Identifying suitable boreholes for irrigation in the bedrock regions of the Sahel.

This study addresses the critical challenge of optimizing borehole drilling techniques and predictive models to improve groundwater utilization for irrigation in Burkina Faso. Initially, the analysis involved drilling 22 boreholes as part of a photovoltaic micro‐sprinkler irrigation project (PRECIS), with only 11 deemed suitable for irrigation, highlighting the difficulty in achieving the required flow rate of 5 m3/h. To enhance the robustness of the study, additional data from 205 high‐yield boreholes provided by the Office National de l'Eau et de l'Assainissement (ONEA) were incorporated. These boreholes, primarily intended for potable water supply, had flow rates often exceeding 5 m3/h. This extensive dataset was crucial in identifying significant predictors of the project flow rate (Qproj), including the flow rate at the end of drilling (QEndBorh) and lithological factors. The predictive model combining QEndBorh and lithological data explained 73.7% of the variance in Qproj, with an adjusted coefficient of determination (R2adj) of 72.4%. The CART (classification and regression tree) regression model effectively identified branches with flow rates suitable for irrigation, such as Terminal Node 3 with a predicted Qproj of 6.67 m3/h and Terminal Node 4 with a predicted Qproj of 10.5 m3/h, demonstrating the model's robustness. These findings underscore the necessity of detailed lithological assessments and advanced predictive modelling to ensure efficient and reliable borehole drilling for irrigation purposes in regions with complex geological conditions. [ABSTRACT FROM AUTHOR]