Walnut is currently grown on over 400 thousand acres in California with the majority of production in the Northern San Joaquin Valley (NSJV). The recurring droughts and climate change in California will likely increase the uncertainty in water supply to walnuts and other specialty crops. Site-specific irrigation is critical to cope with these challenges. Knowing the water use of walnuts is crucial in optimizing irrigation management since it affects nut quality, and productivity. Unlike traditional methods, which are often limited by spatial coverage, high costs, and less precise crop coefficient values, satellite remote sensing offers a cost-effective, widely accessible solution. It enables large-scale evapotranspiration (ET) estimation with increasing adoption in irrigated agriculture, providing a valuable tool for water management. This study compares OpenET models, an open-source database providing ET estimates, against commercial in-situ surface renewal ET sensor. Utilizing OpenET platform provides a good opportunity for growers to improve water use efficiency. Such improvements could lead to the adoption of publicly available irrigation management tools and ensure healthier tree development, better resource utilization, and more resilient orchards in the face of climate change. Based on the data of 2024 season, the Satellite Irrigation Management Support (SIMS) model had the highest accuracy in estimating actual ET when compared to measurements from a commercial in-situ surface renewal system in the orchard, with a mean percent error (MPE) of -18.45%, and R² and mean absolute error (MAE) values of 0.88 and 0.03 inches/d⁻¹, respectively, followed by the Ensemble model. In contrast, the SSEBop model showed the lowest correlation with ETa, with an R² of 0.77 and a relatively high MAE of 0.06 inches, indicating a higher level of uncertainty in its estimates which could potentially lead to over-irrigation if adopted without correction. Based on these findings, growers can confidently incorporate the OpenET SIMS model into their irrigation scheduling, ultimately enhancing water use efficiency. However, further validation through replication over a second year and across multiple sites is essential to substantiate these findings.
