World Agroforestry (ICRAF)

July 29.2020

Photo: by ICRAF

Scientists have created a computer model that can estimate risks for agricultural development projects that were previously undervalued or not valued at all.

Up to USD 300 billion will be needed annually to adapt to the climate crisis, including the costs of projects designed to ensure agriculture is adaptable and sustainable in the face of climate extremes. Yet experience shows that agricultural-development projects in Africa can be highly risky and uncertain. At the design stage, they often fail to account for risks in implementing a project, even though conditions are known to be subject to rapid change. Part of the challenge is that few data are available to predict a project’s impact. So, projects frequently just fly blind.

Writing in the scientific journal, PLoS ONE, a research team from Hacettepe University in Turkey and World Agroforestry (ICRAF), explained their development of a Bayesian Network-based cost-benefit model to estimate these previously unaccounted risks.

Bayesian Networks are a powerful modelling tool that can integrate qualitative and quantitative data, helping to model the world we live in versus the data we have. This makes all the difference when making decisions when dealing with uncertainty and data are scarce.

See https://www.cgiar.org/news-events/news/investments-in-agricultural-development-quantifying-the-socio-political-and-climate-change-risks