Evaluation and optimisation of groundwater observation networks using the Kriging methodology [An article from: Environmental Modelling and Software]
Book Details
Author(s)N. Theodossiou, P. Latinopoulos
PublisherElsevier
ISBN / ASINB000RR95G6
ISBN-13978B000RR95G0
AvailabilityAvailable for download now
Sales Rank13,946,059
MarketplaceUnited States 🇺🇸
Description
This digital document is a journal article from Environmental Modelling and Software, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
Groundwater simulation models have nowadays a decisive role in the development and application of rational water policies. Since the accuracy of the simulation depends strongly on the available data, the task of optimising the observation networks is of great importance. In this paper an application is presented aiming at the optimisation of groundwater level observation networks and the improvement of the quality rather than the quantity of the obtained data. This technique is based on the application of the Kriging methodology and the evaluation of its results in conjunction with the statistical analysis of the available groundwater level data. This procedure that involves different analysis methods of the available data, such as estimation of the interpolation error, data crossvalidation and time variation, is applied to a case study in order to demonstrate the potential of improvement of the quality of the observation network.
Description:
Groundwater simulation models have nowadays a decisive role in the development and application of rational water policies. Since the accuracy of the simulation depends strongly on the available data, the task of optimising the observation networks is of great importance. In this paper an application is presented aiming at the optimisation of groundwater level observation networks and the improvement of the quality rather than the quantity of the obtained data. This technique is based on the application of the Kriging methodology and the evaluation of its results in conjunction with the statistical analysis of the available groundwater level data. This procedure that involves different analysis methods of the available data, such as estimation of the interpolation error, data crossvalidation and time variation, is applied to a case study in order to demonstrate the potential of improvement of the quality of the observation network.
