• Proceedings of the Korea Water Resources Association Conference
• /
• 2018.05a
• /
• pp.151-151
• /
• 2018

The present study is aimed to quantifying the uncertainty in the general circulation model (GCM) selection and its impacts on hydrology studies in the basins. For this reason, 13 GCMs was selected among the 26 GCM models of the Fifth Assessment Report (AR5) scenarios. Then, the climate data and hydrologic data with two Representative Concentration Pathways (RCPs) of the best model (INMCM4) and worst model (HadGEM2-AO) were compared to understand the uncertainty associated with GCM models. In order to project the runoff, the Precipitation-Runoff Modelling System (PRMS) was driven to simulate daily river discharge by using daily precipitation, maximum and minimum temperature as inputs of this model. For simulating the discharge, the model has been calibrated and validated for daily data. Root mean square error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were applied as evaluation criteria. Then parameters of the model were applied for the periods 2011-2040, and 2070-2099 to project the future discharge the five large basins of South Korea. Then, uncertainty caused by projected temperature, precipitation and runoff changes were compared in seasonal and annual time scale for two future periods and RCPs compared to the reference period (1976-2005). The findings of this study indicated that more caution will be needed for selecting the GCMs and using the results of the climate change analysis.

• Atmosphere
• /
• v.18 no.4
• /
• pp.507-524
• /
• 2008

In this paper, future climate changes over East Asia($20^{\circ}{\sim}50^{\circ}N$, $100^{\circ}{\sim}150^{\circ}E$) are projected by anthropogenic forcing of greenhouse gases and aerosols using coupled atmosphere-ocean general circulation model (AOGCM) simulations based on Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) B1, A1B and A2 scenarios. Before projection future climate, model performance is assessed by the $20^{th}$ Century (20C3M) experiment with bias, root Mean Square Error (RMSE), ratio of standard deviation, Taylor diagram analysis. The result of examination of the seasonal uncertainty of T2m and PCP shows that cold bias, lowered than that of observation, of T2m and wet bias, larger than that of observation, of PCP are found over East Asia. The largest wet bias is found in winter and the largest cold bias is found in summer. The RMSE of temperature in the annual mean increases and this trend happens in winter, too. That is, higher resolution model shows generally better performances in simulation T2m and PCP. Based on IPCC SRES scenarios, East Asia will experience warmer and wetter climate in the coming $21^{st}$ century. It is predict the T2m increase in East Asia is larger than global mean temperature. As the latitude goes high, the warming over the continents of East Asia showed much more increase than that over the ocean. An enhanced land-sea contrast is proposed as a possible mechanism of the intensified Asian summer monsoon. But, the inter-model variability in PCP changes is large.

• Journal of Korean Society on Water Environment
• /
• v.32 no.2
• /
• pp.173-182
• /
• 2016

The objective of this study is to quantitatively analyze climate change effects by using statistical trends and a watershed model in the Yongdam dam watershed. The annual average air temperature was found to increase with statistical significance. In particular, greater increases were observed in autumn. Also, this study was performed to evaluate the potential climate change in the streamflow and water temperature using a watershed model (HSPF) with RCP climate change scenarios. The streamflow of Geum river showed a decrease of 5.1% and 0.2%, respectively, in the baseline data for the 2040s and 2080s. The seasonal impact of future climate change on the streamflow showed a decrease in the summer and an increase in the winter. The water temperature of Geum river showed an average increase of 0.7~1.0℃. Especially, the water temperature of Geum river showed an increase of 0.3~0.5℃ in the 2040s and 0.5~1.2℃ in the 2080s. The seasonal impact of future climate change on the water temperature showed an increase in winter and spring, with a decrease in summer. Therefore, it was determined that a statistical analysis-based meteorological and quantitative forecast of streamflow and water temperature using a watershed model is necessary to assess climate change impact and to establish plans for future water resource management.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2005.05b
• /
• pp.143-148
• /
• 2005

