Potential of Irrigated Crop Water Productivity Mapping to Improving Food and Water Security around Lake Bam, Northwest Burkina Faso

Abstract

Pressure on water resources is increasing worldwide due to constantly growing population. This study aims to develop a spatial model and demonstrate its utility for water productivity mapping (WPM) in a smallholder informal irrigation system around Lake Bam (Burkina Faso) with emphasis on tomato. The study involved three major steps leading to WPM: (1) Sentinel-2 (S-2) data were used for crop productivity mapping involving crop classification with random forest algorithm, crop yield modelling with remote sensing (RS) indices, and yield model extrapolation to a larger area; (2) crop water use estimation by multiplying the irrigated surface area by the actual seasonal evapotranspiration developed through the surface energy balance model ‘METRIC’ with Landsat8 (L8) data; and (3) WPM produced by dividing raster layers of the two steps above. An overwhelming 89.46% (769.16 ha) of irrigated tomato area for the season 2016–2017 falls in low WP category of 2.5 kg.m-3 or less. Only 10.5% of the tomato cultivated area had a WP value of 2.5 kg.m-3 or higher. About 82.05% of the tomato area had values lower than 1.63 kg.m-3. The results imply that there is significant scope for increasing WP without having to increase cultivated area or quantity of water utilised. The areas of low WP are spatially pin-pointed and can be used as focus for WP improvements through better land and water management practices.