# GIS를 이용한 유역별 오염부하량 산정시스템의 개발

• Ham, Kwang-Jun (Gangwon Institute of Health & Environment) ;
• Kim, Joon-Hyun (Division of Geosystem and Environmental Eng. Kangwon National University) ;
• Shim, Jae-Min (Department of Geographic Education, Kangwon National University)
• 함광준 (원도보건환경연구원) ;
• 김준현 (강원대학교 지구.환경공학부) ;
• 심재민 (강원대학교 지리교육과)
• Accepted : 2005.04.29
• Published : 2005.06.30

#### Abstract

The purpose of this study is to develop a system, which estimates watershed pollutant loading rate through the combination of GIS and computational mode. Also, the applicability of this study was estimated by the application of the above system for Chuncheon City. The detailed results of these studies are as follows; The pollutant loading estimation system was developed for more convenient estimation of pollutant loading rate in watershed, and the system load was minimized by the separation of estimation module for point and non-point source. This system on the basis of GIS is very economical and efficient because it can be applied to other watershed with the watershed map. System modification is not needed. The pollutant loading estimation system for point source was developed to estimate the pollutant loading rate in watershed through the extraction of the proper data from all districts and yearly data and the execution of spatial analysis which is main function of GIS. From the verification result of spatial analysis, real watershed area and the administrative districtarea extracted by spatial analysis were $1,114,893,340.15m^2$ and $1,114,878,683.68m^2$, respectively. It shows that the spatial analysis results were very exact with only 0.001% error. The pollutant loading estimation system for non-point source was developed to calculate the pollutant loading rate through the overlaying of land-use and watershed map after the construction of new land-use map using the land register database with most exact land use classification. Application result for Chuncheon City shows that the proposed system results in one percent land use error while the statistical method results in five percent. More exact nonpoint source pollutant loading was estimated from this system.

#### References

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