• Journal of Korean Society on Water Environment
• /
• v.27 no.6
• /
• pp.830-840
• /
• 2011

Climate change has been settled as pending issues to consider water resources and environment all over the world, however, scientific and quantitative assessment methods of climate change have never been standardized. When South Korea headed toward water deficiency nation, the study is not only required analysis of atmospheric or hydrologic factors, but also demanded analysis of correlation with water quality environment factors to gain management policies about climate change. Therefore, this study explored appropriate monthly rainfall elasticity in chosen 41 unit watersheds in Nak-dong river which is the biggest river in Korea and applied monitored discharge data in 2004 to 2009 with monthly rainfall using Thiessen method. Each unit watershed drew elasticity between water temperature and water quality factors such as BOD, COD, SS, T-N, and T-P. Moreover, this study performed non-linear correlation analysis with monitored discharge data. Based on results of analysis, this is first steps of climate change analysis using long-term monitoring to develop basic data by Nak-dong river Environmental Research Center (Ministry of Environment) and to draw quantitative results for reliable forecasting. Secondary, the results considered characteristic of air temperature and rainfall in each unit watershed so that the study has significance its various statistical applications. Finally, this study stands for developing comparable data through "The 4 major river restoration" project by Korea government before and after which cause water quality and water environment changes.

• Journal of Korean Society for Atmospheric Environment
• /
• v.28 no.5
• /
• pp.581-594
• /
• 2012

The goal of this study is to investigate the effects of the chemical lateral boundary conditions (CLBCs) on Community Multi-scale Air Quality (CMAQ) simulations of tropospheric ozone for East Asia. We developed linking tool to produce CLBCs of CMAQ from Goddard Earth Observing System-Chemistry (GEOS-Chem) as a global chemistry model. We examined two CLBCs: the fixed CLBC in CMAQ (CLBC-CMAQ) and the CLBC from GEOS-Chem (CLBC-GEOS). The ozone fields by CMAQ simulation with these two CLBCs were compared to Tropospheric Emission Spectrometer (TES) satellite data, ozonesonde and surface measurements for May and August in 2008. The results with CLBC-GOES showed a better tropospheric ozone prediction than that with CLBC-CMAQ. The CLBC-GEOS simulation led to the increase in tropospheric ozone concentrations throughout the model domain, due to be influenced high ozone concentrations of upper troposphere and near inflow western and northern boundaries. Statistical evaluations also showed that the CLBC-GEOS case had better results of both the index of Agreement (IOA) and mean normalized bias. In the case of IOA, the CLBC-GEOS simulation was improved about 0.3 compared to CLBC-CMAQ due to the better predictions for high ozone concentrations in upper troposphere.

• Journal of Wetlands Research
• /
• v.17 no.4
• /
• pp.348-358
• /
• 2015

Impacts of climate change are being observed in the globe as well as the Korean peninsula. In the past 100 years, the average temperature of the earth rose about 0.75 degree in celsius, while that of Korean peninsula rose about 1.5 degree in celsius. The fifth Assessment Report of IPCC(Intergovermental Panel on Climate Change) predicts that the water pollution will be aggravated by change of hydrologic extremes such as floods and droughts and increase of water temperature (KMA and MOLIT, 2009). In this study, future runoff was calculated by applying climate change scenario to analyze the future water quality for each targe period (Obs : 2001 ~ 2010, Target I : 2011 ~ 2040, Target II : 2041 ~ 2070, Target III : 2071 ~ 2100) in Hongcheon river basin, Korea. In addition, The future water quality was analyzed by using multiple linear regression analysis and artificial neural networks after flow-duration curve analysis. As the results of future water quality prediction in Hongcheon river basin, we have known that BOD, COD and SS will be increased at the end of 21 century. Therefore, we need consider long-term water and water quality management planning and monitoring for the improvement of water quality in the future. For the prediction of more reliable future water quality, we may need consider various social factors with climate components.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.2 no.3
• /
• pp.60-70
• /
• 1999

The purpose of this study is to analyze the spatial change of water quality pollutant in the upper-stream of Kumho River basin. For this purpose, it compared with ground survey data of water quality measurement, using GIS and Landsat TM image, and then constructed a database of water quality pollutants in the watershed by Arc/Info. Also the land cover classification maps of 1985 and 1997 were prepared using maximum likelihood classification. This study detected and analysed the classified images to produce the area of land cover change per sub-basin. In addition, choropleth maps were prepared with spatial change value of water quality pollutants, and overlay analysis was carried out with weight score for each layer. The results of this study revealed that population, animals and fruit orchards were main factors in the spatial change of water pollution of Kumho River basin. The Comparision of pollutions by sub-basins showed a high pollution value in Daechang-chun and Omok -chun stream which follows through the urban area.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.12
• /
• pp.2505-2510
• /
• 2009

Semiconductor processes need measurement to confirm where there are problems in quality after progresses manufacturing process. This paper suggests equipment and automatic measure sampling method that control monitoring ratio according to change point occurrence availability of process that is not measure method by the existent simple ratio rate. This paper defines measure section as ailment section, metastable section and stability section by change point standard and create statistical model of each section and developed suitable measure rate model by section. As a result, we have accomplished maximum throughput and minimum sampling number that needs to maintain constant level of quality. Proposed method minimizes load of measure process by brings production quality sophistication and decrease of process badness and lowers measure rate in stable section making perception about problem occurrence quick heightening measure rate at change point occurrence.

