The potential for expansion of irrigated rice under alternate wetting and drying in Burkina Faso

Achieving rice self-sufficiency in West Africa will require an expansion of the irrigated rice area under water scarce conditions. However, little is known about how much area can be irrigated and where and when water-saving practices could be used. The objective of this study was to assess potentially irrigable lands for irrigated rice cultivation under water-saving technology in Burkina Faso. A two-step, spatially explicit approach was developed and implemented. Firstly, machine learning models, namely Random Forest (RF) and Maximum Entropy (MaxEnt) were deployed in ecological niche modeling (ENM) approach to assess the land suitability for irrigated rice cultivation. Spatial datasets on topography, soil characteristics, climate parameters, land use, and water were used along with the current distribution of irrigated rice locations in Burkina Faso to drive ENMs. Secondly, the climatic suitability for alternate wetting and drying (AWD), an irrigation management method for saving water in rice cultivation in irrigated systems, was assessed by using a simple water balance model for the two main growing seasons (February to June and July to November) on a dekadal time scale. The evaluation metrics of the ENMs such as the area under the curve and percentage correctly classified showed values higher than 80% for both RF and MaxEnt. The top four predictors of land suitability for irrigated rice cultivation were exchangeable sodium percentage, exchangeable potassium, depth to the groundwater table, and distance to stream networks and rivers. Potentially suitable lands for rice cultivation in Burkina Faso were estimated at 21.1 x 10(5) ha. The whole dry season was found suitable for AWD implementation against 25-100% of the wet season. Soil percolation was the main driver of the variation in irrigated land suitability for AWD in the wet season. The integrated modeling and water balance assessment approach used in this study can be applied to other West African countries to guide investment in irrigated rice area expansion while adapting to climate change.

Automated summary

This study used machine learning models and water balance assessment to evaluate potentially irrigable lands for rice cultivation in Burkina Faso, and analyzed the climatic suitability for alternate wetting and drying (AWD) in the region.