基于无线传感器网络与GIS的蓝藻水华爆发动态监测与模拟  

Dynamic monitoring and simulation of Cyanobacteria Bloom based on wireless sensor network and GIS

作　　者：杨昆[1,2] 罗毅[1,2,3] 徐玉妃 商春雪 杨扬[1,2] Yang Kun Luo Yi Xu Yufei Shang Chunxue Yang Yang(School of Information Science and Technology, Yunnan Normal University, Kunming 650500, China The Engineering Research Center of GIS Technology in Western China, Ministry of Education, Kunming 650500, China School of Tourism and Geographical Science, Kunming 650500, China Dean＇s Office, Yunnan Normal University, Kunming 650500, China)

机构地区：[1]云南师范大学信息学院,昆明650500 [2]西部资源环境地理信息技术教育部工程研究中心,昆明650500 [3]云南师范大学旅游与地理科学学院,昆明650500 [4]云南师范大学教务处,昆明650500

出　　处：《农业工程学报》2016年第24期197-205,共9页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家863计划(2012AA121402);教育部博士点专项基金(20115303110002);云南省自然科学基金青年项目(2016FD020);云南师范大学博士科研启动项目(01000205020503066)

摘　　要：准确获取水体中物质含量与分布区域是开展蓝藻水华爆发预防、预测、预警工作的基础。针对内陆湖泊蓝藻水华爆发突发性、随机性、区域性等特点,研究了一种基于无线传感器网络（wireless sensors networks,WSNs）及地理信息系统（Geographic Information System,GIS）相结合的蓝藻水华爆发动态监测与模拟方法。利用水质传感器组成多源异构水环境感知单元,获取湖泊水质数据;将改进的灰色理论（A Grey Model,AGM）及BP人工神经网络（BP Artificial Neural Network,BPANN）相结合,从而预测24 h内蓝藻水华的浓度与趋势;结合GIS强大的空间分析能力,实现蓝藻水华变化的空间描述。滇池现场试验结果表明,该方法具有一定的普适性,能够为湖泊环境保护与治理提供理论依据及数据支持。Because of the fast development of Chinese urbanization,the intense growth of mankind activities,and the global warming,the inland lake pollution problems have become more serious and complex,the inland lakes are becoming more eutrophic,suffering from both point and non-point pollutions,and exposing to both endogenous and exogenous pollutions,and the deterioration of water quality has severely hindered sustainable social and economic development of nearby cities.Eutrophication is not just the result of natural process,but the aggregated result of the interaction and mutual influences between natural process and human process.As the ＂eyes＂ of water protection and management,water quality monitoring is the premise for the forecast of cyanobacteria outbreak and the assessment of bloom intensity.As technology advances,the monitoring tools and measuring indicators become increasingly diverse.In the meantime,the measurement accuracy is also constantly improving.In the domain of water quality monitoring,the combination of position sensors and wireless sensor networks makes the observations with high density,high precision and continuity possible.In addition,such methods can simultaneously collect both water quality data and surrounding environmental data,which can be used to simulate the interaction between the internal and external factors of water pollution as well as the mechanism of pollution process.The cyanobacteria bloom of inland lake has the characteristics of suddenness,randomness,and regionalism,the paper proposed a cyanobacteria bloom dynamic monitoring and spatial-temporal process simulation method based on wireless sensor networks（WSNs） and geographic information system（GIS）.Firstly,multi-parameter sensor array is designed using water quality sensors in order to acquire real-time water quality data,and the monitoring node is composed of 4-layer architecture,including monitoring layer,data storage layer,model layer,and application layer; secondly,the improved grey model and back propagation（BP

关 键 词：污染 无线传感器网络 地理信息系统 灰色理论 人工神经网络 

分 类 号：TH89[机械工程—仪器科学与技术]