Estimating Crop Evapotranspiration Variability in Processing Tomatoes Using High-Resolution Aerial Imagery and pySEBAL Algorithm

Abstract

In the pursuit of optimizing use of limited water resources in agriculture, leveraging high-resolution aerial imagery to estimate ETa (actual crop evapotranspiration) is of interest to farmers and water managers. However, there remains a dearth of information regarding the efficacy of energy balancing algorithms—initially developed for satellite remote sensing for estimating ETa from aerial imagery. This study presents an approach that estimates ETa for processing tomatoes employing high-resolution aerial data and the pySEBAL (Surface Energy Balance Algorithm for Land) remote sensing algorithm. During the 2021 growing season, an aircraft captured multispectral and thermal imagery over a processing tomato farm near Esparto, California, USA. Simultaneously, low-frequency biometeorological data essential for energy balance assessment, along with high-frequency turbulent fluxes, were measured by an eddy covariance flux tower installed within the field. Extensive evaluation of ETa and other energy balance components showed that pySEBAL produced accurate, high-resolution estimates of ETa. The root mean square error (RMSE) for the energy balance components were as follows: 33 Wm-2 for the latent heat flux, 29 Wm-2 for the sensible heat flux, 24 Wm-2 for the net radiation, and 10 Wm-2 for the soil heat flux. Moreover, the RMSE for ETa was 0.26 mm d-1. Notably, each component exhibited an R2 value exceeding 0.92. Furthermore, the ETa mapping of the processing tomato field delineated spatial variability linked to irrigation schedules, crop development, areas affected by disease, and soil heterogeneity, visually representing these aspects. This research underscores the pivotal role of high-resolution spatial aerial imagery and the pySEBAL algorithm in estimating ETa variability within fields, demonstrating high potential for improving precision irrigation management and maximizing the judicious utilization of water resources in agriculture.