Skip navigation
Journal article

Targeting investments in small-scale groundwater irrigation using Bayesian networks for a data-scarce river basin in sub-Saharan Africa

This paper describes the application of a Bayesian network decision tool in the White Volta Basin, West Africa .

Joanne Morris / Published on 3 May 2016

Read the paper  Closed access

Citation

Katic, P. and J. Morris (2016). Targeting investments in small-scale groundwater irrigation using Bayesian networks for a data-scarce river basin in sub-Saharan Africa. Environmental Modelling & Software Volume 82, August 2016, Pages 44–72.

Irrigation for smallholder farming systems is an important approach for sustainable intensification and increased productivity in Sub-Saharan Africa, provided investments in irrigation are properly targeted and accompanied by complementary improvements.

Many GIS-based tools have been developed to identify suitable areas for investments in different types of small scale irrigation (SSI), but they do not explicitly address uncertainty on the data input and on the determination of factors that affect success of an investment in a given context.

This paper addresses this problem by presenting an application of a decision-support targeting tool based on Bayesian networks (BNs) that can be used by non-expert policy-makers and investors to assess the potential success of specific technologies used for groundwater-based SSI. A case study application for the White Volta Basin in West Africa is presented to illustrate the BN approach.

Read the article (external link to journal)

Read the paper

Closed access

SEI author

Joanne Morris

Research Associate

SEI York

Read the paper
10.1016/j.envsoft.2016.04.004 Closed access
Topics and subtopics
Water : Water resources
Tags
hydrology
Related centres
SEI York
Regions
Burkina Faso, Ghana