nerc.ac.uk

Screening for long-term trends in groundwater nitrate monitoring data

Stuart, M.E.; Chilton, P.J.; Kinniburgh, D.G.; Cooper, D.M. ORCID: https://orcid.org/0000-0001-7578-7918. 2007 Screening for long-term trends in groundwater nitrate monitoring data. Quarterly Journal of Engineering Geology and Hydrogeology, 40 (4). 361-376. https://doi.org/10.1144/1470-9236/07-040

Before downloading, please read NORA policies.
[img]
Preview
Text
Final version QJEGH 2007-40[1].pdf

Download (550kB) | Preview

Abstract/Summary

A large body of UK groundwater nitrate data has been analysed by linear regression to define past trends and estimate future concentrations. Robust regression was used. The datasets showed too many irregularities to justify more traditional time-series approaches such as ARIMA-type methods. Tests were included for lack of linearity, outliers, seasonality and a break in the trend (by piecewise linear regression). Of the series analysed, 21% showed a significant improvement in the overall fit when a break was included. Half of these indicated an increase in trend with time. Significant seasonality was found in about one-third of the series, with the largest nitrate concentrations usually found during winter months. Inclusion of nearby water-level data as an additional explanatory variable successfully accounted for much of this seasonality. Based on 309 datasets from 191 distinct sites, nitrate concentrations were found to be rising at an average of 0.34 mg NO3 l–1 a–1. In 2000, 34% of the sites analysed exceeded the 50 mg l–1 EU drinking water standard. If present trends continue, 41% could exceed the standard by 2015. We explored an alternative to the previously proposed Water Framework Directive aggregation approach for estimating trends in whole groundwater bodies (the ‘Grath’ approach: spatially average then find the trend). We first determined the trends for single boreholes and then spatially averaged these. This approach preserves information about the spatial distribution of trends within the water body and is less sensitive to ‘missing data’.

Item Type: Publication - Article
Digital Object Identifier (DOI): https://doi.org/10.1144/1470-9236/07-040
Programmes: CEH Programmes pre-2009 publications > Biogeochemistry
BGS Programmes > Groundwater Management
UKCEH and CEH Sections/Science Areas: Emmett
ISSN: 0481-2085
NORA Subject Terms: Ecology and Environment
Hydrology
Date made live: 29 Nov 2007 14:28 +0 (UTC)
URI: https://nora.nerc.ac.uk/id/eprint/1333

Actions (login required)

View Item View Item

Document Downloads

Downloads for past 30 days

Downloads per month over past year

More statistics for this item...