230
Views
13
CrossRef citations to date
0
Altmetric
Articles

Geostatistics-based design of regional groundwater monitoring framework

Pages 80-87 | Published online: 15 Apr 2013
 

Abstract

A methodology is developed based on the optimisation model and the geostatistical kriging model for the optimal design of groundwater head and quality monitoring plan. The multi-objective optimisation model considers minimisation of hydraulic head and concentration estimation error under budgetary limitation. The methodology incorporates Kriging as the external model for spatial estimation of hydraulic head and concentration values. Performances of the proposed model are evaluated for a regional groundwater aquifer in the Kanpur area. Multi-objective solution sets show directional preference along the hydraulic gradient. Performance evaluation results demonstrate the potential applicability of the methodology for optimal groundwater head and concentration monitoring plan design.

Acknowledgement

Author is thankful to Mr. Uday Mandal and Mr. Selva Balaji M., research scholars at the Indian Institute of Technology Kharagpur, for their help in data management.

This article is among the selected papers presented at the “Hydro-2012” conference held at the Indian Institute of Technology Bombay on 7–8 December 2012 and short-listed by Editor for publication in this Journal after re-review and revisions where necessary.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 173.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.