• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.1
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• pp.88-100
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• 2018

Methane emissions from rice paddies are the largest source of greenhouse gases in the agricultural sector, but there are significant regional differences depending on the surrounding conditions and cultivation practices. To visualize these differences and to analyze their causes and characteristics, the methane emissions from each administrative district in South Korea were calculated according to the IPCC guidelines using the data from the 2010 Agriculture, Forestry and Fisheries Census, and then the results were mapped by using the ArcGIS. The nationwide average of methane emissions per unit area was $380{\pm}74kg\;CH_4\;ha^{-1}\;yr^{-1}$. The western region showed a trend toward higher values than the eastern region. One of the major causes resulting in such regional differences was the $SF_o$ (scaling factor associated with the application of organic matter), where the number of cultivation days played an important role to either offset or deepen the differences. Comparison of our results against the actual methane emissions data observed by eddy covariance flux measurement in the three KoFlux rice paddy sites in Gimje, Haenam and Cheorwon showed some differences but encouraging results with a difference of 10 % or less depending on the sites and years. Using the updated GWP (global warming potential) value of 28, the national total methane emission in 2010 was estimated to be $8,742,000tons\;CO_2eq$ - 13% lower than that of the National Greenhouse Gas Inventory Report (i.e., $10,048,000tons\;CO_2eq$). The administrative districts-based map of methane emissions developed in this study can help identify the regional differences, and the analysis of their key controlling factors will provide important scientific basis for the practical policy makings for methane mitigation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.1
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• pp.39-47
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• 2009

The importance of securing water resources and their efficient management has attracted more attention recently due to water deficit. In water budget analysis, however, evapotranspiration(${\lambda}E$) has been approximated as the residual in the water balance equation or estimated from empirical equations and assumptions. To minimize the uncertainties in these estimates, it is necessary to directly measure ${\lambda}E$. In this study, using the eddy covariance technique, we have measured ${\lambda}E$ in a mixed forest in the Seolmacheon catchment in Korea from September 2007 to December 2008. During the growing season(May-July), ${\lambda}E$ in this mixed forest averaged about $2.2\;mm\;d^{-1}$, whereas it was on average $0.5\;mm\;d^{-1}$ during the non-growing season in winter. The annual total ${\lambda}E$ in 2008 was $581\;mm\;y^{-1}$, which is about 1/3 of the annual precipitation of 1997 mm. Despite the differences in the amount and frequency of precipitation, the accumulated ${\lambda}E$ during the overlapping period(i.e., September to December) for 2007 and 2008 was both ${\sim}110$ mm, showing virtually no difference. The omega factor, which is a measure of decoupling between forest and the atmosphere, was on average 0.5, indicating that the contributions of equilibrium ${\lambda}E$ and imposed ${\lambda}E$ to the total ${\lambda}E$ were about the same. The results suggest that ${\lambda}E$ in this mixed forest was controlled by various factors such as net radiation, vapor pressure deficit, and canopy conductance. In this study, based on the direct measurements of ${\lambda}E$, we have quantified the relative contribution of ${\lambda}E$ in the water balance of a mixed forest in the Seolmacheon catchment. In combination with runoff data, the information on ${\lambda}E$ would greatly enhance the reliability of water budget analysis in this catchment.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.4
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• pp.277-288
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• 2010

The multi-level $H_2O/CO_2$ profile system has been widely used to quantify the storage and advection effects on energy and mass fluxes measured by eddy covariance systems. In this study, we expanded the utility of the profile system by accommodating air sampling devices for isotope analyses of water vapor and $CO_2$. A pre-evacuated 2L glass flask was connected to the discharge of an Infrared Gas Analyzer (IRGA) of the profile system so that airs with known concentration of $H_2O$ and $CO_2$ can be sampled. To test the performance of this sampling system, we sampled airs from 8 levels (from 0.1 to 40 m) at the KoFlux tower of Gwangneung deciduous forest, Korea. Air samples in the 2L flask were separated into its component gases and pure $H_2O$ and $CO_2$ were extracted by using a vacuum extraction line. This novel technique successfully produced vertical profiles of ${\delta}D$ of $H_2O$ and ${\delta}^{13}C$ of $CO_2$ in a mature forest, and estimated ${\delta}D$ of evapotranspiration (${\delta}D_{ET}$) and ${\delta}^{13}C$ of $CO_2$ from ecosystem respiration (${\delta}^{13}C_{resp}$) by using Keeling plots. While technical improvement is still required in various aspects, our sampling system has two major advantages over other proposed techniques. First, it is cost effective since our system uses the existing structure of the profile system. Second, both $CO_2$ and $H_2O$ can be sampled simultaneously so that net ecosystem exchange of $H_2O$ and $CO_2$ can be partitioned at the same temporal resolution, which will improve our understanding of the coupling between water and carbon cycles in terrestrial ecosystems.

