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Mapping Decision Support Tools (DSTs) on agricultural water productivity: A global systematic scoping review

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  • Mabhaudhi, Tafadzwanashe
  • Dirwai, Tinashe Lindel
  • Taguta, Cuthbert
  • Sikka, Alok
  • Lautze, Jonathan

Abstract

While there is a proliferation of Decision Support Tools (DSTs) to enhance agricultural water productivity (AWP) and related objectives such as food security, an assessment of their adoption and performance is not known to be undertaken. To develop new or improved DSTs for bespoke applications in optimizing AWP, there needs to be a stock-take of the existing tools, their functionality, user-friendliness and uptake. We compiled and assessed existing DSTs for AWP as a starting point for present and future developers who intend to improve existing or develop new DSTs for optimizing AWP. Secondarily, this review identifies DSTs' key characteristics, availability, and applicability for different typologies and spatio-temporal scales. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach was applied to search for literature from Scopus and WoS databases. The study revealed the existence of 81 documented AWP DSTs whose development started from around the 1970 s, peaked in the 1990 s, and declined after that although the improvement and upgrading of existing DSTs continued. Over half (51%) of the DSTs are not readily available in the public domain. The prevalent spatial and temporal application scales are field and day, respectively. There is limited reporting on the application at scale, partly due to the wide unavailability of DSTs. A gap exists in AWP DSTs with geospatial capabilities (one in 10 or 10% had geographic information systems (GIS) integration capabilities). Most DSTs focus on water and food (yield) components but omit energy and other dimensions of AWP. Regarding format, most tools were available as desktop (35%) and web-based (48%) applications, and codes (27%). Developers should strive to deliver AWP tools in convenient, compatible, and user-friendly for a wide range of users, from novices to experts.

Suggested Citation

  • Mabhaudhi, Tafadzwanashe & Dirwai, Tinashe Lindel & Taguta, Cuthbert & Sikka, Alok & Lautze, Jonathan, 2023. "Mapping Decision Support Tools (DSTs) on agricultural water productivity: A global systematic scoping review," Agricultural Water Management, Elsevier, vol. 290(C).
    • Handle: RePEc:eee:agiwat:v:290:y:2023:i:c:s0378377423004559
    DOI: 10.1016/j.agwat.2023.108590
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