Multi-Parameter Analysis of Groundwater Resources Quality in the Auvergne-Rhône-Alpes Region (France) Using a Large Database

IF 3.6 Q2 ENVIRONMENTAL SCIENCES
Meryem Ayach, Hajar Lazar, Abderrahim Bousouis, Abdessamad Touiouine, I. Kacimi, Vincent Valles, L. Barbiero
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引用次数: 0

Abstract

The aim of this work is to gain a better understanding of the diversity of groundwater resource quality in the Auvergne-Rhône-Alpes region (France) using the national Sise-Eaux database. Three matrices were extracted, which included a hollow matrix (approximately 120,000 observations and 21 variables) and two complete matrices (8078 observations with 13 variables each and 150 observations with 20 variables each, respectively). The mapping of these parameters, the chemical profiles of the water, and the characteristics of the variograms make it possible to estimate the importance of the temporal variance compared with the spatial variance. This distinction led to a typology separating 4 groups of chemical parameters and 2 groups of bacteriological parameters, highlighting the information redundancies linking several parameters. A PCA was used to considerably reduce the size of the hyperspace of the data. The study of the factorial axes combined with their distribution over the study area made it possible to discriminate and identify certain mechanisms for acquiring the physico-chemical and bacteriological characteristics of groundwater, the importance of lithology, the components of faecal contamination, and the role of environmental conditions. A typology of the parameters by hierarchical clustering on the major part of the information makes it possible to reduce the information to that carried by a few representative parameters. This work is a new step in understanding the diversity of groundwater resources in general, with a view to more targeted monitoring based on this diversity.
利用大型数据库对奥弗涅-罗纳-阿尔卑斯大区(法国)的地下水资源质量进行多参数分析
这项工作的目的是利用国家Sise-Eaux数据库,更好地了解Auvergne-Rhône-Alpes地区(法国)地下水资源质量的多样性。提取了3个矩阵,其中包括一个中空矩阵(约120,000个观测值和21个变量)和两个完整矩阵(8078个观测值,每个观测值13个变量和150个观测值,每个观测值20个变量)。这些参数的映射,水的化学剖面,以及变异函数的特征,使得与空间变异相比,估计时间变异的重要性成为可能。这种区分导致了一种分4组化学参数和2组细菌参数的类型学,突出了连接几个参数的信息冗余。采用主成分分析大大减小了数据的超空间大小。对因子轴的研究结合它们在研究区域的分布,可以区分和确定某些机制,以获得地下水的物理化学和细菌特性、岩性的重要性、粪便污染的组成和环境条件的作用。通过对信息的主要部分进行分层聚类的参数类型学,可以将信息减少到由几个代表性参数携带的信息。这项工作是了解地下水资源总体多样性的新一步,目的是基于这种多样性进行更有针对性的监测。
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来源期刊
Resources
Resources Environmental Science-Nature and Landscape Conservation
CiteScore
7.20
自引率
6.10%
发文量
0
审稿时长
11 weeks
期刊介绍: Resources (ISSN 2079-9276) is an international, scholarly open access journal on the topic of natural resources. It publishes reviews, regular research papers, communications and short notes, and there is no restriction on the length of the papers. Our aim is to encourage scientists to publish their experimental and theoretical research in as much detail as possible. Full experimental and methodical details must be provided so that the results can be reproduced. There are, in addition, unique features of this journal: manuscripts regarding research proposals and research ideas will be particularly welcomed, electronic files or software regarding the full details of the calculation and experimental procedure, if unable to be published in a normal way, can be deposited as supplementary material. Subject Areas: natural resources, water resources, mineral resources, energy resources, land resources, plant and animal resources, genetic resources, ecology resources, resource management and policy, resources conservation and recycling.
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