Water Uptake Rates Estimation from Sentinel-1 C-band Synthetic Aperture Radar over Olive Orchards

Monitoring the water-uptake rate (WUR) in olive orchards is a key parameter for improving irrigation efficiency and represents an indicator of tree health and yield. Commercial olive orchards extend over large areas and therefore, the use of in-situ sensors to monitor tree WUR, such as the installation of sap flow meters, which are costly and time-consuming to install, are not feasible. The aim of this study is to investigate the potential of C-band Synthetic Aperture Radar (SAR) data acquired by Sentinel-1 with 6-days revisit time to estimate the WUR in very high-density olive orchards in the hot and arid desert climate of Saudi Arabia. A random forest regression (RFR) model was used to calibrate the SAR-derived metrics against WUR measurements recorded by sap flow meters in six plots in 2019, 2020, and 2021. Later, SAR-derived metrics and the coincident WUR measurements were used for RFR optimization and validation. A SAR-derived metric to predict the WUR in a plot at a given Sentinel-1 acquisition date was the difference between the SAR backscattering at that image date and the average SAR backscattering in the second-half of January, when WUR was negligible (around 0.1 L.h-1). The optimized RFR approach provided an accurate estimate of WUR (R² = 0.86, RMSE = 0.13 [L.h^-1]). The optimized RFR was used to operationally map the WUR at the plot level between 2019 and 2021 with a revisit time of 6 days. Results showed that the average WUR over the mapped area co-varied with the average daily air temperature (R² = 0.82) and inversely co-varied with the average daily air humidity (R² = 0.58), both recorded by a weather station installed at the study site. These observations support the operational mapping results as they are consistent with the principle of soil-plant-atmosphere interactions, where the WUR generally increases with air temperature and decreases with air humidity. Future work should focus on the assimilation of SAR-derived WUR into water-use models to evaluate the added value of SAR-derived WUR for water resource management in olive orchards.