• Korean Journal of Agricultural and Forest Meteorology
• /
• v.15 no.4
• /
• pp.264-272
• /
• 2013

Climate changes have caused not only changes in the frequency and intensity of extreme climate events, but also temperature and precipitation. The damages on agricultural production system will be increased by heavy rainfall and snow. In this study we assessed vulnerability of crop cultivation facility and animal husbandry facility by heavy rain in 232 agricultural districts. The climate data of 2000 years were used for vulnerability analysis on present status and the data derived from A1B scenario were used for the assessment in the years of 2020, 2050 and 2100, respectively. Vulnerability of local districts was evaluated by three indices such as climate exposure, sensitivity and adaptive capacity, and each index was determined from selected alternative variables. Collected data were normalized and then multiplied by weight value that was elicited in delphi investigation. Jeonla-do and Gangwon-do showed higher climate exposures than the other provinces. The higher sensitivity to abnormal weather was observed from the regions that have large-scale cultivation facility complex compared to the other regions and vulnerability to abnormal weather also was higher at these provinces. In the projected estimation based on the SRES A1B, the vulnerability of controlled agricultural facility in Korea totally increased, especially was dramatic between 2000's and 2020 year.

• Journal of Korea Water Resources Association
• /
• v.46 no.12
• /
• pp.1235-1247
• /
• 2013

This study is to evaluate the climate change impact on future storage behavior of Chungju dam($2,750{\times}10^6m^3$) and the regulation dam($30{\times}10^6m^3$) using SWAT(Soil Water Assessment Tool) model. Using 9 years data (2002~2010), the SWAT was calibrated and validated for streamflow at three locations with 0.73 average Nash-Sutcliffe model Efficiency (NSE) and for two reservoir water levels with 0.86 NSE respectively. For future evaluation, the HadCM3 of GCMs (General Circulation Models) data by scenarios of SRES (Special Report on Emission Scenarios) A2 and B1 of the IPCC (Intergovernmental Panel on Climate Change) were adopted. The monthly temperature and precipitation data (2007~2099) were spatially corrected using 30 years (1977~2006, baseline period) of ground measured data through bias-correction, and temporally downscaled by Change Factor (CF) statistical method. For two periods; 2040s (2031~2050), 2080s (2071~2099), the future annual temperature were predicted to change $+0.9^{\circ}C$ in 2040s and $+4.0^{\circ}C$ in 2080s, and annual precipitation increased 9.6% in 2040s and 20.7% in 2080s respectively. The future watershed evapotranspiration increased up to 15.3% and the soil moisture decreased maximum 2.8% compared to baseline (2002~2010) condition. Under the future dam release condition of 9 years average (2002~2010) for each dam, the yearly dam inflow increased maximum 21.1% for most period except autumn. By the decrease of dam inflow in future autumn, the future dam storage could not recover to the full water level at the end of the year by the present dam release pattern. For the future flood and drought years, the temporal variation of dam storage became more unstable as it needs careful downward and upward management of dam storage respectively. Thus it is necessary to adjust the dam release pattern for climate change adaptation.

• Journal of Korea Water Resources Association
• /
• v.46 no.8
• /
• pp.833-842
• /
• 2013

The quantile mapping is utilized to reproduce reliable GCM(Global Climate Model) data by correct systematic biases included in the original data set. This scheme, in general, projects the Cumulative Distribution Function (CDF) of the underlying data set into the target CDF assuming that parameters of target distribution function is stationary. Therefore, the application of stationary quantile mapping for nonstationary long-term time series data of future precipitation scenario computed by GCM can show biased projection. In this research the Nonstationary Quantile Mapping (NSQM) scheme was suggested for bias correction of nonstationary long-term time series data. The proposed scheme uses the statistical parameters with nonstationary long-term trends. The Gamma distribution was assumed for the object and target probability distribution. As the climate change scenario, the 20C3M(baseline scenario) and SRES A2 scenario (projection scenario) of CGCM3.1/T63 model from CCCma (Canadian Centre for Climate modeling and analysis) were utilized. The precipitation data were collected from 10 rain gauge stations in the Han-river basin. In order to consider seasonal characteristics, the study was performed separately for the flood (June~October) and nonflood (November~May) seasons. The periods for baseline and projection scenario were set as 1973~2000 and 2011~2100, respectively. This study evaluated the performance of NSQM by experimenting various ways of setting parameters of target distribution. The projection scenarios were shown for 3 different periods of FF scenario (Foreseeable Future Scenario, 2011~2040 yr), MF scenario (Mid-term Future Scenario, 2041~2070 yr), LF scenario (Long-term Future Scenario, 2071~2100 yr). The trend test for the annual precipitation projection using NSQM shows 330.1 mm (25.2%), 564.5 mm (43.1%), and 634.3 mm (48.5%) increase for FF, MF, and LF scenarios, respectively. The application of stationary scheme shows overestimated projection for FF scenario and underestimated projection for LF scenario. This problem could be improved by applying nonstationary quantile mapping.

