Improving evapotranspiration computation with electrical resistivity tomography in a maize field

Hydrogeophysical methods have been increasingly used to study subsurface soil-water dynamics, yet their application beyond the soil compartment or the quantitative link to soil hydraulic properties remains limited. To examine how these methods can inform model-based evapotranspiration (ET) calculation under varying soil water conditions, we conducted a pilot-scale field study at an experimental maize plot with manipulated irrigation treatments. Our goal was to develop a workflow for (1) acquiring and inverting field electrical resistivity tomography (ERT) data, (2) correlating ERT to soil hydraulic properties, (3) spatially characterizing soil water stress that feeds into ET modeling (the FAO-56 model), and (4) evaluating the performance of ERT-based ET computation. Our results showed that ERT was able to capture decimeter-scale soil water content (SWC) dynamics from root water uptake and irrigation manipulation and the contrast of soil water stress between deficiently and fully irrigated maize. We also demonstrated the flexibility of using ERT to spatially integrate soil water stress in the soil volume of interest, which could be adjusted based on different crops and plot layouts. The integration of the ERT datasets into ET modeling provided insights into the spatial heterogeneity of the subsurface that has been challenging for point-based sensing, which can further our understanding of the hydraulic dynamics in the soil-plant-atmosphere continuum. Electrical resistivity tomography (ERT) captured soil water dynamics induced by root water uptake and irrigation manipulation.ERT enabled spatial analysis and quantification of soil water stress, a key input to the evapotranspiration (ET) model.A workflow from field ERT data acquisition to ET computation was demonstrated.