Contributions of lateral flow and groundwater to the spatio-temporal variation of irrigated rice yields and water productivity in a West-African inland valley

• Lateral flow masks the effect of water management practices.
• Shallow groundwater tables strongly influence rice performance along toposequences.
• Mixed regression model is able to predict rice yields in African inland valleys.
• Model is a function of groundwater table, rainfall and standard soil characteristics.

Water management techniques to elevate rice yields and productive use of water resources in Africa, frequently lack a substantial spatial assessment as they are often based on plot level measurements without taking into account toposequential effects present in the landscape. These effects have been shown to significantly affect spatio-temporal variations in water availability and rice productivity in Asia. Therefore, this study addresses the spatio-temporal variations of the various water components within irrigated toposequences in an African inland valley and assesses its effect on water productivity and respective rice yields for two irrigation practices: (i) continuous flooding (CF), a well-known water management practice in rice cultivation used worldwide and (ii) a reduced irrigation scheme (RI) where irrigation is applied every 5 days resulting in a 1–2 cm water layer after irrigation.The lateral flow observed in the inland valley had a strong two-dimensional character, contributing to water gains between fields, located at the same toposequential level as well as along toposequences. The toposequential effect on sub-surface hydrological processes masked the overall effect of water management treatment on rice production. Additionally, the associated water productivity (WP) was not found to differ significantly between the treatments when standard calculations (i.e. net irrigation and evapotranspiration) were used but a clear toposequential effect was found for the fertilized lower lying fields when the net irrigation was corrected by the lateral flow component. Results of the established mixed regression model indicated that based on the groundwater table, rainfall and standard soil physico-chemical characteristics rice yields can be predicted in these African inland valleys under continuous flooding and reduced irrigation practices. Validation of the established regression function of inland valleys, representing various groundwater tables in the region, could lead to improved regression functions suitable to estimate spatial variation in rice production and water consumption across scales as affected by water management, fertilizer application and groundwater tables.