The main purpose of this study is to suggest and evaluate an operational method for assessing the potential impact of climate change on hydrologic components and water resources of regional scale river basins. The method, which uses large scale climate change information provided by a state of the art general circulation model(GCM) comprises a statistical downscaling approach and a spatially distributed hydrological model applied to a river basin located in Korea. First, we construct global climate change scenarios using the YONU GCM control run and transient experiments, then transform the YONU GCM grid-box predictions with coarse resolution of climate change into the site-specific values by statistical downscaling techniques. The values are used to modify the parameters of the stochastic weather generator model for the simulation of the site-specific daily weather time series. The weather series fed into a semi-distributed hydrological model called SLURP to simulate the streamflows associated with other water resources for the condition of $2CO_2$. This approach is applied to the Yongdam dam basin in southern part of Korea. The results show that under the condition of $2CO_2$, about $7.6\% of annual mean streamflow is reduced when it is compared with the observed one. And while Seasonal streamflows in the winter and autumn are increased, a streamflow in the summer is decreased. However, the seasonality of the simulated series is similar to the observed pattern and the analysis of the duration cure shows the mean of averaged low flow is increased while the averaged wet and normal flow are decreased for the climate change.

• Journal of Environmental Impact Assessment
• /
• v.4 no.3
• /
• pp.73-86
• /
• 1995

This paper demonstrates Environmental Impact Assessment (EIA) has to be applied for development projects with regard to the ecological, economical and social aspects before any decisions made in the project. Korea has confronted various environmental problems during the last fifteen years, even though EIA has been enacted since 1981. The role of impact assessment in planning and policy processes should be emphasized to investigate the magnitude and intensity of the adverse influences of economic development. In the Seoul Metropolitan Region, it is necessary to apply EIA all urban projects to reduce the adverse effects of urbanization. Special attention should be given to the climatological effects throughout the urbanization process in Korea to keep the urban area energy-efficient. This study intends not only to establish basic data for national-and regional-based land-use policy in the environmental aspects, but also to provide the basic data for the possible climate model (scenarios) that may provide spatial and temporal variability by analyzing the actual climatic record. There is a noticeable impact of urbanization on the atmospheric environment in the Seoul Metropolitan Region. In this sense, the climatic aspect must be taken into consideration in the process of EIA to mitigate the well-known climatic alterations of urbanization. Moreover, the techniques of assessment should be improved by developing geo-reference data sets to build models of the global climate in response to the man-made environmental change.

• Journal of Environmental Impact Assessment
• /
• v.19 no.2
• /
• pp.117-125
• /
• 2010

Korea's researchers have recently studied the prediction of forest change, but they have not considered landuse/cover change compared to distribution of forest vegetation. The purpose of our study is to predict forest vegetation based on landuse/cover change on the Korean Peninsula in the 2090's. The methods of this study were Multi-layer perceptrom neural network for Landuse/cover (water, urban, barren, wetland, grass, forest, agriculture) change and Multinomial Logit Model for distribution prediction for forest vegetation (Pinus densiflora, Quercus Spp., Alpine Plants, Evergreen Broad-Leaved Plants). The classification accuracy of landuse/cover change on the Korean Peninsula was 71.3%. Urban areas expanded with large cities as the central, but forest and agriculture area contracted by 6%. The distribution model of forest vegetation has 63.6% prediction accuracy. Pinus densiflora and evergreen broad-leaved plants increased but Quercus Spp. and alpine plants decreased from the model. Finally, the results of forest vegetation based on landuse/cover change increased Pinus densiflora to 38.9% and evergreen broad-leaved plants to 70% when it is compared to the current climate. But Quercus Spp. decreased 10.2% and alpine plants disappeared almost completely for most of the Korean Peninsula. These results were difficult to make a distinction between the increase of Pinus densiflora and the decrease of Quercus Spp. because of they both inhabit a similar environment on the Korean Peninsula.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.59 no.6
• /
• pp.9-18
• /
• 2017

