ source (and turning to a moderate CO₂ source for the recent five years) and (2) the interannual variability of solar radiation, growing season length, and leaf area index showed a positive correlation with that of gross primary production (GPP) (R²=0.32~0.45); whereas the interannual variability of both air and surface temperature was not significantly correlated with that of ecosystem respiration (RE). Furthermore, the machine learning-based model trained using the dataset of early monitoring period (first 10 years) failed to reproduce the observed interannual variations of GPP and RE for the recent five years. Biomass data analysis suggests that carbon emissions from coarse woody debris may have contributed partly to the conversion to a moderate CO₂ source. To properly understand and interpret the long-term CO₂ budget dynamics of GDK, new framework of analysis and modeling based on complex systems science is needed. Also, it is important to maintain the flux monitoring and data quality along with the monitoring of coarse woody debris and disturbances.

• Journal of Korea Water Resources Association
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• v.45 no.12
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• pp.1293-1307
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• 2012

This study is to evaluate the RHESSys (Regional Hydro-Ecological Simulation System) simulated streamflow (Q), evapotranspiration (ET), soil moisture (SM), gross primary productivity (GPP) and photosynthetic productivity (PSNnet) with the measured data. The RHESSys is a hydro-ecological model designed to simulate integrated water, carbon, and nutrient cycling and transport over spatially variable terrain. A 8.5 $km^2$ Seolma-cheon catchment located in the northwest of South Korea was adopted. The catchment covers 90.0% forest and the dominant soil is sandy loam. The model was calibrated with 2 years (2007-2008) daily Q at the watershed outlet and MODIS (Moderate Resolution Imaging Spectroradiometer) GPP, PSNnet and 3 year (2007～2009) daily ET data measured at flux tower using the eddy-covariance technique. The coefficient of determination ($R^2$) and the Nash-Sutcliffe model efficiency (ME) for Q were 0.74 and 0.63, and the average $R^2$ for ET and GPP were 0.54 and 0.93 respectively. The model was validated with 1 year (2009) Q and GPP. The $R^2$ and the ME for Q were 0.92 and 0.84, the $R^2$ for GPP were 0.93.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.2
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• pp.107-121
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• 2010

We conducted a sensitivity test of Joint UK Land Environment Simulator (JULES), in which the influence of biophysical parameters on the simulation of gross primary productivity (GPP) and ecosystem respiration (RE) was investigated for two typical ecosystems in Korea. For this test, we employed the whole-year observation of eddy-covariance fluxes measured in 2006 at two KoFlux sites: (1) a deciduous forest in complex terrain in Gwangneung and (2) a farmland with heterogeneous mosaic patches in Haenam. Our analysis showed that the simulated GPP was most sensitive to the maximum rate of RuBP carboxylation and leaf nitrogen concentration for both ecosystems. RE was sensitive to wood biomass parameter for the deciduous forest in Gwangneung. For the mixed farmland in Haenam, however, RE was most sensitive to the maximum rate of RuBP carboxylation and leaf nitrogen concentration like the simulated GPP. For both sites, the JULES model overestimated both GPP and RE when the default values of input parameters were adopted. Considering the fact that the leaf nitrogen concentration observed at the deciduous forest site was only about 60% of its default value, the significant portion of the model's overestimation can be attributed to such a discrepancy in the input parameters. Our finding demonstrates that the abovementioned key biophysical parameters of the two ecosystems should be evaluated carefully prior to any simulation and interpretation of ecosystem carbon exchange in Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.2
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• pp.137-145
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• 2014

