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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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    1. Susanne Scheierling & David O. Treguer & James F. Booker, 2016. "Water Productivity in Agriculture: Looking for Water in the Agricultural Productivity and Efficiency Literature," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 2(03), pages 1-33, September.
    2. Mailhol, Jean Claude & Olufayo, Ayorinde A. & Ruelle, Pierre, 1997. "Sorghum and sunflower evapotranspiration and yield from simulated leaf area index," Agricultural Water Management, Elsevier, vol. 35(1-2), pages 167-182, December.
    3. Upali A. Amarasinghe & Vladimir Smakhtin, 2014. "Water productivity and water footprint: misguided concepts or useful tools in water management and policy?," Water International, Taylor & Francis Journals, vol. 39(7), pages 1000-1017, November.
    4. Cai, X. & Rosegrant, M. W., 2003. "World water productivity: current situation and future options," Book Chapters,, International Water Management Institute.
    5. Liu, Junguo & Williams, Jimmy R. & Zehnder, Alexander J.B. & Yang, Hong, 2007. "GEPIC - modelling wheat yield and crop water productivity with high resolution on a global scale," Agricultural Systems, Elsevier, vol. 94(2), pages 478-493, May.
    6. Descheemaeker, K. & Bunting, S. W. & Bindraban, P. & Muthuri, C. & Molden, D. & Beveridge, M. & van Brakel, Martin & Herrero, M. & Clement, Floriane & Boelee, Eline & Jarvis, D. I., 2013. "Increasing water productivity in Agriculture," IWMI Books, Reports H046126, International Water Management Institute.
    7. Fortes, P.S. & Platonov, A.E. & Pereira, L.S., 2005. "GISAREG--A GIS based irrigation scheduling simulation model to support improved water use," Agricultural Water Management, Elsevier, vol. 77(1-3), pages 159-179, August.
    8. Lorite, I.J. & Gabaldón-Leal, C. & Ruiz-Ramos, M. & Belaj, A. & de la Rosa, R. & León, L. & Santos, C., 2018. "Evaluation of olive response and adaptation strategies to climate change under semi-arid conditions," Agricultural Water Management, Elsevier, vol. 204(C), pages 247-261.
    9. López-Riquelme, J.A. & Pavón-Pulido, N. & Navarro-Hellín, H. & Soto-Valles, F. & Torres-Sánchez, R., 2017. "A software architecture based on FIWARE cloud for Precision Agriculture," Agricultural Water Management, Elsevier, vol. 183(C), pages 123-135.
    10. Tinashe Lindel Dirwai & Aidan Senzanje & Tafadzwanashe Mabhaudhi, 2021. "Calibration and Evaluation of the FAO AquaCrop Model for Canola ( Brassica napus ) under Varied Moistube Irrigation Regimes," Agriculture, MDPI, vol. 11(5), pages 1-18, May.
    11. van der Laan, M. & Jarmain, C. & Bastidas-Obando, E. & Annandale, J.G. & Fessehazion, M. & Haarhoff, D., 2019. "Are water footprints accurate enough to be useful? A case study for maize (Zea mays L.)," Agricultural Water Management, Elsevier, vol. 213(C), pages 512-520.
    12. Chen, Shilei & Huo, Zailin & Xu, Xu & Huang, Guanhua, 2019. "A conceptual agricultural water productivity model considering under field capacity soil water redistribution applicable for arid and semi-arid areas with deep groundwater," Agricultural Water Management, Elsevier, vol. 213(C), pages 309-323.
    13. Jiang, Yao & Xu, Xu & Huang, Quanzhong & Huo, Zailin & Huang, Guanhua, 2015. "Assessment of irrigation performance and water productivity in irrigated areas of the middle Heihe River basin using a distributed agro-hydrological model," Agricultural Water Management, Elsevier, vol. 147(C), pages 67-81.
    14. Sharma, R. & Kumar, A. & Joshi, P.K., 2017. "Nepal-India Agricultural Trade: Trends, Issues and Prospects," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 30(2).
    15. Megan D. Higgs & Xiaoke Zhang & Angelo Elmi & James M. Flegal & Jessica Utts & Sandra E. Safo & Craig A. Rolling & Michael J. Higgins & Jingyi Jessica Li, 2019. "blogdown: Creating Websites With R Markdown," The American Statistician, Taylor & Francis Journals, vol. 73(1), pages 94-104, January.
    16. Descheemaeker, K. & Bunting, S. W. & Bindraban, P. & Muthuri, C. & Molden, D. & Beveridge, M. & van Brakel, Martin & Herrero, M. & Clement, Floriane & Boelee, Eline & Jarvis, D. I., 2013. "Increasing water productivity in Agriculture," Book Chapters,, International Water Management Institute.
