Estimation of Irrigation Needs by Monitoring Crop Rotations and Phenology of Tomato in Southern Italy

In the Mediterranean environment, water scarcity has always been a structural constraint to the availability of arable land: the current water crisis and the effects of climate change with increasing temperatures, and the different rainfall regime and its increased variability, require the adoption of measures to maximize water use in agriculture. 
Particular attention must be paid to the irrigated cropping systems, whose water requirements represent about 60% of the entire water demand; it is essential to encourage both infrastructural interventions and new policies that increase the resilience of supply systems, to promote the use of alternative water resources, while implementing more efficient irrigation practices.
In this context is the research project “EarTH Observation for the Early forecasT of Irrigation needsS (THETIS),” that aims to build a spatial decision support system (SDSS) capable of providing, at the watershed scale, estimates of crop water needs to water supply and management agencies with the goal of improving services to farmers. 
The components of the SDSS are: i) a hydrological model (HM); ii) a crop growth model (CGM); iii) Earth observation (EO) data; iv) artificial intelligence (AI) techniques. Earth observation data were used to estimate the transplanting dates of processing tomato in the study area in the province of Foggia, Southern Italy. Sentinel 2 images from the Copernicus constellation were used to calculate the Leaf Area Index of tomato fields from 2000 to 2024, utilizing the biophysical processor in ESA's SNAP application. Additionally, in District 6/B of the CBC, the crop rotations (crop sequences in the same field), were studied to evaluate the occurrence of tomato, as reported by the CBC during in situ surveys in the same period.
The results of the phenological study using LAI data from Sentinel 2 showed that about 50% of tomato fields are transplanted around 15th May and the other half around 15th June. Regarding crop rotations of the 857 monitored tomato fields, 94.2% were found to return to tomato cultivation after 2, 3, and 4 years, with percentages of 35.1, 40.0, and 21.2, respectively.
This study will allow early identification of likely tomato fields (spatial position and area) on 1st April of each year for the THETIS project; these fields are then associated with soil characteristic parameters and forecast weather data to start the simulation of the entire irrigation district with the Aquacrop crop model in the Python version, to serially simulate the predicted fields and estimate irrigation requirements.

Acknowledgment: The project “EarTH Observation for the Early forecasT of Irrigation needS” (THETIS) is funded by ASI under the Agreement N. 2023-52-HH.0 in the framework of ASI’s program “Innovation for Downstream Preparation for Science” (I4DP_SCIENCE). 

References
M. Rinaldi, et al., “A crop model for large scale and early irrigation requirements estimation”, Proc. of the 2024 IEEE International Geoscience and Remote Sensing Symposium, pp. 2807- 2810, DOI: 10.1109/IGARSS53475.2024.10640683.
G. Satalino, et al., “Earth observation for the early forecast of irrigation needs”, Proc. of the 2024 IEEE International Geoscience and Remote Sensing Symposium, pp. 4912- 4915, DOI: 10.1109/IGARSS53475.2024.10642240.