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Mapping the potential success of agricultural water management interventions for smallholders: Where are the best opportunities?

Research output: Contribution to journalArticlepeer-review



Publication details

JournalWater Resources and Rural Development
DateE-pub ahead of print - 15 Jun 2015
DatePublished (current) - Nov 2015
Number of pages26
Pages (from-to)24-49
Early online date15/06/15
Original languageEnglish


Abstract From field to basin scales, there are many appropriate interventions used to manage rainfall efficiently and productively in smallholder farming systems. Yet, successful targeting and scaling-out of these approaches remains a challenge. This paper presents an innovative approach in decision support called ‘Targeting Agricultural Water Management Interventions’ (TAGMI) with application in Limpopo and Volta river basins (available at The online open-access TAGMI uses country-scale Bayesian network models to assess the likelihood of success for outscaling various agricultural water management (AWM) interventions at sub-national level. The web tool integrates multiple sources of expertise on the enabling environment for outscaling based on key social, human, physical, financial, and natural factors. It estimates the relative probability of success of an AWM intervention across the Limpopo and Volta river basins. Here we present TAGMI as a ‘proof of concept’, areas of high, medium, and low probabilities of success for three AWM technologies common in Limpopo and Volta River Basins: the soil water conservation/in situ rainwater harvesting technologies in rain-fed systems, small-scale private irrigation and small reservoirs used for communal irrigation purposes. We then apply a climate change scenario and discuss the robustness in potential AWM, according to the TAGMI tool. Finally, we discuss the need for generic or specific information on ‘best practices of implementation’ for successful uptake of technologies in poverty-constrained smallholder farming systems.

    Research areas

  • Bayesian analysis, Limpopo, Rainwater harvesting, TAGMI, Technology adoption, Volta

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