The objective of this study was to estimate the climate change impact on inflow to Namgang Dam using SWAT (Soil and Water Assessment Tool) model. The SWAT model was calibrated and validated using observed flow data from 2003 to 2014 for the study watershed. The $R^2$ (Determination Coefficient), RMSE (Root Mean Square Error), NSE (Nash-Sutcliffe efficiency coefficient), and RMAE (Relative Mean Absolute Error) were used to evaluate the model performance. Calibration results showed that the annual mean inflow were within ${\pm}5%$ error compared to the observed. $R^2$ were ranged 0.61~0.87, RMSE were 1.37~7.00 mm/day, NSE were 0.47~0.83, and RMAE were 0.25~0.73 mm/day for daily runoff, respectively. Climate change scenarios were obtained from the HadGEM3-RA. The quantile mapping method was adopted to correct bias that is inherent in the climate change scenarios. Based on the climate change scenarios, calibrated SWAT model simulates the future inflow and evapotranspiration for the study watershed. The expected future inflow to Namgang dam using RCP 4.5 is increasing by 4.8 % and RCP 8.5 is increasing by 19.0 %, respectively. The expected future evapotranspiration for Namgang dam watershed using RCP 4.5 is decreasing by 6.7 % and RCP 8.5 is decreasing by 0.7 %, respectively.

• Journal of Climate Change Research
• /
• v.9 no.1
• /
• pp.1-12
• /
• 2018

There is an emphasis on the importance of adaptation against to climate change and related natural disasters. As a result, various climate information with different time-scale can be used for science-based climate change adaptation policy. From the aspects of Global Framework for Climate Services (GFCS), various time-scaled climate information in Korea is mainly produced by Korea Meteorological Administration (KMA) However, application of weather and climate information in different application sectors has been done individually in the fields of agriculture and water resources mostly based-on weather information. Furthermore, utilization of climate information including seasonal forecast and climate change projections are insufficient. Therefore, establishment of the Cooperation Center for Application of Weather and Climate Information is necessary as an institutional platform for the UIP (User Interface Platform) focusing on multi-model ensemble (MME) based climate service, seamless climate service, and climate service based on multidisciplinary approach. In addition, APCC Integrated Modeling Solution (AIMS) was developed as a technical platform for UIP focusing on user-centered downscaling of various time-scaled climate information, application of downscaled data into impact assessment modeling in various sectors, and finally producing information can be used in decision making procedures. AIMS is expected to be helpful for the increase of adaptation capacity against climate change in developing countries and Korea through the voluntary participation of producer and user groups within in the institutional and technical platform suggested.

• Atmosphere
• /
• v.18 no.1
• /
• pp.33-41
• /
• 2008

This study provides an impact assesment of climate change on energy consumption, based on active-deal scenario. This approach assumes that the amount of electric energy consumption depends on human spontaneous acts against local (REC) has ben developed by using monthly mean temperature and monthly amount of electric energy consumption in the 6 major cities over the 19-205 period. The statistical model is utilized to estimate the past and future REEC, and to assess the economic benefits and damage in energy consumption sector. For an estimation of the future REEC, climate change scenario, which is generated by National Institute of Meteorological Research, is utilized in this study. According to the model, it is estimated that over the standard period (1999~2005), there might be economic benefits of about 31 bilion Won/year in Seoul due to increasing temperature than in the 1980s. The REC is also predicted to be gradually reduced across the Korean peninsula since the 2020s. These results suggest that Korea will gain economic benefits in the REC sector during the 21st century as temperature increases under global warming scenarios.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.18 no.3
• /
• pp.170-178
• /
• 2016

It is not clear how to apply the climate scenario to assess the impact of climate change in the agricultural sector. Even if you apply the same scenario, the result can vary depending on the temporal-spatial downscaling, the post-treatment to adjust the bias of a model, and the prediction model selection (used for an impact assessment). The end user, who uses the scenario climate data, should select climate factors, a spatial extend, and a temporal range appropriate for the objectives of an analysis. It is important to draw the impact assessment results with minimum uncertainty by evaluating the suitability of the data including the reproducibility of the past climate and calculating the optimum future climate change scenario. This study introduced data processing methods for reducing the uncertainties in the process of applying the future climate change scenario to users in the agricultural sector and tried to provide basic information for appropriately using the scenario data in accordance with the study objectives.