• 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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.366-377
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• 2016

Water use efficiency (WUE) is considered as an important ecological indicator which may provide information on the process-structure relationships associated with energy-matter-information flows in ecosystem. The WUE at ecosystem-level can be defined as the ratio of gross primary productivity (GPP) to evapotranspiration (ET). In this study, KoFlux's long-term (2007-2015) eddy covariance measurements of $CO_2$ and water vapor fluxes were used to examine the WUE of needle fir plantation in Korea National Arboretum. Our objective is to ascertain the seasonality and inter-annual variability in WUE of this needle fir plantation so that the results may be assimilated into the development of a holistic ecological indicator for resilience assessment. Our results show that the WUE of needle fir plantation is characterized by a concave seasonal pattern with a minimum ($1.8-3.3g\;C{\cdot}(kg\;H_2O)^{-1}$) in August and a maximum ($5.1-11.4g\;C{\cdot}(kg\;H_2O)^{-1}$) in February. During the growing season (April to October), WUE was on average $3.5{\pm}0.3g\;C\;(kg\;H_2O)^{-1}$. During the dormant seasons (November to March), WUE showed more variations with a mean of $7.4{\pm}1.0g\;C{\cdot}(kg\;H_2O)^{-1}$. These values are in the upper ranges of WUE reported in the literature for coniferous forests in temperate zone. Although the growing season was defined as the period from April to October, the actual length of the growing season (GSL) varied each year and its variation explained 62% of the inter-annual variability of the growing season WUE. This is the first study to quantify long-term changes in ecosystem-level WUE in Korea and the results can be used to test models, remote-sensing algorithms and resilience of forest ecosystem.

• Korean Journal of Remote Sensing
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• v.28 no.1
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• pp.145-157
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• 2012

In this study, we simulated a carbon flux model, so called Vegetation Integrated Simulator for Trace gases (VISIT) using Spatio-temporal Environmental Information, to estimate carbon budgets of vegetation ecosystem in South Korea. As results of the simulation, the model estimated that the annual-average gross primary production (GPP), net primary production (NPP) for 10 years were $91.89Tg\;C\;year^{-1}$, and $40.16Tg\;C\;year^{-1}$, respectively. The model also estimated the vegetation ecosystems in South Korea as a net carbon sink, with a value of $3.51Tg\;C\;year^{-1}$ during the simulation period. Comparing with the anthropogenic emission of South Korea, vegetation ecosystems offsets 3.3% of human emissions as a net carbon sink in 2007. To estimate the carbon budget more accurately, it is important to prepare reliable input datasets. And also, model parameters should be calibrated through comparing with various independent method. The result of this study, however, would be helpful for devising ecosystem management strategies that may help to mitigate global climate change.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.3
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• pp.233-245
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• 2014

Nighttime correction of $CO_2$ flux is one of the most important and challenging tasks in eddy covariance measurements over a complex mountainous terrain. In this study, we have scrutinized the quality and the credibility of the $CO_2$ flux datasets which were produced by employing three different methods of nighttime correction, i.e., (1) friction velocity ($u^*$) correction, (2) light response curve (LRC) correction, and (3) advection-based van Gorsel (VG) correction. The whole year datasets used in our analysis were collected at the two KoFlux tower sites (i.e., GDK deciduous forest site at the upper hill and GCK coniferous forest site at the lower hill) located in the valley of Gwangneung National Arboretum in central Korea. The resultant magnitudes and patterns of ecosystem respiration ($R_E$), gross primary productivity (GPP), and net ecosystem exchange (NEE) of $CO_2$ showed marked differences among the datasets produced with three different correction methods, which were also site-specific. The examination from micrometeorological and ecological perspectives suggests that the major cause of some inconsistency seems to be associated with the advection of $CO_2$ along the sloping terrain and the inappropriate selection of the correction data that might have been already affected by advective flows. The comparison with the results from other studies indicated that the overall characteristics of the corrected $CO_2$ fluxes at GDK and GCK (except those with LRC correction) were well within the ranges reported in the literature for various ecosystems in East Asia in similar latitudes. However, our study also implies that there will be always a room for further improvement in the present datasets. Therefore, caution must be exercised for the data users in order to properly use the updated version of datasets through transparent, open and participatory communication with data producers.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.99-99
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• 2022

Jeju island has a humid subtropical climate and this climate zone is expected to migrate northward toward the main land, Korea Peninsula, as temperature increases are accelerated. Vegetation type has been inevitably shifted along with the climatic change, having more subtropical species native in southeast Asia or even in Africa. With the forest composition shift, it becomes more important than ever to analyze the water balance of the forest wihth the ongoing as well as upcoming climate change. Here, we implemented the Ecosystem Demography Biosphere Model (ED2) by initializing the key variables using forest inventory data (diameter at breast height in 2012). Out of 10,000 parameter sets randomly generated from prior distribution distributions of each parameter (i.e., Monte-Carlo Method), we selected four behavioral parameter sets using remote-sensing data (LAI-MOD15A2H, GPP-MOD17A2H, and ET-MOD16A2, 8-days at 500-m during 2001-2005), and evaluated the performances using eddy-covariance carbon flux data (2012 Mar.-Sep. 30-min) and remote sensing data between 2006-2020. We simulated each of the four RCP scenarios (2.6, 4.5, 6.0, and 8.5) from four climate forcings (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, and MIROC5 from ISIMIP2b). Based on those 64 simulation sets, we estimate the changes in water balance resulting from the forest composition shift, and also uncertainty in the estimates and the sensitivity of the estimates to the parameters, climate forcings, and RCP scenarios.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1449-1463
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• 2020

As recent global warming and climate changes become more serious, the importance of CO2 absorption by forests is increasing to cope with the greenhouse gas issues. According to the UN Framework Convention on Climate Change, it is required to calculate national CO2 absorptions at the local level in a more scientific and rigorous manner. This paper presents the gridded expansion of forest flux observations and mapping of daily CO2 absorption by the forests in Korea using numerical weather prediction data and satellite images. To consider the sensitive daily changes of plant photosynthesis, we built a machine learning model to retrieve the daily RACA (reference amount of CO2 absorption) by referring to the climax forest in Gwangneung and adopted the NIFoS (National Institute of Forest Science) lookup table for the CO2 absorption by forest type and age to produce the daily AACA (actual amount of CO2 absorption) raster data with the spatial variation of the forests in Korea. In the experiment for the 1,095 days between Jan 1, 2013 and Dec 31, 2015, our RACA retrieval model showed high accuracy with a correlation coefficient of 0.948. To achieve the tier 3 daily statistics for AACA, long-term and detailed forest surveying should be combined with the model in the future.