Trends in surface water chemistry in afforested Welsh catchments recovering from acidification, 1991–2012

Broadmeadow, S.B.; Nisbet, T.R.; Forster, J.

Trends in surface water chemistry in afforested Welsh catchments recovering from acidification, 1991–2012

2019

Broadmeadow, S.B. | Nisbet, T.R. | Forster, J.

A key criterion of the UK Government's policy on sustainable forest management is safeguarding the quality and quantity of water. Forests and forestry management practices can have profound effects on the freshwater environment. Poor forest planning or management can severely damage water resources at great cost to other water users; in contrast good management that restores and maintains the natural functions of woodland can benefit the whole aquatic ecosystem.Forests and forest management practices can affect surface water acidification. Monitoring of water chemistry in ten forest and two moorland acid-sensitive catchments in upland Wales commenced in 1991. The streams were selected to supplement the United Kingdom Upland Waters Monitoring Network (UWMN) with additional examples of afforested catchments. Analysis of 22 years of water chemistry data revealed trends indicative of recovery from acidification. Excess sulphate exhibited a significant coherent decline, accompanied by increases in pH and “charge-balance based” acid neutralising capacity (CB-ANC). Alkalinity and “alkalinity-based” acid neutralising capacity (AB-ANC) exhibited fewer trends, possibily due to the variable responses of the organic - carbonate species to increasing pH in these low alkalinity streams. Whilst total anthropogenic acidity declined, dissolved organic carbon and Nitrate-Nitrogen (NNO₃) concentrations have risen, and the contribution of NNO₃ to acidification has increased.Between-stream variability was analysed using Principal Component Analysis of the trend slopes. Hierarchical clustering of the changes in stream water chemistry indicated three distinct clusters with no absolute distinction between moorland and forest streams. Redundancy analysis was used to test for significant site-specific variables that explained differences in the trend slopes, with rainfall, crop age, base cation concentration and forest cover being significant explanatory variables.

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