Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Modelling water chemistry for a major Scottish river from catchment attributes

Modelling water chemistry for a major Scottish river from catchment attributes 1. The prediction of water quality is increasingly required in river catchment management, but methods are still developmental. We therefore derived empirical models to predict the concentrations of base cations, H+ and alkalinity at any point in a complex Scottish river system, and under diverse discharge conditions. Input data were readily available from geological and topographic maps, whole rock composition data and catchment land use inventories in geographical information systems (GIS). 2. A key and novel feature of the model was prediction using geological data for the riparian zone within 50 m of the river. The discharge contributions that passed through soil derived from each parent rock were estimated and used as weightings in predicting final run‐off quality. 3. Typical equations for upland catchments for mean, maximum or minimum river water Ca concentration, (Ca), were of the form (Ca) = a + b √{Carz}, where {Carz} denotes flow routing‐weighted rock CaO concentration of the riparian zone rock types present. These equations were significant at P < 0·0001. Similar approaches were applicable to alkalinity and to other base cations. 4. Predictions of (Ca) in catchments with mixed land use were improved by including model terms for catchment riparian zone cover of agriculturally improved (intensified) grassland and arable land. These results indicated anthropogenic effects on base cation flux that would not be represented by geological data alone. 5. Similarly, concentrations of Na, Mg and K were correlated with Cl concentration in the river water, primarily as a consequence of marine‐derived Cl. Including distance from the east coast as a predictive variable in place of (Cl) obviated the need for direct (Cl) measurement in model operation. 6. We advocate further work to assess whether similar models can be developed and applied in other geographical locations, where features such as land use, geology and sea salt inputs will all vary. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Applied Ecology Wiley

Modelling water chemistry for a major Scottish river from catchment attributes

Download PDF
14 pages

Loading next page...
 
/lp/wiley/modelling-water-chemistry-for-a-major-scottish-river-from-catchment-J9xdZZxLWp

References (39)

Publisher
Wiley
Copyright
Copyright © 2000 Wiley Subscription Services, Inc., A Wiley Company
ISSN
0021-8901
eISSN
1365-2664
DOI
10.1046/j.1365-2664.2000.00525.x
Publisher site
See Article on Publisher Site

Abstract

1. The prediction of water quality is increasingly required in river catchment management, but methods are still developmental. We therefore derived empirical models to predict the concentrations of base cations, H+ and alkalinity at any point in a complex Scottish river system, and under diverse discharge conditions. Input data were readily available from geological and topographic maps, whole rock composition data and catchment land use inventories in geographical information systems (GIS). 2. A key and novel feature of the model was prediction using geological data for the riparian zone within 50 m of the river. The discharge contributions that passed through soil derived from each parent rock were estimated and used as weightings in predicting final run‐off quality. 3. Typical equations for upland catchments for mean, maximum or minimum river water Ca concentration, (Ca), were of the form (Ca) = a + b √{Carz}, where {Carz} denotes flow routing‐weighted rock CaO concentration of the riparian zone rock types present. These equations were significant at P < 0·0001. Similar approaches were applicable to alkalinity and to other base cations. 4. Predictions of (Ca) in catchments with mixed land use were improved by including model terms for catchment riparian zone cover of agriculturally improved (intensified) grassland and arable land. These results indicated anthropogenic effects on base cation flux that would not be represented by geological data alone. 5. Similarly, concentrations of Na, Mg and K were correlated with Cl concentration in the river water, primarily as a consequence of marine‐derived Cl. Including distance from the east coast as a predictive variable in place of (Cl) obviated the need for direct (Cl) measurement in model operation. 6. We advocate further work to assess whether similar models can be developed and applied in other geographical locations, where features such as land use, geology and sea salt inputs will all vary.

Journal

Journal of Applied Ecology – Wiley

Published: Sep 1, 2000

There are no references for this article.