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Sci Total Environ. 2012 Sep 15;434:186-200. doi: 10.1016/j.scitotenv.2011.10.052. Epub 2011 Nov 25.

An analysis of long-term trends, seasonality and short-term dynamics in water quality data from Plynlimon, Wales.

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1
Department of Geography and Environmental Science, University of Reading, Reading, UK. s.j.halliday@pgr.reading.ac.uk

Abstract

This paper examines two hydrochemical time-series derived from stream samples taken in the Upper Hafren catchment, Plynlimon, Wales. One time-series comprises data collected at 7-hour intervals over 22 months (Neal et al., 2012-this issue), while the other is based on weekly sampling over 20 years. A subset of determinands: aluminium, calcium, chloride, conductivity, dissolved organic carbon, iron, nitrate, pH, silicon and sulphate are examined within a framework of non-stationary time-series analysis to identify determinand trends, seasonality and short-term dynamics. The results demonstrate that both long-term and high-frequency monitoring provide valuable and unique insights into the hydrochemistry of a catchment. The long-term data allowed analysis of long-term trends, demonstrating continued increases in DOC concentrations accompanied by declining SO(4) concentrations within the stream, and provided new insights into the changing amplitude and phase of the seasonality of the determinands such as DOC and Al. Additionally, these data proved invaluable for placing the short-term variability demonstrated within the high-frequency data within context. The 7-hour data highlighted complex diurnal cycles for NO(3), Ca and Fe with cycles displaying changes in phase and amplitude on a seasonal basis. The high-frequency data also demonstrated the need to consider the impact that the time of sample collection can have on the summary statistics of the data and also that sampling during the hours of darkness provides additional hydrochemical information for determinands which exhibit pronounced diurnal variability. Moving forward, this research demonstrates the need for both long-term and high-frequency monitoring to facilitate a full and accurate understanding of catchment hydrochemical dynamics.

PMID:
22119034
DOI:
10.1016/j.scitotenv.2011.10.052
[Indexed for MEDLINE]
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