Spatial variability of the green water footprint using a medium-resolution remote sensing technique: The case of soybean production in the Southeast Argentine Pampas

Agriculture accounts for about 70% of the fresh water use in the world, dominating rainfed production systems. As meeting future food demand will require an increase in crop production, new techniques are necessary to monitor the spatial variability of agricultural water use. However, the use of remote sensing for the water footprint estimation is limited. This study aims at evaluating the spatial variability of the soil-water consumption in soybean crops, also termed as green water footprint (WFgreen), in a sector of the Argentine Pampas using satellite data. WFgreen was evaluated at spatial resolution of 250 m, estimating the soil water availability through the evaporative fraction and crop yield from Moderate-Resolution Imaging Spectroradiometer (MODIS/Aqua) data. In the analysed soybean plots, the WFgreen varied from 900 m3 t−1 to 1800 m3 t−1. The preliminary comparison of the method with field measurements showed a RMSE = 494 m3 t−1 and Bias = −410 m3 t−1, respectively. The high spatial variability reflected the heterogeneity of soil-water use efficiency. The proposed technique can be useful to obtain WFgreen maps at medium spatial resolutions (250 m–1000 m). Also, it can be applied in regions with poor ground data coverage to estimate the WFgreen, after a parameterization of the model. The contribution to our understanding of the relationship between soil-water availability, rainfed-crop productivity and then WFgreen is expected. [Display omitted] •The estimation of the Green Water Footprint can be optimized using satellite data•Spatial variability was obtained using evaporative fraction and yield data•The technique allows the calculation of Green Water Footprint at regional scale•It can be a contribution to previous methods for agricultural water use estimation