,,- Departament of Engineering, IS-FOOD Institute (Innovation & Sustainable Development in Food Chain), Universidad Pública de Navarra, Campus de Arrosadia s/n, 31006 Pamplona, Navarre, Spain. (milton.campero@unavarra.es)
Irrigation uniformity is essential for the efficient use of water and depends on both the design of the irrigation system and the operation of the sprinklers. Manual monitoring of sprinklers is inefficient and prone to errors, which has driven the use of remote sensing technologies for crop monitoring.
This study explored the potential of high-resolution multispectral imagery for the detection of blocked sprinklers in maize fields during the irrigation season. The research was conducted in a field in Larraga (Navarra, Spain), irrigated with sprinklers spaced 15x18 m apart, with three sprinklers randomly blocked for 15 to 25 days during four stages of maize growth. Images captured with an unmanned aerial vehicle (UAV) were subsequently resampled to simulate a 3 m satellite resolution; this approach allowed the generation of complete time series of the Normalised Difference Vegetation Index (NDVI) without interruptions caused by cloud cover, ensuring detailed monitoring of crop development.
The study field was divided into a non-irrigated zone around the blocked sprinklers and a control zone with normal irrigation, allowing comparison of crop development through multitemporal NDVI analysis and time series incorporating daily data on irrigation applied to the field, as well as precipitation and evapotranspiration recorded at the nearest weather station, which allowed assessment of their influence on vegetation dynamics.
The results showed that the images enabled clear identification of areas affected by sprinkler blockage, with significant differences in vegetation indices between the control and non-irrigated areas. Continuously irrigated zones maintained high and stable NDVI values, whereas areas with interruptions showed marked decreases, only partially mitigated by rainfall events in early stages. These findings highlight that irrigation interruption has an adverse effect on crop health, which can be detected accurately using remote sensing tools, emphasising the importance of maintaining uniform irrigation for optimal plant development.
How to cite: Campero-Taboada, M. J., Casalí Sarasíbar, J., González-Audícana, M., and Campo-Bescós, M. A.: Identification of Sprinkler anomalies using Multispectral Remote Sensing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11754, https://doi.org/10.5194/egusphere-egu26-11754, 2026.
