2009, Vol.18, No.5

Journal of Environmental Impact Assessment 2023 KCI Impact Factor : 0.51

pISSN : 1225-7184
https://journal.kci.go.kr/kseia

The central government in Korea has pursued a policy to privatize municipal solid waste treatment facilities in order to enhance the effectiveness of public financial management in recent years. To understand the intentions of local governments on this policy, the survey with questionnaires on 37 out of 256 local governments was made in October, 2007. The results were analyzed and compared in 6 classified policy areas. The results showed that local government had enough financial status to operate the facilities with proper services and had the opinion with positive management in finance with increasing rate of prospective views. Among the facilities operated by local governments, the satisfaction levels for landfill(46.2%) and incineration(40.0%) were relatively higher. However those for recycling and food waste resource facilities were not satisfied with showing lower rate of satisfaction. The priority of privatization in consideration among them were following in order of food waste resource plants(76.2%), incinerators(63.6%), and recycling facilities(53.9%) and the most considerable reason to privatize them was due to resolve financial problems(59.7%). They thought and expected that the privatization would provide cost reduction effects in local governments and also be easier to achieve the environmental goals. To enhance such privatization, expanding more incentives by central government would be essential as shown in the investigation of this survey.

The objective of this study is to develop a reliable flow forecasting model based on neural network algorithm in order to provide flow rate at stream sections without flow measurement in Nakdong river. Stream flow rate measured at 8-days interval by Nakdong river environment research center, daily upper dam discharge and precipitation data connecting upstream stage gauge were used in this development. Back propagation neural network and multi-layer with hidden layer that exists between input and output layer are used in model learning and constructing, respectively. Model calibration and verification is conducted based on observed data from 3 station in Nakdong river.

In Total Water Pollutant Load Management System of Korea, unit load approach based on land register data is currently used for the estimation of non-point pollutant load. However, a problem raised that land register data could not always reflect the actual land surface coverages which determine runoff characteristics of non-point pollution sources. As a way to overcome this, we tried to establish quantitative relationships between the aerial images (0.4m resolution) which reflect actual land surface coverages and the land registration maps according to the 19 major designated land-use categories in Kyeongan watershed. Analyses showed different relationships according to the land-use categories. Only a few land-use categories including forestry, road and river showed essentially identical and some categories such as orchard, parking lot and sport utility site showed no relationships at all between image data and land register data. Except for the two cases, all the other categories showed statistically significant linear relationships between image data and land register data. The analyses indicate that using high resolution aerial maps is a better way to estimate non-point pollutant load. If the aerial maps are not available, application of the linear relationships as conversion factors of land register data to image data could be an possible option to estimate non-point pollutant loads for the specific land-use categories in Kyeongan watershed.