Home > Basin > Volta > Volta Project on Targeting and Scaling Out (V1)


Opportunities to adopt and adapt agricultural water management interventions for improved income and livelihoods in the Volta River basin still exist. Replicating successful agricultural water management interventions in new locations requires consideration of economic, biophysical, institutional, and cultural factors.

During the past 50 years several agricultural water management interventions have proved successful in the Volta river basin, including soil and water conservation, small-scale irrigation, and small reservoirs. Yet, according to key stakeholders, successful targeting and scaling-out of interventions remains a challenge and more support for decisions is needed.

The Targeting and Scaling Out project (V1) set out to develop an evidence- and knowledge-based tool to assess and map the likelihood that a given intervention will be successful in a given location. The project sought to answer: What works where and why?

By developing the Targeting Agricultural Water Management Interventions (TAGMI) tool, the project intended to help decision-makers answer these questions. The tool is based on both biophysical and socio-economic data. In addition to data about a district’s background, i.e. key social, human, physical, financial and natural factors, the tool also relies on local knowledge and expert opinion collected through stakeholder consultations. Based on these inputs, the tool calculates the relative probability that an agricultural water management intervention would be successful in a given district.

TAGMI uses Bayesian network models to assess the potential success of interventions, estimating how different factors, such as access to water and climate variability, interact. TAGMI offers a map-based visualization of the Bayesian model’s results, showing how likely it is that soil and water conservation, small-scale irrigation, or small reservoirs could be successfully adopted in different districts. The certainty with which the model predicts the likelihood of success would be greatly improved if more data could be collected and made available.

TAGMI was developed by the Stockholm Environment Institute in partnership with the Institut de l’Environnement et de Recherches Agricoles, the Civil Engineering Department of the Kwame Nkrumah University of Science and Technology in Ghana, the Council for Scientific and Industrial research of the Savanna Agricultural Research Institute, and University of Ouagadougou in Burkina Faso.


Outcomes: Change in Knowledge

  • Researchers and students have become better at conducting participatory geographic information systems research;
  • Students improved fieldwork for their theses, presented and engaged in regional and international fora;
  • Farmers have better understanding of participatory geographic information systems and use of Google Earth;
  • Expert stakeholders have learned how to use the TAGMI tool and are finding it relevant, useful, and timely.


Institut National de l’Environnement et de Recherches Agricoles (INERA); Civil Engineering Dept. of the Kwame Nkrumah University of Science and Technology (KNUST); Savanna Agricultural Research Institute (SARI); Département de Géographie de l’Université de Ouagadougou.

Project Leader

Project Leader:

Jennie Barron (jennie.barron@sei.se)