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An integrated modelling and multicriteria analysis approach to managing nitrate diffuse pollution: 2. A case study for a chalk catchment in England

Lookup NU author(s): Bhon Koo, Professor Enda O'Connell


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The site-specific land use optimisation methodology, suggested by the authors in the first part of this two-part paper, has been applied to the River Kennet catchment at Marlborough, Wiltshire, UK, for a case study. The Marlborough catchment (143 km2) is an agriculture-dominated rural area over a deep chalk aquifer that is vulnerable to nitrate pollution from agricultural diffuse sources. For evaluation purposes, the catchment was discretised into a network of 1 km x 1 km grid cells. For each of the arable-land grid cells, seven land use alternatives (four arable-land alternatives and three grassland alternatives) were evaluated for their environmental and economic potential. For environmental evaluation, nitrate leaching rates of land use alternatives were estimated using SHETRAN simulations and groundwater pollution potential was evaluated using the DRASTIC index. For economic evaluation, economic gross margins were estimated using a simple agronomic model based on nitrogen response functions and agricultural land classification grades. In order to see whether the site-specific optimisation is efficient at the catchment scale, land use optimisation was carried out for four optimisation schemes (i.e. using four sets of criterion weights). Consequently, four land use scenarios were generated and the site-specifically optimised land use scenario was evaluated as the best compromise solution between long term nitrate pollution and agronomy at the catchment scale. © 2005 Elsevier B.V. All rights reserved.

Publication metadata

Author(s): Koo BK, O'Connell PE

Publication type: Article

Publication status: Published

Journal: Science of the Total Environment

Year: 2006

Volume: 358

Issue: 1-3

Pages: 1-20

ISSN (print): 0048-9697

ISSN (electronic): 1879-1026

Publisher: Elsevier BV


DOI: 10.1016/j.scitotenv.2005.05.013

PubMed id: 15970313


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