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Related Experiment Video

Updated: Jun 23, 2026

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Continuous Instream Monitoring of Nutrients and Sediment in Agricultural Watersheds

Published on: September 26, 2017

Roadmap for assessing regional trends in groundwater quality.

Karl Wahlin¹, Anders Grimvall

¹Department of Computer and Information Science, Linköping University, Linköping, Sweden. kawah@ida.liu.se

Environmental Monitoring and Assessment

|May 16, 2009

Summary

Statistical methods for analyzing multiple groundwater quality time series reveal true trends while preventing misinterpretation of natural system changes. This approach enhances data quality assessment for regional groundwater monitoring.

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Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds

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Published on: November 13, 2017

Area of Science:

Environmental Science
Hydrogeology
Statistical Modeling

Background:

Assessing regional groundwater quality trends is challenging due to scattered data and natural system inertia.
Distinguishing anthropogenic trends from natural variations in groundwater concentration requires robust analytical methods.
Existing methods often struggle to effectively analyze complex, multi-station groundwater datasets.

Purpose of the Study:

To develop and demonstrate a roadmap for trend analysis and data quality assessment in regional groundwater monitoring.
To integrate statistical methods and software for the joint analysis of multiple groundwater quality time series.
To improve the detection of genuine environmental trends and avoid misinterpretation of natural groundwater system dynamics.

Main Methods:

Utilized ordinary and partial Mann-Kendall (MK) tests for monotonic trend detection.
Employed semiparametric smoothers for the joint analysis of multiple time series, facilitating the detection of synchronous changes.
Incorporated methods to correct for serial dependence and accommodate covariates and nondetects within the MK tests.

Main Results:

Identified true upward trends in acid-neutralizing capacity and downward trends in sulfate in Swedish groundwater data.
Detected a misleading shift in alkalinity that would have been missed with separate time series analysis.
Demonstrated the effectiveness of the integrated statistical approach in accurately assessing groundwater quality trends.

Conclusions:

The integrated statistical roadmap provides a powerful tool for reliable regional groundwater quality trend assessment.
Joint analysis of multiple time series is crucial for distinguishing true environmental changes from natural system fluctuations.
The developed methods enhance the critical examination of data quality and improve the interpretation of groundwater monitoring networks.