Estimating Crop Water Productivity Using Remote Sensing Data at Plot Scale in an Irrigation System: The Case of Chisumbanje and Ratelshoek Estate

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Abstract As a key water user, irrigation is critical to food production and security. The study’s main objective is to estimate crop water productivity using remotely sensed data at a plot scale in an irrigation system. To achieve this, the study assessed the biophysical site-specific factors affecting crop water productivity and irrigation performance in Chisumbanje sugarcane and Ratelshoek wheat farms of the Chipinge district of Manicaland province, Zimbabwe. This study estimated and compared the spatial distribution of seasonal actual evapotranspiration (ETa) of sugarcane and wheat for two contrasting irrigation schemes using the Surface Energy Balance Systems algorithms (SEBS) and WaPOR-derived products from 2012 to 2020. The results show substantial seasonal variation in actual evapotranspiration, with the maximum ETa in the summer season of 9 mm/day, a minimum of 3.98 mm/day in the winter season, and a mean ETa of 5.85 mm/day and a standard deviation of 2.02 mm/day. The actual evapotranspiration is high (>7.5 mm/day) in September, October, and December. The spatial–temporal variability of ETa maps in the Chisumbanje sugarcane estate and Ratelshoek wheat estate reveals that the sugarcane estate has higher ET values than the wheat estate. The findings from SEBS and WaPOR were used to assess the crop water productivity in both estates. Crop water productivity (CWP) varies from 2.4–3.0 kg m−3 (for wheat) to 1.2–1.6 kg m−3 (sugarcane). The findings from this research demonstrate the potential for irrigation managers to use remote sensing-based models to monitor irrigation water usage for efficient and sustainable use of water resources.

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