Rice-barley double cropping system is typical in southwestern part of South Korea. However, the information of carbon dioxide ($CO_2$) exchange for barley growing season has still limited in comparison with rice. Using the eddy covariance (EC) technique, seasonal variation of $CO_2$ exchange was analyzed for the barley growing season at a rice-barley double cropping field in Gimje, Korea. The effects of environmental factors and biomass on the $CO_2$ flux also were investigated. Quality control and gap-filling of flux data were conducted before this analysis and investigation. The results indicated that $CO_2$ uptake increased rapidly at tillering stage and maximum net ecosystem exchange of $CO_2$ (NEE) occurred at the early of May, 2012 ($-11.2gCm^{-2}d^{-1}$), when the heading of barley occurred. NEE, gross primary production (GPP), and ecosystem respiration (Re) during the barley growing season were -348.0, 663.3, and $315.2gCm^{-2}$, respectively. In this study, an attempt has been made to measure NEE, GPP, and Re with the help of the EC system for the barley growing season for the first time in Korea, focusing on $CO_2$ exchange between the biosphere and the atmosphere.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.273-281
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• 2013

Based on the results of continuous flux measurements at the Gimje paddy flux site in the southwestern coast of Korea, carbon dioxide and energy exchanges between customarily cultivated rice-barley double cropping paddy field and the atmosphere during the 2012 rice growing season (from $9^{th}$ Jun. 2012 through $20^{th}$ Oct. 2012) were analyzed. Carbon dioxide and energy (H, LE) fluxes were estimated by the eddy covariance method. Environmental parameters (net radiation, precipitation, etc.) and plant biomass (LAI, plant height, etc.) were measured along with fluxes. After the quality control and gap-filling, the observed fluxes were analyzed. The results have been showed that net ecosystem exchange (NEE), gross primary production (GPP), and ecosystem respiration (Re) during the rice cropping period were -277.1, 710.3, and 433.2 g C $m^{-2}$, respectively.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1117-1132
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• 2019

Forest covers 30% of the Earth's land area and plays an important role in global carbon flux through its ability to store much greater amounts of carbon than other terrestrial ecosystems. The Gross Primary Production (GPP) represents the productivity of forest ecosystems according to climate change and its effect on the phenology, health, and carbon cycle. In this study, we estimated the daily GPP for a forest ecosystem using remote-sensed data from Moderate Resolution Imaging Spectroradiometer (MODIS) and machine learning algorithms Support Vector Machine (SVM). MODIS products were employed to train the SVM model from 75% to 80% data of the total study period and validated using eddy covariance measurement (EC) data at the six flux tower sites. We also compare the GPP derived from EC and MODIS (MYD17). The MODIS products made use of two data sets: one for Processed MODIS that included calculated by combined products (e.g., Vapor Pressure Deficit), another one for Unprocessed MODIS that used MODIS products without any combined calculation. Statistical analyses, including Pearson correlation coefficient (R), mean squared error (MSE), and root mean square error (RMSE) were used to evaluate the outcomes of the model. In general, the SVM model trained by the Unprocessed MODIS (R = 0.77 - 0.94, p < 0.001) derived from the multi-sites outperformed those trained at a single-site (R = 0.75 - 0.95, p < 0.001). These results show better performance trained by the data including various events and suggest the possibility of using remote-sensed data without complex processes to estimate GPP such as non-stationary ecological processes.

• Korean Journal of Remote Sensing
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• v.27 no.4
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• pp.481-494
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• 2011