• Journal of Wetlands Research
• /
• v.8 no.4
• /
• pp.41-47
• /
• 2006

Global climatic changes are expected to influence various biogeochemical processes in wetland ecosystems. In particular, coastal mud flat is anticipated to be affected directly by temperature increase as well as indirectly by a sea level rise and changes in precipitation. This study aimed to determine changes in methane production under different temperature and salinity by employing a laboratory-scale manipulation experiment. Soil samples were collected from a mud flat in Dong-Gum Kang-Hwa island in winter and two types of experiments were conducted. In the first experiment soil samples at 0-5 cm, 5-10 cm depth were incubated under same salinity with pore water and diluted salinity to 50 % of natural condition for 20 days and methane production was measured every other days. In the second experiment, soil samples at 5-10 cm depth were incubated in different temperature, $5^{\circ}C$ and $15^{\circ}C$, under same salinity conditions with first experiment for 31 days and methane production was measured. Results of the first experiment revealed that higher amount of methane was produced at 5-10 cm depth, and salinity effect was predominant at the end of the experiment. The second experiment showed that methane production was higher in $15^{\circ}C$ than $5^{\circ}C$. In addition, methane production was higher when sea water diluted to 50 % compared to control. Global climatic changes are expected to influence various biogeochemical processes in wetland ecosystems. In particular, coastal mud flat is anticipated to be affected directly by temperature increase as well as indirectly by a sea level rise and changes in precipitation. This study aimed to determine changes in methane production under different temperature and salinity by employing a laboratory-scale manipulation experiment. Soil samples were collected from a mud flat in Dong-Gum Kang-Hwa island in winter and two types of experiments were conducted. In the first experiment soil samples at 0-5 cm, 5-10 cm depth were incubated under same salinity with pore water and diluted salinity to 50 % of natural condition for 20 days and methane production was measured every other days. In the second experiment, soil samples at 5-10 cm depth were incubated in different temperature, $5^{\circ}C$ and $15^{\circ}C$, under same salinity conditions with first experiment for 31 days and methane production was measured. Results of the first experiment revealed that higher amount of methane was produced at 5-10 cm depth, and salinity effect was predominant at the end of the experiment. The second experiment showed that methane production was higher in $15^{\circ}C$ than $5^{\circ}C$. In addition, methane production was higher when sea water diluted to 50 % compared to control. These results suggest that methane production is highly influenced by changes in temperature and salinity in coastal mud flat. And that global climatic change may induce biological feedback by affecting production of another greenhouse gas, namely methane from coastal mud flat.

• Journal of Wetlands Research
• /
• v.25 no.4
• /
• pp.353-365
• /
• 2023

The effects of climate change on green infrastructure and environmental media remain uncertain and context-specific despite numerous climate projections globally. In this study, the extreme weather conditions in seven major cities in South Korea were characterized through statistical analysis of 20-year daily meteorological data extracted fro m the Korea Meteorological Administration (KMA). Additionally, the impacts of extreme weather on Nature-based Solutions (NbS) were determined through a comprehensive review. The results of the statistical analysis and comprehensive review revealed the studied cities are potentially vulnerable to varying extreme weather conditions, depending on geographic location, surface imperviousness, and local weather patterns. Temperature extremes were seen as potential threats to the resilience of NbS in Seoul, as both the highest maximum and lowest minimum temperatures were observed in the mentioned city. Moreover, extreme values for precipitation and maximum wind speed were observed in cities from the southern part of South Korea, particularly Busan, Ulsan, and Jeju. It was also found that extremely low temperatures induce the most impact on the resilience of NbS and environmental media. Extremely cold conditions were identified to reduce the pollutant removal efficiency of biochar, sand, gravel, and woodchip, as well as the nutrient uptake capabilities of constructed wetlands (CWs). In response to the negative impacts of extreme weather on the effectiveness of NbS, several adaptation strategies, such as the addition of shading and insulation systems, were also identified in this study. The results of this study are seen as beneficial to improving the resilience of NbS in South Korea and other locations with similar climate characteristics.

