D-Risk: A decision-support webtool for improving drought risk management in irrigated agriculture

David Haro Monteagudo, Jerry Knox, Ian Holman* (Corresponding Author)

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

Drought constitutes a significant production and business risk in agriculture, particularly for those enterprises dependent on irrigation to deliver high quality continuous supplies of fresh produce to the retail sector. Whilst most farmers are well attuned to managing short term weather-related crop risks, they lack access to tools that can support medium-term decision-making and risk management strategies under conditions of increasing water scarcity and climate uncertainty. This paper describes D-Risk, an intuitive online webtool designed to help farming enterprises easily understand their existing and emergent drought and irrigation abstraction risks and thereby support more robust decision-making regarding future changes in crop planning and water resources infrastructure investment.
Original languageEnglish
Pages (from-to)855-858
Number of pages4
JournalComputers and Electronics in Agriculture
Volume162
Early online date22 May 2019
DOIs
Publication statusPublished - Jul 2019

Bibliographical note

The authors acknowledge funding support from UK Research and Innovation (UKRI) Natural Environment Research Council (NERC) innovation grant (NE/N017471/1) and access to the MaRIUS event sets (developed in NERC grants NE/L010364/1, NE/L010208/1, NE/L010399/1, NE/L010186/1). We acknowledge support from Melvyn Kay (UK Irrigation Association), Paul Hammett (National Farmers Union), Tim Jolly (WO & PO Jolly), Andrew Blenkiron (Euston Estate), Lindsay Hargreaves (Frederick Hiam Ltd), and Andrew Francis (Elveden) in co-design and testing, and website development by Mick Redman. The supporting annual PSMDmax data referred to in this article can be accessed at https://doi.org/10.17862/cranfield.rd.6792260. The MaRIUS event set data are available on the Centre for Environmental Data Analysis (CEDA) platform (see https://doi.org/10.5285/0cea8d7aca57427fae92241348ae9b03).

Keywords

  • Irrigation
  • Reservoir
  • Water Resources
  • Probabilistic
  • Risk

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