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Assessment of water quality monitoring for the optimal sensor placement in lake Yahuarcocha using pattern recognition techniques and geographical information systems

机译:使用模式识别技术和地理信息系统评估在Yahuarcocha湖中最佳传感器位置的水质监测

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摘要

Pollution and the eutrophication process are increasing in lake Yahuarcocha and constant water quality monitoring is essential for a better understanding of the patterns occurring in this ecosystem. In this study, key sensor locations were determined using spatial and temporal analyses combined with geographical information systems (GIS) to assess the influence of weather features, anthropogenic activities, and other non-point pollution sources. A water quality monitoring network was established to obtain data on 14 physicochemical and microbiological parameters at each of seven sample sites over a period of 13 months. A spatial and temporal statistical approach using pattern recognition techniques, such as cluster analysis (CA) and discriminant analysis (DA), was employed to classify and identify the most important water quality parameters in the lake. The original monitoring network was reduced to four optimal sensor locations based on a fuzzy overlay of the interpolations of concentration variations of the most important parameters.
机译:Yahuarcocha湖的污染和富营养化过程正在增加,不断进行水质监测对于更好地了解该生态系统中发生的模式至关重要。在这项研究中,关键的传感器位置是使用时空分析结合地理信息系统(GIS)来确定的,以评估天气特征,人为活动和其他非点源污染的影响。建立了水质监测网络,以在13个月内获得七个采样点中每个站点的14个理化和微生物参数的数据。使用模式识别技术(例如聚类分析(CA)和判别分析(DA))的时空统计方法来分类和识别湖泊中最重要的水质参数。基于最重要参数浓度变化的内插值的模糊叠加,原始监控网络减少到四个最佳传感器位置。

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