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The Decision Support Matrix (DSM) Approach to Reducing Environmental Risk in Farmed Landscapes

Lookup NU author(s): Dr Caspar Hewett, Dr Paul Quinn, Dr Mark Wilkinson

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Abstract

Modern intensive farming is an essential reality of modern life which brings major benefits but results in environmental pressures in constant need of solution, from increased flood risk and soil erosion to nutrient and pesticide export. The Decision Support Matrix (DSM) approach described here utilizes visualization and communication tools to help reduce environmental risk in farmed landscapes. Drawing on methods from physical and human geography, from mathematical modelling to participatory action research, the approach captures research expertise and local knowledge in forms accessible to farmers, land-use managers, planners and policy-makers. Conceptual models, easy-to-use interactive tools and examples of good and bad practice are co-developed by researchers and stakeholders, resulting in tools that enable practitioners to better understand the risks associated with specific land-use practices and assess measures to attenuate those risks. Most importantly it encourages users to take steps to reduce environmental risks. This paper sets out the philosophy underpinning the DSM approach and describes the tools developed. Examples are given of how the approach has been applied successfully to phosphorus and nitrate export, and to flood risk associated with arable and livestock farming.


Publication metadata

Author(s): Hewett CJM, Quinn PF, Wilkinson ME

Publication type: Article

Publication status: Published

Journal: Agricultural Water Management

Year: 2016

Volume: 172

Pages: 74-82

Print publication date: 01/07/2016

Online publication date: 29/04/2016

Acceptance date: 12/03/2016

Date deposited: 27/06/2016

ISSN (print): 0378-3774

ISSN (electronic): 1873-2283

Publisher: Elsevier

URL: http://dx.doi.org/10.1016/j.agwat.2016.03.008

DOI: 10.1016/j.agwat.2016.03.008


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