Temporal and Spatial Statistical Methods to Remove External Effects on Groundwater Levels View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2012

AUTHORS

Daniele Imparato , Andrea Carena , Mauro Gasparini

ABSTRACT

This paper illustrates a project on monitoring groundwater levels elaborated jointly with officers from Regione Piemonte. Groundwater levels are strongly affected by external predictors, such as rain precipitation, neighboring waterways or local irrigation ditches. We discuss a kriging and transfer function approach applied to monthly and daily series of piezometric levels to model these neighboring effects. The aims of the study are to reconstruct a groundwater virgin level as an indicator of the state of health of the groundwater itself and to provide important regulatory tools to the local government. More... »

PAGES

241-251

References to SciGraph publications

Book

TITLE

Advanced Statistical Methods for the Analysis of Large Data-Sets

ISBN

978-3-642-21036-5
978-3-642-21037-2

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-21037-2_22

DOI

http://dx.doi.org/10.1007/978-3-642-21037-2_22

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1004484069


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