流域复合系统协调度预警研究:以河南省淮河流域为例  

Early Warning Research on Complex System Coordination Degree of Basin:Taking Huaihe River Basin in Henan as An Example

作　　者：于鲁冀[1,2] 王小青[1] 梁亦欣[2] 章显[2] 梁静[1] 贾佳[1] 

机构地区：[1]郑州大学水利与环境学院 [2]郑州大学环境政策规划评价研究中心,河南郑州450002

出　　处：《环境科学与技术》2014年第9期168-173,共6页Environmental Science & Technology

基　　金：河南省软科学研究计划项目(122400430118)

摘　　要：流域是由社会、经济、水资源和水环境4个子系统组成的复合生态系统,其协调发展关系到流域未来的长远发展,因此是流域需要重点关注的问题。淮河流域作为河南省四大流域中最大的水系,其协调发展受到多方面因素的约束,文章以此为例进行协调度预警研究具有一定的代表性和现实意义。首先建立流域复合系统协调度预警模型,通过从社会子系统、经济子系统、资源子系统和环境子系统4个指标类别构建流域复合系统协调发展预警指标体系,采用BP神经网络模型,对流域内9的地市和流域整体共10个地区未来10年的协调度进行预测,并根据预警等级划分标准得到对预测结果进行预警。其次从时间和空间尺度分析协调度预警结果,结果表明:流域未来10年整体发展状况始终保持良好,但流域内各地市协调发展状况参差不齐,应特别重视开封、周口和商丘地区协调发展状况,及时采取有效措施进行调整和引导。Watershed is a complex system which is composed of social, economic, resource and environmental subsystems. Its coordinated development is related to long-term development of watershed. Huaihe River Basin is the largest river of four basins in Henan Province, and its coordinated development is constrained by many factors, so it is representative and practical to take it as an example. Early warning model is established, building early warning index system on coordinated development of complex system in basin, which includes social, economic, resource and environmental subsystems and adopting BP neural network model, coordinated degree of ten regions including nine cities and watershed overall is predicted and prediction results are warned according to warning grading standards. Then, analyzing early warning results from time and space perspectives. Results show that basin overall has always maintained good development. However, watershed development is uneven among cities, Cities such as Kaifeng, Zhoukou and Shangqiu should be paid special attention and effective measures should be taken for adjustment and guidance.

关 键 词：流域 协调度 BP神经网络 预警 

分 类 号：X196[环境科学与工程—环境科学]