• Journal of Korea Water Resources Association
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• v.49 no.2
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• pp.107-119
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• 2016

Since future climate scenarios indicate that extreme precipitation events will intensity, probable maximum precipitations (PMPs) without being taken climate change into account are very likely to be underestimated. In this study future PMPs in accordance with the variation of future rainfall are estimated. The hydro-meteorologic method is used to calculate PMPs. The orographic transposition factor is applied in place of the conventional terrain impact factor which has been used in previous PMPs estimation reports. Future DADs are indirectly obtained by using bias-correction and moving-averaged changing factor method based on daily precipitation projection under KMA RCM (HEDGEM3-RA) RCP 8.5 climate change scenario. As a result, future PMPs were found to increase and the spatially-averaged annual PMPs increase rate in 4-hour and $25km^2$ was projected to be 3 mm by 2045. In addition, the increased rate of future PMPs is growing increasingly in the future, but it is thought that the uncertainty of estimating PMPs caused by future precipitation projections is also increased in the distant future.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.83-96
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• 2018

The objective of this study was to estimate the climate change impact on water quantity and quality to Saemanguem watershed using SWAT (Soil and water assessment tool) model. The SWAT model was calibrated and validated using observed data from 2008 to 2017 for the study watershed. The $R^2$ (Determination coefficient), RMSE (Root mean square error), and NSE (Nash-sutcliffe efficiency coefficient) were used to evaluate the model performance. RCP scenario data were produced from 10 GCM (General circulation model) and all relevant grid data including the major observation points (Gusan, Jeonju, Buan, Jeongeup) were extracted. The systematic error evaluation of the GCM model outputs was performed as well. They showed various variations based on analysis of future climate change effects. In future periods, the MIROC5 model showed the maximum values and the CMCC-CM model presented the minimum values in the climate data. Increasing rainfall amount was from 180mm to 250mm and increasing temperature value ranged from 1.7 to $5.9^{\circ}C$, respectively, compared with the baseline (2006~2017) in 10 GCM model outputs. The future 2030s and 2070s runoff showed increasing rate of 16~29% under future climate data. The future rate of change for T-N (Total nitrogen) and T-P (Total phosphorus) loads presented from -26 to +0.13% and from +5 to 47%, respectively. The hydrologic cycle and water quality from the Saemanguem headwater were very sensitive to projected climate change scenarios so that GCM model should be carefully selected for the purpose of use and the tendency analysis of GCM model are needed if necessary.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.1
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• pp.39-51
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• 2016

Extreme floods occur more often recently as the frequency of extreme storm events increase due to the climate change. Because the extreme flood exceeding the design flood can cause large-scale disasters, it is important to predict and prepare for the future extreme flood. Flood flow is affected by two main factors; rainfall and land use. To predict the future extreme flood, both changes in rainfall due to the climate change and land use should be considered. The objective of this study was to simulate the future design flood in the Hwangguji river watershed, South Korea. The climate and land use change scenarios were derived from the representative concentration pathways (RCP) 4.5 and 8.5 scenarios. Conversion of land use and its effects (CLUE) and hydrologic modelling system (HEC-HMS) models were used to simulate the land use change and design flood, respectively. Design floods of 100-year and 200-year for 2040, 2070, and 2100 under the RCP4.5 and 8.5 scenarios were calculated and analyzed. The land use change simulation described that the urban area would increase, while forest would decrease from 2010 to 2100 for both the RCP4.5 and 8.5 scenarios. The overall changes in design floods from 2010 to 2100 were similar to those of probable rainfalls. However, the impact of land use change on design flood was negligible because the increase rate of probable rainfall was much larger than that of curve number (CN) and impervious area.

• Journal of Wetlands Research
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• v.24 no.1
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• pp.25-37
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• 2022

Climate change is becoming increasingly unpredictable. This has led to changes in various systems such as ecosystems, human life and hydrological cycles. In particular, the recent unpredictable climate change frequently causes extreme droughts and torrential rains, resulting in complex water resources disasters that cause water pollution due to inundation and retirement rather than primary disasters. SWAT was used as a watershed model to analyze future runoff and pollutant loads. The climate scenario analyzed the RCP4.5 climate scenario of the Meteorological Agency standard scenario (HadGEM3-RA) using the normal quantitative mapping method. Runoff and pollutant load analysis were performed by linkage simulation of climate scenario and watershed model. Finally, the results of application and verification of linkage model and analysis of future water quality change due to climate change were presented. In this study, we simulated climate change scenarios using artificial neural networks, analyzed changes in water temperature and turbidity, and compared the results of dams with artificial neural network results through W2 model, a reservoir water quality model. The results of this study suggest the possibility of applying the nonlinearity and simplicity of neural network model to Hapcheon dam water quality prediction using climate change.