• 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 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 Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.327-339
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• 2020

Transpiration is the movement of water into the atmosphere through leaf stomata of plant, and it accounts for more than half of evapotranspiration from the land surface. The measurements of transpiration could be conducted in various ways including eddy covariance and water balance method etc. However, the transpiration measurements of individual trees are necessary to quantify and compare the water use of each species and individual component within stands. For the measurement of the transpiration by individual tree, the thermometric methods such as heat dissipation and heat pulse methods are widely used. However, it is difficult and labor consuming to maintain the transpiration measurements of individual trees in a wide range area and especially for long-term experiment. Therefore, the sharing of sapflow data through database should be useful to promote the studies on transpiration and water balance for large spatial scale. In this paper, we present sap flow database, which have Granier type sap flux data from 18 Korean pine (Pinus koraiensis) since 2011 and 16 (Quercus aliena) since 2013 in Mt.Taehwa Seoul National University forest and 18 needle fir (Abies holophylla), seven (Quercus serrata), three (Carpinus laxiflora and C. cordata each since 2013 in Gwangneung. In addition, the database includes the sapling transpiration of nine species (Prunus sargentii, Larix kaempferii, Quercus accutisima, Pinus densiflora, Fraxinus rhynchophylla, Chamecypans obtuse, P. koraiensis, Betulla platyphylla, A. holophylla, Pinus thunbergii), which were measured using heat pulse method since 2018. We believe this is the first database to share the sapflux data in Rep. of Korea, and we wish our database to be used by other researchers and contribute a variety of researches in this field.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.251-267
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• 2021

Remotely sensed vegetation indices (VIs) are empirically related with gross primary productivity (GPP) in various spatio-temporal scales. The uncertainties in GPP-VI relationship increase with temporal resolution. Uncertainty also exists in the eddy covariance (EC)-based estimation of GPP, arising from the partitioning of the measured net ecosystem CO2 exchange (NEE) into GPP and ecosystem respiration (RE). For two forests and two agricultural sites, we correlated the EC-derived GPP in various time scales with three different near-surface remotely sensed VIs: (1) normalized difference vegetation index (NDVI), (2) enhanced vegetation index (EVI), and (3) near infrared reflectance from vegetation (NIRv) along with NIRvP (i.e., NIRv multiplied by photosynthetically active radiation, PAR). Among the compared VIs, NIRvP showed highest correlation with half-hourly and monthly GPP at all sites. The NIRvP was used to test the reliability of GPP derived by two different NEE partitioning methods: (1) original KoFlux methods (GPP_Ori) and (2) machine-learning based method (GPP_ANN). GPP_ANN showed higher correlation with NIRvP at half-hourly time scale, but there was no difference at daily time scale. The NIRvP-GPP correlation was lower under clear sky conditions due to co-limitation of GPP by other environmental conditions such as air temperature, vapor pressure deficit and soil moisture. However, under cloudy conditions when photosynthesis is mainly limited by radiation, the use of NIRvP was more promising to test the credibility of NEE partitioning methods. Despite the necessity of further analyses, the results suggest that NIRvP can be used as the proxy of GPP at high temporal-scale. However, for the VIs-based GPP estimation with high temporal resolution to be meaningful, complex systems-based analysis methods (related to systems thinking and self-organization that goes beyond the empirical VIs-GPP relationship) should be developed.