NDLI: Optimal design of monitoring networks for multiple groundwater quality parameters using a Kalman filter: application to the Irapuato-Valle aquifer

Content Provider	Springer Nature Link
Author	Júnez Ferreira, H. E. Herrera, G. S. González Hita, L. Cardona, A. Mora Rodríguez, J.
Copyright Year	2015
Abstract	A new method for the optimal design of groundwater quality monitoring networks is introduced in this paper. Various indicator parameters were considered simultaneously and tested for the Irapuato-Valle aquifer in Mexico. The steps followed in the design were (1) establishment of the monitoring network objectives, (2) definition of a groundwater quality conceptual model for the study area, (3) selection of the parameters to be sampled, and (4) selection of a monitoring network by choosing the well positions that minimize the estimate error variance of the selected indicator parameters. Equal weight for each parameter was given to most of the aquifer positions and a higher weight to priority zones. The objective for the monitoring network in the specific application was to obtain a general reconnaissance of the water quality, including water types, water origin, and first indications of contamination. Water quality indicator parameters were chosen in accordance with this objective, and for the selection of the optimal monitoring sites, it was sought to obtain a low-uncertainty estimate of these parameters for the entire aquifer and with more certainty in priority zones. The optimal monitoring network was selected using a combination of geostatistical methods, a Kalman filter and a heuristic optimization method. Results show that when monitoring the 69 locations with higher priority order (the optimal monitoring network), the joint average standard error in the study area for all the groundwater quality parameters was approximately 90 % of the obtained with the 140 available sampling locations (the set of pilot wells). This demonstrates that an optimal design can help to reduce monitoring costs, by avoiding redundancy in data acquisition.
Starting Page	1
Ending Page	22
Page Count	22
File Format	PDF
ISSN	01676369
Journal	Environmental Monitoring and Assessment
Volume Number	188
Issue Number	1
e-ISSN	15732959
Language	English
Publisher	Springer International Publishing
Publisher Date	2015-12-17
Publisher Place	Cham
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Optimal monitoring network Geostatistics Kalman filter Groundwater quality Priority zones Environmental Monitoring/Analysis Environmental Management Ecotoxicology Atmospheric Protection/Air Quality Control/Air Pollution Ecology
Content Type	Text
Resource Type	Article
Subject	Pollution Medicine Management, Monitoring, Policy and Law

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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