Floods and Agriculture Risk Matrix: a decision support tool for effectively communicating flood risk from farmed landscapes

• Published in: International journal of river basin management Vol. 11; no. 3; pp. 237 - 252
• Main Authors: Wilkinson, Mark E, Quinn, Paul F, Hewett, Caspar J.M
• Format: Journal Article
• Language: English
• Published: Abingdon IAHR 01.09.2013; Taylor & Francis; Taylor & Francis Ltd
• Subjects: agricultural land; Agriculture; Decision support systems; decision support tool; Distributed memory; Earth sciences; Earth, ocean, space; Engineering and environment geology. Geothermics; Exact sciences and technology; farmers; Farming; farming systems; Flood insurance; Flood risk; Floods; Freshwater; Hydrology; Hydrology. Hydrogeology; land management; land use; Landscapes; Management; Marine and continental quaternary; Natural hazards: prediction, damages, etc; relative risk; Risk; Runoff; stakeholders; Surficial geology; Tillage; England; United Kingdom; Great Britain; Europe; Western Europe; landscapes; land management; floods; water policy; runoff; inundations; decision support systems; agriculture; decision support tool; land use; Flood risk; farming; soil erosion; Risk management; storms
• ISSN: 1814-2060; 1571-5124; 1814-2060
• DOI: 10.1080/15715124.2013.794145

Intense farming plays a key role in high runoff rates. It is vital to communicate this risk to stakeholders and policy-makers effectively. There is great potential for agriculture to become a major component in managing flood risk. It is proposed here that lower flood risk can be achieved by reducing runoff rates from farmed landscapes. Hence, tools to evaluate and communicate management options are needed alongside improved understanding of runoff generation from farming systems. The Floods and Agriculture Risk Matrix is a decision support tool designed to assess the relative risk of flooding from farm land. The tool includes a series of pre-determined runoff scenarios to provide the end-user with a number of potential land-management practices and flood runoff management options to reduce runoff rates. Visual scenarios are used to illustrate the impact of good and bad practice on runoff rates. The level of risk associated with particular land-management options is represented by mapping a position on a Decision Support Matrix (DSM). Multiple questions allow the user to explore different management options and see the impact of decisions on the DSM. A nominal scoring system is used to rank higher or lower runoff risk. The end-user can then assess numerous land-use management options to lower the risk of rapid runoff. The objective is to encourage policy-makers and farmers to produce resilient local landscapes.