Investigation of the $CO_2$ exchange between biosphere and atmosphere at regional, continental, and global scales can be directed to combining remote sensing with carbon cycle process to estimate vegetation productivity. NASA Earth Observing System (EOS) currently produces a regular global estimate of gross primary productivity (GPP) and annual net primary productivity (NPP) of the entire terrestrial earth surface at 1 km spatial resolution. While the MODIS GPP algorithm uses meteorological data provided by the NASA Data Assimilation Office (DAO), the sub-pixel heterogeneity or complex terrain are generally reflected due to coarse spatial resolutions of the DAO data (a resolution of $1{\circ}\;{\times}\;1.25{\circ}$). In this study, we estimated inputs retrieved from MODIS products of the AQUA and TERRA satellites with 5 km spatial resolution for the purpose of finer GPP and/or NPP determinations. The derivatives included temperature, VPD, and solar radiation. Seven AmeriFlux data located in the Corn Belt region were obtained to use for evaluation of the input data from MODIS. MODIS-derived air temperature values showed a good agreement with ground-based observations. The mean error (ME) and coefficient of correlation (R) ranged from $-0.9^{\circ}C$ to $+5.2^{\circ}C$ and from 0.83 to 0.98, respectively. VPD somewhat coarsely agreed with tower observations (ME = -183.8 Pa ~ +382.1 Pa; R = 0.51 ~ 0.92). While MODIS-derived shortwave radiation showed a good correlation with observations, it was slightly overestimated (ME = -0.4 MJ $day^{-1}$ ~ +7.9 MJ $day^{-1}$; R = 0.67 ~ 0.97). Our results indicate that the use of inputs derived MODIS atmosphere and land products can provide a useful tool for estimating crop GPP.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.278-278
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• 2021

가뭄이 장기간 지속되어 농업적 가뭄 상태가 되면 토양의 수분이 마르기 시작하면서, 식생의 생장활동이 방해되고, 이는 식생의 광합성 활동까지 영향을 미친다. 광합성을 통해 대기 중의 이산화탄소가 흡수되고 산소 발생이 증가하는데, 광합성이 활발하지 못하면 상대적으로 대기 중의 이산화탄소 농도가 증가한다. 본 연구에서는 이러한 토양수분, 식생활동과 대기 중 이산화탄소의 농도의 관계를 다중분광센서인 MODerate resolution Imaging Spectroradiometer (MODIS) 산출물을 이용하여 분석하였다. 기존 토양수분의 경우, 마이크로파 센서를 통해 산출된 값을 활용했지만, 이는 상대적으로 공간 해상도가 조악하다는 단점을 갖고 있어서 면적이 작은 연구지역을 분석할 때에는 한계점을 갖고 있다. 이러한 문제를 해결하기 위하여 상대적으로 고해상도인 광학센서를 이용한 토양수분 산정 방법을 적용하였다. 또한, MODIS 총 일차생산량 (Gross Primary Productivity, GPP) 산출물을 이용하여 식생 호흡량과의 관계식을 통해 이산화탄소 플럭스를 계산하였다. 원격탐사 기반의 토양수분, 식생지수, 이산화탄소 플럭스를 한국에서 발생한 가뭄 기간 중, 2014년과 2015년도에 대하여 지점 관측자료인 플럭스 타워에서 제공되는 값과 비교 분석하였다. 분석한 결과 토양수분, 식생 지수, 탄소플럭스는 순차적으로 지연시간을 두고 상관성이 발생함을 확인하였다. 토양수분과 식생 지수 사이에는 1개월, 식생지수와 탄소플럭스는 0.5개월의 지연시간 후에 가장 높은 상관성을 보였다.

• Journal of Climate Change Research
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• v.5 no.1
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• pp.71-81
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• 2014

Using the Eddy Covariance technique, we analyzed seasonal variation in net ecosystem $CO_2$ exchange (NEE) and investigated the effects of environmental factors and aboveground biomass of rice on the $CO_2$ fluxes in a rice-barley double cropping paddy field of Gimje, Korea. Quality control and gap-filling were conducted before this investigation of the effects. The results have been showed that NEE, gross primary production (GPP), and ecosystem respiration (Re) during the rice growing period were -215.6, 763.9, and $548.3g\;C\;m^{-2}$, respectively. Relation between NEE and net radiation (Rn) could be described by a quadratic equation, and about 65 % of variation in NEE was explained by changes in Rn. On the other hand, an exponential function relating Re to soil temperature accounted for approximately 43 % of variation in Re under the flooded condition of paddy field. Aboveground biomass showed significant linear relationships with NEE ($r^2=0.93$), GPP ($r^2=0.96$), and Re ($r^2=0.95$), respectively.