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Roadmap for assessing regional trends in groundwater quality
Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
2010 (English)In: Environmental Monitoring and Assessment, ISSN 0167-6369, Vol. 165, no 1-4, 217-231 p.Article in journal (Refereed) Published
Abstract [en]

Assessing regional trends in groundwater quality can be a difficult task. Data are often scattered in space and time, and the inertia of groundwater systems can create natural, seemingly persistent changes in concentration that are difficult to separate from anthropogenic trends. Here, we show how statistical methods and software for joint analysis of multiple time series can be integrated into a roadmap for trend analysis and critical examination of data quality. Ordinary and partial Mann-Kendall (MK) tests for monotonic trends and semiparametric smoothers for multiple time series constitute the cornerstones of our procedure. The MK tests include a simple and easily implemented method to correct for serial dependence, and the associated software is designed to enable convenient handling of numerous data series and to accommodate covariates and nondetects. The semiparametric smoothers are intended to facilitate detection of synchronous changes in a network of stations. A study of Swedish groundwater quality data revealed true upward trends in acid-neutralizing capacity (ANC) and downward trends in sulphate, but also a misleading shift in alkalinity level that would have been difficult to detect if the time series had been analysed separately.

Place, publisher, year, edition, pages
Springer Science Business Media , 2010. Vol. 165, no 1-4, 217-231 p.
Keyword [en]
Groundwater quality, Environmetrics, Multiple time series, Environmental monitoring, Mann-Kendall test
National Category
Mathematics
Identifiers
URN: urn:nbn:se:liu:diva-52246DOI: 10.1007/s10661-009-0940-7ISI: 000277371000019OAI: oai:DiVA.org:liu-52246DiVA: diva2:280809
Note
The original publication is available at www.springerlink.com: Karl Wahlin and Anders Grimvall, Roadmap for assessing regional trends in groundwater quality, 2010, Environmental Monitoring and Assessment, (165), 1-4, 217-231. http://dx.doi.org/10.1007/s10661-009-0940-7 Copyright: Springer Science Business Media http://www.springerlink.com/ Available from: 2009-12-11 Created: 2009-12-11 Last updated: 2010-05-31Bibliographically approved
In thesis
1. Roadmap for trend detection and assessment of data quality
Open this publication in new window or tab >>Roadmap for trend detection and assessment of data quality
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Regular measurements of the state of the environment constitute a cornerstone of environmental management. Without the support of long time series of reliable data, we would know much less about changes that occur in the environment and their causes. The present research aimed to explore how improved techniques for data analysis can help reveal flawed data and extract more information from environmental monitoring programmes. Based on our results, we propose that the organization of such monitoring should be transformed from a system for measuring and collecting data to an information system where resources have been reallocated to data analysis. More specifically, this thesis reports improved methods for joint analysis of trends in multiple time series and detection of artificial level shifts in the presence of smooth trends. Furthermore, special consideration is given to methods that automatically detect and adapt to the interdependence of the collected data. The current work resulted in a roadmap describing the process of proceeding from a set of observed concentrations to arrive at conclusions about the quality of the data and existence of trends therein. Improvements in existing software accompanied the development of new statistical procedures.

Place, publisher, year, edition, pages
Linköping: Linköpings universitet, 2008. 81 + papers 1-5 p.
Series
Linköping Studies in Statistics, ISSN 1651-1700 ; 10Linköping Studies in Arts and Science, ISSN 0282-9800 ; 454
National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-43109 (URN)71719 (Local ID)978-91-7393-792-4 (ISBN)71719 (Archive number)71719 (OAI)
Public defence
2008-10-10, Alan Turing, Hus E, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Supervisors
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2014-09-25Bibliographically approved

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Wahlin, KarlGrimvall, Anders

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  • de-DE
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