• Human Ecology Research
• /
• v.58 no.1
• /
• pp.87-103
• /
• 2020

This study discusses the institutional change of Chinese early childhood education quality assurance institution (ECEQAI) from the three dimensions of the perspective of historical institutionalism of that refer to the external environment, dynamic mechanism containing with nation-market-society, and the invisible ideology of the institutional change. Chinese ECEQAI was divided into five historical periods, which were 17 years after the founding of China (1949-1966), the Great Cultural Revolution (GCR) period (1966-1976), the early stage of Reform and Opening-up (RO) (1976-1995), the social change period (1995-2010) and the new period (2010-now). This study also concludes five separate change models for Chinese ECEQAI that correspond to the five periods. The first was a compulsory and gradual institutional change model influenced by the Soviet model and dominated by national power. The second was compulsory and radical change model controlled by the counter-revolutionary group. The third was a compulsory and gradual institutional change model dominated by national power. The fourth was induced and gradual^① institutional change model driven by market power and forced by society power. The fifth was a compulsory and gradual institutional change model led by national power and forced by society power. Finally, the future change direction of China's ECEQAI was further pointed out, that was the government-leading and tend to balanced three-pole power model of "Nation-Market-Society", as well as the "three-pole power relationship" of indepth communication and positive interaction.

• Proceedings of the Korean Society for Quality Management Conference
• /
• 2006.04a
• /
• pp.319-324
• /
• 2006

In this paper, we propose Bayesian procedure for the multiple change points analysis in a sequence of fractions nonconforming. We first compute the Bayes factor for detecting the existence of no change, a single change or multiple changes. The Gibbs sampler with the Metropolis-Hastings subchain is run to estimate parameters of the change point model, once the number of change points is identified. Finally, we apply the results developed in this paper to both a real and simulated data.

• Journal of Environmental Science International
• /
• v.19 no.6
• /
• pp.771-778
• /
• 2010

The prediction of discharge is very important in water resources management and plan. In this study, we have analyzed discharge data of site at up and down stream in watershed. In order to forecast discharge the regression equations were developed by measuring flow data. Also, to forecast the change of water quality followed by change of inflow the correlation relationship between inflow of the Youngchun site and the Chunhju dam was shown as very high. The forecast of inflow at the Chungju dam would be possible through flow analysis of the Youngchun site. And, it is possible to forecast water quality by flow analysis because the correlation relationship of SS and turbidity followed by change of flow for each station of investigation was very high.

• Journal of Climate Change Research
• /
• v.7 no.4
• /
• pp.451-463
• /
• 2016

We explore the impact of Chinese future air pollutant emissions on ozone air quality in Northeast Asia (NEA) and health in South-Korea using an assessment framework including ICAMS (The Integrated Climate and Air Quality Modeling System) and BenMAP (The Environmental Benefits Mapping and Analysis Program). The emissions data sets from the climate change scenarios, the Representative Concentration Pathways (RCPs) (emission scenarios, EMSO), are used to simulate ozone air quality in NEA in the current (1996~2005, 2000s), the near future (2016~2025, 2020s) and the distant future (2046~2055, 2050s). Furthermore, the simulated ozone changes in the 2050s are used to analyze ozone-related premature mortality and economic cost in South-Korea. While different EMSOs are applied to the China region, fixed EMSO are used for other country regions to isolate the impacts of the Chinese emissions. Predicted ozone changes in NEA are distinctively affected by large changes in NOx emission over most of China region. Comparing the 2020s with the 2000s situation, the largest increase in mean ozone concentrations in NEA is simulated under RCP 8.5 and similarly small increases are under other RCPs. In the 2050s in NEA, the largest increase in mean ozone concentrations is simulated under RCP 6.0 and leads to the occurrence of the highest premature mortalities and economic costs in South-Korea. Whereas, the largest decrease is simulated under RCP 4.5 leads to the highest avoided premature mortality numbers and economic costs. Our results suggest that continuous reduction of NOx emissions across the China region under an assertive climate change mitigation scenario like RCP 4.5 leads to improved future ozone air quality and health benefits in the NEA countries including South-Korea.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2011.05a
• /
• pp.18-18
• /
• 2011

Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.