    17. Xu, Xu & Huang, Guanhua & Sun, Chen & Pereira, Luis S. & Ramos, Tiago B. & Huang, Quanzhong & Hao, Yuanyuan, 2013. "Assessing the effects of water table depth on water use, soil salinity and wheat yield: Searching for a target depth for irrigated areas in the upper Yellow River basin," Agricultural Water Management, Elsevier, vol. 125(C), pages 46-60.
    18. Molden, David & Oweis, Theib & Steduto, Pasquale & Bindraban, Prem & Hanjra, Munir A. & Kijne, Jacob, 2010. "Improving agricultural water productivity: Between optimism and caution," Agricultural Water Management, Elsevier, vol. 97(4), pages 528-535, April.
    19. Srinivasan, M.S. & Measures, Richard & Muller, Carla & Neal, Mark & Rajanayaka, Channa & Shankar, Ude & Elley, Graham, 2021. "Comparing the water use metrics of just-in-case, just-in-time and justified irrigation strategies using a scenario-based tool," Agricultural Water Management, Elsevier, vol. 258(C).
    20. Al-Jamal, M. S. & Sammis, T. W. & Mexal, J. G. & Picchioni, G. A. & Zachritz, W. H., 2002. "A growth-irrigation scheduling model for wastewater use in forest production," Agricultural Water Management, Elsevier, vol. 56(1), pages 57-79, July.
    21. Perimenis, Anastasios & Walimwipi, Hartley & Zinoviev, Sergey & Müller-Langer, Franziska & Miertus, Stanislav, 2011. "Development of a decision support tool for the assessment of biofuels," Energy Policy, Elsevier, vol. 39(3), pages 1782-1793, March.
    22. Taguta, C. & Senzanje, A. & Kiala, Z. & Malota, M. & Mabhaudhi, Tafadzwanashe, 2022. "Water-energy-food nexus tools in theory and practice: a systematic review," Papers published in Journals (Open Access), International Water Management Institute, pages 1-4:837316..
    23. Richards, Q.D. & Bange, M.P. & Johnston, S.B., 2008. "HydroLOGIC: An irrigation management system for Australian cotton," Agricultural Systems, Elsevier, vol. 98(1), pages 40-49, July.
    24. Kiniry, James R. & Williams, J. R. & Gassman, Philip W. & Debacke, P., 1992. "General, Process-Oriented Model for Two Competing Plant Species (A)," Staff General Research Papers Archive 483, Iowa State University, Department of Economics.
    25. Bautista, E. & Clemmens, A.J. & Strelkoff, T.S. & Schlegel, J., 2009. "Modern analysis of surface irrigation systems with WinSRFR," Agricultural Water Management, Elsevier, vol. 96(7), pages 1146-1154, July.
    26. Gassman, Philip W. & Reyes, Manuel R. & Green, Colleen H. & Arnold, Jeffrey G., 2007. "The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions," ISU General Staff Papers 200701010800001027, Iowa State University, Department of Economics.
    27. Cai, X. & Rosegrant, M. W., 2003. "World water productivity: current situation and future options," IWMI Books, Reports H032641, International Water Management Institute.
    28. de Wit, Allard & Boogaard, Hendrik & Fumagalli, Davide & Janssen, Sander & Knapen, Rob & van Kraalingen, Daniel & Supit, Iwan & van der Wijngaart, Raymond & van Diepen, Kees, 2019. "25 years of the WOFOST cropping systems model," Agricultural Systems, Elsevier, vol. 168(C), pages 154-167.
    29. Taguta, C. & Dirwai, T. L. & Senzanje, A. & Sikka, Alok & Mabhaudhi, Tafadzwanashe, 2022. "Sustainable irrigation technologies: a water-energy-food (WEF) nexus perspective towards achieving more crop per drop per joule per hectare," Papers published in Journals (Open Access), International Water Management Institute, pages 1-17(7):073.
    30. Hanson, J. D. & Ahuja, L. R. & Shaffer, M. D. & Rojas, K. W. & DeCoursey, D. G. & Farahani, H. & Johnson, K., 1998. "RZWQM: Simulating the effects of management on water quality and crop production," Agricultural Systems, Elsevier, vol. 57(2), pages 161-195, June.
    31. Hearn, A. B., 1994. "OZCOT: A simulation model for cotton crop management," Agricultural Systems, Elsevier, vol. 44(3), pages 257-299.
    32. Foster, T. & Brozović, N. & Butler, A.P. & Neale, C.M.U. & Raes, D. & Steduto, P. & Fereres, E. & Hsiao, T.C., 2017. "AquaCrop-OS: An open source version of FAO's crop water productivity model," Agricultural Water Management, Elsevier, vol. 181(C), pages 18-22.
    33. Molden, D. & Murray-Rust, H. & Sakthivadivel, R. & Makin, I., 2003. "A water-productivity framework for understanding and action," IWMI Books, Reports H032632, International Water Management Institute.
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