• Journal of Animal Environmental Science
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• v.20 no.2
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• pp.49-56
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• 2014

The climate of the earth is expected to change rapidly and continuously. Despite climate change is expected to impact on productivity of crop and livestock, a study for adaptation and impact of livestock to global warming is not enough. This study was performed to develop a method to evaluate the effects of heat stress on dairy cattle. Feedlot environment and health status of livestock were measured through an infrared thermography camera and a temperature-humidity sensor. Environmental factors such as temperature and humidity were measured to calculate the Temperature humidity index (THI). The change of the milk yield was similar to THI data pattern, suggesting that THI might play an important role to predict the effect of climate change on dairy cattle. THI data would be useful to predict long-term climate change effects on dairy cattle with RCP8.5 scenario.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.4
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• pp.275-280
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• 2015

In order to figure out the future drought characteristics of the Jeonju plains, the major crop production area in Korea, daily agricultural drought indexes based on soil water balance were calculated for the relevant 12.5 km by 12.5 km grid cell using the weather data generated by the RCP8.5 climate scenario during 1951-2100. The calculations were grouped into five climatological normal years, the past (1951-1980), the present (1981-2010), and the three futures (2011-2040, 2041-2070, and 2071-2100). Results showed that the soil moisture conditions in early spring, worst for both the past and present normal years, will ameliorate gradually in the future and the crop water stress in spring season was projected to become negligible by the end of this century. Furthermore, the drought frequency in early spring was projected to diminish, resulting in rare occurrence of spring drought by that time. However, the result also showed that the soil moisture conditions during the summer season (when most crops grow in Jeonju plain) will deteriorate and the drought incidence will be more frequent than in the past or present period.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.1
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• pp.31-43
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• 2017

Recent studies about irrigation water use have focused on agricultural reservoir operation in irrigation period. At the same time, it is significant to store water resource in reservoir during non-irrigation period in order to secure sufficient water in early growing season. In this study, Representative Concentration Pathways (RCP) 4.5, 8.5 scenarios with the Global Climate Model (GCM) of The Second Generation Earth System Model (CanESM2) were downscaled with bias correlation method. Cumulative precipitation during non-irrigation season, October to March, was analyzed. Interaction between cumulative precipitation and carry-over storage was analyzed with linear regression model for ten study reservoirs. Using the regression model, reservoir drought response ability was evaluated with expression of excess and deficiency. The results showed that future droughts will be more severe than past droughts. Especially in case of non-exceedance probability of 10%, drought in southern region seemed to be serious. Nine study reservoirs showed deficiency range from 10% to 55%, which turned out to be vulnerable for future drought. Only Jang-Chan reservoir was secure for early growing season in spite of drought with deficiency of 8% and -2%. The results of this study represents current agricultural reservoirs have vulnerability for the upcoming drought.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2015.08a
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• pp.146-150
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• 2015

• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.1
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• pp.1-8
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• 2013

In this paper, we predicted sea-level rise for RCP 4scenarios(RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5). To calculate sea-level rise, a semi-empirical method was used and it needs atmospheric temperature rise for each scenario. According to the results, the sea-level has been rising steadily in all scenarios. By 2050 the maximum difference of sea-level rise between the scenarios was within 0.08 m, but its difference was showed more than 0.5 m in 2100. The values of sea-level rise for RCP 2.6, RCP 4.5, RCP 6.0, RCP 8.5 scenarios are 0.87 m, 1.21 m, 1.02 m, 1.36 m, respectively. In the case of RCP 8.5, the slope of atmospheric temperature rise since 2060 was very steep compared to the other scenarios so that the maximum difference of sea-level rise between the scenarios will be much larger after 2100. Estimated by a simple approximation, the maximum difference of sea-level rise can be more than 1.2 m in 2120.

• Journal of Climate Change Research
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• v.9 no.1
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• pp.13-29
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• 2018

This study presented evaluation procedure for selecting appropriate GCMs and downscaling method by focusing on the climate extreme indices suitable for climate change adaptation. The procedure includes six stages of processes as follows: 1) exclusion of unsuitable GCM through raw GCM analysis before bias correction; 2) calculation of the climate extreme indices and selection of downscaling method by evaluating reproducibility for the past and distortion rate for the future period; 3) selection of downscaling method based on evaluation of reproducibility of spatial correlation among weather stations; and 4) MME calculation using weight factors and evaluation of uncertainty range depending on number of GCMs. The presented procedure was applied to 60 weather stations where there are observed data for the past 30 year period on Korea Peninsula. First, 22 GCMs were selected through the evaluation of the spatio-temporal reproducibility of 29 GCMs. Between Simple Quantile Mapping (SQM) and Spatial Disaggregation Quantile Delta Mapping (SDQDM) methods, SQM was selected based on the reproducibility of 27 climate extreme indices for the past and reproducibility evaluation of spatial correlation in precipitation and temperature. Total precipitation (prcptot) and annual 1-day maximum precipitation (rx1day), which is respectively related to water supply and floods, were selected and MME-based future projections were estimated for near-future (2010-2039), the mid-future (2040-2069), and the far-future (2070-2099) based on the weight factors by GCM. The prcptot and rx1day increased as time goes farther from the near-future to the far-future and RCP 8.5 showed a higher rate of increase in both indices compared to RCP 4.5 scenario. It was also found that use of 20 GCM out of 22 explains 80% of the overall variation in all combinations of RCP scenarios and future periods. The result of this study is an example of an application in Korea Peninsula and APCC Integrated Modeling Solution (AIMS) can be utilized in various areas and fields if users want to apply the proposed procedure directly to a target area.