Identify The Water Quality Of Liao River And Study Of Information System Using The Neural Networks Evaluation And ArcGIS Engine Approaches

Northeast region that covering the provinces of Heilongjiang, Jinlin and Liaoning has numerous achievements in the history of China's industrial development, Northeast region was the "industrial cradle of China" and played a major role in the industrial development. However, the traditional economic development model with the exploitation of natural resources-oriented industries and the extensive production process, led to the severe environmental problems.Taking national basic research development plan (973 project)—"the environment pollution formation and ecological rehabilitation research of northeast region "as research foundation of water environment quality. Analysed the data of pollution of Liao river basin in the year of 1990-2006 and based on the platform of ArcGIS Engine, design the pollution information system of Liao river basin. Through the collection and processing of different categories of spatial data of Liao river basin to storage and manage in the framework of ArcGIS. With the classification of original data of different pollutants of each section in Liao river basin to storage in attribute database. Through the modules of different functional, accomplish the managing of spatial information and pollutant data. Operator can use different types of spatial data to display of result of superposition analysis. Thus, research content and research scope can be easily located by management personnel. Through the operate of query of the spatial data and edit of data, people can accurately understand the information and quality changes of specific section and made the pollution data updates timely. Based on the operation of database of Liao river basin, policymakers can made decision more effectively through the massive data of pollution.Application of the principle of BP neural network model, this paper presented a studying to access water quality condition. Thirteen indices were comprehensively considered of water quality within 19 monitoring sites during the year of 1990-2006. The finding clearly indicated that the technique could be successfully used to interpret the water quality condition. With the support of GIS and the BP neural network model, analysed the characteristics of water pollution trends in Liao river basin from the industrial structure. The results showed that water quality of the Liao river basin was improving. The results also showed that the quality of Liao river varied in different hydrologichal periods.