Editor’s choice
This paper describes an innovative approach in decision support called Targeting Agricultural Water Management Interventions (TAGMI) that addresses the challenge of identifying appropriate interventions used to manage rainfall efficiently and productively in smallholder farming systems.
The online open-access TAGMI tool (available at www.seimapping.org/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. In this paper it estimates the relative probability of success of an AWM intervention across the Limpopo and Volta river basins.
TAGMI is presented as a ‘proof of concept’, to assess current areas of high, medium, and low probability 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. A climate change scenario is applied and used to discuss the robustness in potential AWM, according to the TAGMI tool. The paper then discusses the need for further development of Decision Support Systems for AWM interventions, and the need for generic or specific information on ‘best practices of implementation’ for successful uptake of technologies in poverty-constrained smallholder farming systems.
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