• Korean Journal of Ecology and Environment
• /
• v.56 no.4
• /
• pp.281-302
• /
• 2023

Carbon is not only an essential element for life but also a key player in climate change. The radiocarbon (¹⁴C) analysis using accelerator mass spectrometry (AMS) is a powerful tool not only to understand the carbon cycle but also to track pollutants derived from fossil carbon, which have a distinct radiocarbon isotope ratio (Δ¹⁴C). Many studies have reported Δ¹⁴C of carbon compounds in streams, rivers, rain, snow, throughfall, fine particulate matter (PM_2.5), and wastewater treatment plant effluents in South Korea, which are reviewed in this manuscript. In summary, (1) stream and river carbon in South Korea are largely derived from the chemical weathering of soils and rocks, and organic compounds in plants and soils, strongly influenced by precipitation, wastewater treatment effluents, agricultural land use, soil water, and groundwater. (2) Unprecedentedly high Δ¹⁴C of precipitation during winter has been reported, which can directly and indirectly influence stream and river carbon. Although we cannot exclude the possibility of local contamination sources of high Δ¹⁴C, the results suggest that stream dissolved organic carbon could be older than previously thought, warranting future studies. (3) The ¹⁴C analysis has also been applied to quantify the sources of forest throughfall and PM_2.5, providing new insights. The ¹⁴C data on a variety of ecosystems will be valuable not only to track the pollutants derived from fossil carbon but also to improve our understanding of climate change and provide solutions.

• Atmosphere
• /
• v.24 no.3
• /
• pp.303-315
• /
• 2014

Terrestrial ecosystem plays the important role as carbon sink in the global carbon cycle. Understanding of interactions of terrestrial carbon cycle with climate is important for better prediction of future climate change. In this paper, terrestrial carbon cycle is investigated by Hadley Centre Global Environmental Model, version 2, Carbon Cycle (HadGEM2-CC) that considers vegetation dynamics and an interactive carbon cycle with climate. The simulation for future projection is based on the three (8.5/4.5/2.6) representative concentration pathways (RCPs) from 2006 to 2100 and compared with historical land carbon uptake from 1979 to 2005. Projected changes in ecological features such as production, respiration, net ecosystem exchange and climate condition show similar pattern in three RCPs, while the response amplitude in each RCPs are different. For all RCP scenarios, temperature and precipitation increase with rising of the atmospheric $CO_2$. Such climate conditions are favorable for vegetation growth and extension, causing future increase of terrestrial carbon uptakes in all RCPs. At the end of 21st century, the global average of gross and net primary productions and respiration increase in all RCPs and terrestrial ecosystem remains as carbon sink. This enhancement of land $CO_2$ uptake is attributed by the vegetated area expansion, increasing LAI, and early onset of growing season. After mid-21st century, temperature rising leads to excessive increase of soil respiration than net primary production and thus the terrestrial carbon uptake begins to fall since that time. Regionally the NEE average value of East-Asia ($90^{\circ}E-140^{\circ}E$, $20^{\circ}N{\sim}60^{\circ}N$) area is bigger than that of the same latitude band. In the end-$21^{st}$ the NEE mean values in East-Asia area are $-2.09PgC\;yr^{-1}$, $-1.12PgC\;yr^{-1}$, $-0.47PgC\;yr^{-1}$ and zonal mean NEEs of the same latitude region are $-1.12PgC\;yr^{-1}$, $-0.55PgC\;yr^{-1}$, $-0.17PgC\;yr^{-1}$ for RCP 8.5, 4.5, 2.6.