Redirigiendo al acceso original de articulo en 24 segundos...
Inicio  /  Hydrology  /  Vol: 10 Par: 4 (2023)  /  Artículo
ARTÍCULO
TITULO

Search for a Relevant Scale to Optimize the Quality Monitoring of Groundwater Bodies in the Occitanie Region (France)

Meryem Jabrane    
Abdessamad Touiouine    
Vincent Valles    
Abdelhak Bouabdli    
Said Chakiri    
Ismail Mohsine    
Youssouf El Jarjini    
Moad Morarech    
Yannick Duran and Laurent Barbiero    

Resumen

In France, and more generally in Europe, the high number of groundwater bodies (GWB) per administrative region is an obstacle for the management and monitoring of water for human consumption by regional health agencies. Moreover, GWBs show a high spatial, temporal, physico-chemical, and bacteriological variability. The objective is to establish homogeneous groupings of GWB from the point of view of water quality and the processes responsible for this quality. In the Occitanie region in southwestern France, the cross-referencing of two databases, namely the French reference system for groundwater bodies and SISE-EAUX, provided a dataset of 8110 observations and 15 parameters distributed over 106 GWB. The 8-step approach, including data conditioning, dimensional reduction by Principal Component Analysis, and hierarchical clustering, resulted in 20 homogeneous groups of GWB over the whole region. The loss of information caused by this grouping is quantified by the evolution of the explained variance. Splitting the region into two large basins (Adour-Garonne and Rhône Méditerranée) according to the recommendations of the European community does not result in a significant additional loss of information contained in the data. A quick study of a few groups allows to highlight the specificities of each one, thus enabling targeted guidelines or recommendations for water quality management and monitoring. In the future, the method will have to be tested on the scale of large European watersheds, as well as in the context of an increase in the number of parameters.

 Artículos similares

       
 
Atik Kulakli and Cenk Lacin Arikan    
In the era of the Internet of Things, innovative business model initiatives continue to deepen, and the trend of search domains continues to expand. This paper aims to scientifically analyze research trends of the Internet of Things in relation to Busine... ver más
Revista: Future Internet

 
Eric Hsueh-Chan Lu and You-Ru Lin    
With the rise in the Internet of Things (IOT), mobile devices and Location-Based Social Network (LBSN), abundant trajectory data have made research on location prediction more popular. The check-in data shared through LBSN hide information related to lif... ver más

 
Yu Cao, Yan Chen, Huizan Wang, Xiaojiang Zhang and Wenjing Zhao    
Grid remapping is one of the most fundamental functions in Earth simulation systems, and is essentially a kind of data interpolation. The key to an efficient interpolation method is how to quickly find the relevant grid points required for interpolation.... ver más

 
George Lazaroiu, Mihai Andronie, Mariana Iatagan, Marinela Geamanu, Roxana ?tefanescu and Irina Dijmarescu    
The purpose of our systematic review is to examine the recently published literature on the Internet of Manufacturing Things (IoMT), and integrate the insights it configures on deep learning-assisted smart process planning, robotic wireless sensor networ... ver más

 
Sampada Tavse, Vijayakumar Varadarajan, Mrinal Bachute, Shilpa Gite and Ketan Kotecha    
With the advances in brain imaging, magnetic resonance imaging (MRI) is evolving as a popular radiological tool in clinical diagnosis. Deep learning (DL) methods can detect abnormalities in brain images without an extensive manual feature extraction proc... ver más
Revista: Future Internet