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Research article - Peer-reviewed, 2019

Developing and validating a decision support tool for media selection to mitigate drainage waters

Ezzati, Golnaz; Healy, M. G.; Christianson, L.; Feyereisen, G. W.; Thornton, S.; Daly, K.; Fenton, O.


The nitrate nitrogen (NO3-N) and ammonium (NH4-N) and/or dissolved reactive phosphorus (DRP) load in drainage water from farms can be managed by reactive or biological media filters. The nutrient content of the drainage water can be obtained directly from water analysis, which immediately focuses attention on filter media selection. There are many factors that may be important before choosing a medium or media e.g. nutrient removal capacity, lifetime, hydraulic conductivity, the potential for “pollution swapping”, attenuation of non-target contaminants (e.g. pesticides, organic carbon, etc.), and local availability and transportation cost of media to site. In this study, a novel decision support tool (DST) was developed, which brought all these factors together in one place for five nutrient scenarios. A systematic literature review was conducted to create a database containing 75 media with an associated static scoring system across seven criteria (% of nutrient concentration reduction, removal of other pollutants, lifetime, hydraulic conductivity, negative externalities) and a dynamic scoring system across two criteria (delivery cost and availability). The DST was tested using case studies from Ireland, Belgium and USA with different agricultural practices and nutrient scenarios. It was then validated by SWOT (strength, weakness, opportunities and threats) analysis. The DST provided a rapid, easily modifiable screening of many media-based treatments for specific dual or single nutrient-based water drainage problems. This provides stakeholders (farmers/regulators/advisors) with a versatile, flexible and robust yet easy-to-understand framework to make informed choices on appropriate media-based mitigation measures according to users’ relevant technical, economic and logistical factors.

Published in

Ecological Engineering
2019, Volume: 142, number: Suppl., article number: 100010

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    Agricultural Science

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