University of Tasmania
146296 - Application, adoption and opportunities.pdf (3.25 MB)

Application, adoption and opportunities for improving decision support systems in irrigated agriculture: a review

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journal contribution
posted on 2023-05-21, 01:59 authored by Iffat Ara, Lydia Turner, Matthew HarrisonMatthew Harrison, Monjardino, M, DeVoil, P, Rodriguez, D
Decision support systems (DSS) have long been used in research, service provision and extension. Despite the diversity in technological applications in which past agricultural DSS canvass, there has been relatively little information on either the functional aspects of DSS designed for economic decisions in irrigated cropping, or human and social factors influencing the adoption of knowledge from such DSS. The objectives of the study were to (1) review the functionality and target end-users of economic DSS for irrigated cropping systems, (2) document the extent to which these DSS account for and visualise uncertainty in DSS outputs, (3) examine tactical or strategic decisions able to be explored in DSS (with irrigation infrastructure being a key strategic decision), and (4) explore the human and social factors influencing adoption of DSS heuristics. This study showed that development of previous DSS has often occurred as a result of a technology push instead of end-user pull, which has meant that previous DSS have been generated in a top-down fashion rather than being demand-driven by end-user needs. We found that few DSS enable analysis of both tactical and strategic decisions, and that few DSS account for uncertainty in their outputs. Perhaps more surprising was the lack of documented end-user feedback on economic DSS for irrigated cropping, such as end-user satisfaction with DSS functionality or future intentions to use the technology, as well as the lack of DSS application outside regions in which they were originally developed. Declining adoption of DSS does not necessarily imply declining adoption of DSS heuristics; in fact, declining DSS uptake may indicate that knowledge and heuristics extended by the DSS has been successful, obviating the need for use of the DSS per se. Future DSS could be improved through the use of demand-driven participatory approaches more aligned with user needs, with more training to build human capacity including understanding uncertainty and ability to contrast tactical and strategic decisions using multiple economic, environmental and social metrics.


Grains Research & Development Corporation


Publication title

Agricultural Water Management



Article number









Tasmanian Institute of Agriculture (TIA)


Elsevier Science Bv

Place of publication

Po Box 211, Amsterdam, Netherlands, 1000 Ae

Rights statement

Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0)

Repository Status

  • Open

Socio-economic Objectives

Water policy (incl. water allocation); Management of water consumption by plant production; Wheat