liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Roadmap for trend detection and assessment of data quality
Linköping University, Department of Computer and Information Science, Statistics. Linköping University, Faculty of Arts and Sciences.
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: urn:nbn:se:liu:diva-43109Local ID: 71719ISBN: 978-91-7393-792-4 (print)OAI: oai:DiVA.org:liu-43109DiVA: diva2:263967
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
List of papers
1. Semiparametric smoothers for trend assessment of multiple time series of environmental quality data
Open this publication in new window or tab >>Semiparametric smoothers for trend assessment of multiple time series of environmental quality data
2008 (English)In: Environmetrics, ISSN 1180-4009Article in journal (Other academic) Submitted
Abstract [en]

Multiple time series of environmental quality data with similar, but not necessarily identical, trends call for multivariate methods for trend detection and adjustment for covariates. Here, we show how an additive model in which the multivariate trend function is specified in a nonparametric fashion (and the adjustment for covariates is based on a parametric expression) can be used to estimate how the human impact on an ecosystem varies with time and across components of the observed vector time series. More specifically, we demonstrate how a roughness penalty approach can be utilized to impose different types of smoothness on the function surface that describes trends in environmental quality as a function of time and vector component. Compared to other tools used for this purpose, such as Gaussian smoothers and thin plate splines, an advantage of our approach is that the smoothing pattern can easily be tailored to different types of relationships between the vector components. We give explicit roughness penalty expressions for data collected over several seasons or representing several classes on a linear or circular scale. In addition, we define a general separable smoothing method. A new resampling technique that preserves statistical dependencies over time and across vector components enables realistic calculations of confidence and prediction intervals.

National Category
Computer and Information Science
Identifiers
urn:nbn:se:liu:diva-52243 (URN)
Available from: 2009-12-11 Created: 2009-12-11 Last updated: 2009-12-11Bibliographically approved
2. Uncertainty in water quality data and its implications for trend detection: lessons from Swedish environmental data
Open this publication in new window or tab >>Uncertainty in water quality data and its implications for trend detection: lessons from Swedish environmental data
2008 (English)In: Environmental Science and Policy, ISSN 1462-9011, Vol. 11, no 2, 115-124 p.Article in journal (Refereed) Published
Abstract [en]

The demands on monitoring systems have gradually increased, and interpretation of the data is often a matter of controversy. As an example of this, we investigated water quality monitoring and the eutrophication issue in Sweden. Our results demonstrate that powerful statistical tools for trend analysis can reveal flaws in the data and lead to new and revised interpretations of environmental data. In particular, we found strong evidence that long-term trends in measured nutrient concentrations can be more extensively influenced by changes in sampling and laboratory practices than by actual changes in the state of the environment. On a more general level, our findings raise important questions regarding the need for new paradigms for environmental monitoring and assessment. Introduction of a system in which conventional quality assurance is complemented with thorough statistical follow-up of reported values would represent a first step towards recognizing that environmental monitoring and assessment should be transformed from being a system for sampling and laboratory analyses into a system for interpreting information to support policy development.

National Category
Computer Science
Identifiers
urn:nbn:se:liu:diva-44473 (URN)10.1016/j.envsci.2007.12.001 (DOI)76781 (Local ID)76781 (Archive number)76781 (OAI)
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2009-12-11Bibliographically approved
3. Roadmap for assessing regional trends in groundwater quality
Open this publication in new window or tab >>Roadmap for assessing regional trends in groundwater quality
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
Keyword
Groundwater quality, Environmetrics, Multiple time series, Environmental monitoring, Mann-Kendall test
National Category
Mathematics
Identifiers
urn:nbn:se:liu:diva-52246 (URN)10.1007/s10661-009-0940-7 (DOI)000277371000019 ()
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
4. Estimating artificial level shifts in the presence of smooth trends
Open this publication in new window or tab >>Estimating artificial level shifts in the presence of smooth trends
2008 (English)In: Environmental Monitoring and Assessment, ISSN 0167-6369Article in journal (Other academic) Submitted
Abstract [en]

Changes in observational data over time can be severely distorted by errors in measurements, sampling, or reporting. Here, we show how smooth trends in vector time series can be separated from one or two abrupt level shifts that occur simultaneously in all coordinates. Trends are modelled nonparametrically, whereas abrupt changes and the impact of covariates are modelled parametrically. The model is estimated using a backfitting algorithm in which estimation of smooth trends is alternated with estimation of regression coefficients for covariates and assessment of sudden level shifts. The proposed method is adaptive in the sense that the degree of smoothing over time and across coordinates is controlled by a roughness penalty and cross-validation procedure that automatically identifies the interdependence of the analysed data. Furthermore, it uses a resampling technique that can accommodate correlated error terms in the assessment of the uncertainty of both smooth trends and discontinuities. The method is applied to water quality data from Swedish national monitoring programmes to illustrate how known discontinuities can be quantified and how previously unrecognized discontinuities can be detected.

National Category
Social Sciences
Identifiers
urn:nbn:se:liu:diva-52245 (URN)
Available from: 2009-12-11 Created: 2009-12-11 Last updated: 2011-05-20Bibliographically approved
5. Reduced Models of the Retention of Nitrogen in Catchments
Open this publication in new window or tab >>Reduced Models of the Retention of Nitrogen in Catchments
Show others...
2004 (English)In: Proceedings of the International Environmental Modelling and Software Society Conference (iEMSs), 14-17 June, Osnabrück, Germany, 2004, 1081-1086 p.Conference paper, Published paper (Refereed)
Abstract [en]

Process-oriented models of the retention of nitrogen in catchments are by necessity rather complex. We introduced several types of ensemble runs that can provide informative summaries of meteorologically normalised model outputs and also clarify the extent to which such outputs are related to various model parameters. Thereafter we employed this technique to examine policy-relevant outputs of the catchment model INCA-N. In particular, we examined how long it will take for changes in the application of fertilisers on cultivated land to affect the predicted riverine loads of nitrogen. The results showed that the magnitude of the total intervention effect was influenced mainly by the parameters governing the turnover of nitrogen in soil, whereas the temporal distribution of the water quality response was determined primarily by the hydromechanical model parameters. This raises the question of whether the soil nitrogen processes included in the model are elaborate enough to correctly explain the widespread observations of slow water quality responses to changes in agricultural practices.

Keyword
Model reduction; Ensemble runs; Catchment; Nitrogen; Retention
National Category
Computer and Information Science
Identifiers
urn:nbn:se:liu:diva-17110 (URN)
Available from: 2009-03-06 Created: 2009-03-06 Last updated: 2009-12-11Bibliographically approved

Open Access in DiVA

No full text

Authority records BETA

Wahlin, Karl

Search in DiVA

By author/editor
Wahlin, Karl
By organisation
StatisticsFaculty of Arts and Sciences
Computer Science

Search outside of DiVA

GoogleGoogle Scholar

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 480 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf