Assessing vineyard irrigation uniformity and drip system malfunction by remote and ground sensing: Insights from Sentinel-1, Sentinel-2 and Planet monitoring

This research assesses the efficacy of satellite imagery from Sentinel-1, Sentinel-2, and Planet constellations in monitoring irrigation uniformity and identifying malfunctions in a vineyard's drip irrigation system at farm-level. Utilizing Volumetric Water Content (VWC) from Sentinel-1 and the Normalized Difference Vegetation Index (NDVI) from Sentinel-2 and Planet, this study highlights the potential of remote sensing technologies to optimize irrigation practices and enhance water management in viticulture. Despite erratic behaviour, Sentinel-1 VWC data showed an R-squared of up to 0.83 with catch-cans discharge rate, allowing immediate soil moisture anomaly detection post-irrigation and facilitating early interventions. Meanwhile, NDVI from Sentinel-2 and Planet, with R-squared with catch-cans discharge rate peaking at 0.50 and 0.46, respectively, effectively captured the delayed vegetative responses, crucial for long-term vineyard health monitoring. The results demonstrate the potential of satellite data for deriving the Satellite-Derived Uniformity Coefficient (SDCU) and the Satellite-Derived Low-Quarter Distribution Uniformity (SDDULQ), enabling a faster and more efficient assessment of irrigation uniformity. Among them, SDCU exhibited a lower bias than in-field CU (7.9 %), whereas SDDULQ showed a higher bias relative to in-field DULQ, reaching approximately 33.8 %. This integrated satellite-based approach substantially improves over traditional manual methods, providing greater efficiency, broader coverage, and enhanced scalability. The findings advocate for a broader application of integrated satellite data to support sustainable agricultural practices, particularly in regions experiencing variable climatic conditions.