Modelling Risk and Uncertainty in Flood-Based Farming Systems in East Africa
Issoufou Liman1,3, Cory Whitney2,1, James Kungu3, Eike Luedeling1,2
1World Agroforestry Center (ICRAF), ESAF, Kenya
Flood-based farming systems (FBFS) rely on seasonal floods that provide beneficial water and nutrients, but also pose many risks and uncertainties for agricultural production. FBFS are extensive in East Africa, particularly in Kenya and Ethiopia, where they provide food to millions of people, along with many other agro-ecosystems services. Scientists have developed many crop models as important tools for agricultural development, but existing models are difficult to use in FBFS settings, due to the particular water supply characteristics of such systems. Development of new models that produce reliable results in FBFS settings has proven difficult due to system complexity, site-specific differences among different FBFS and lack of adequate datasets to develop and parameterise models. This difficulty is further exacerbated by socio-economic and management aspects that are crucial for system functioning. FBFS models must consider sediment management, infrastructure for water acquisition and social rules for water sharing among FBFS users.
Keywords: Bayesian Networks, Crop Model, East Africa, flood-based Farming Systems
Contact Address: Issoufou Liman, World Agroforestry Center (ICRAF), ESAF, United Nations Avenue Gigiri, 00100 Nairobi, Kenya, e-mail: l.issoufoucgiar.org