Caro (2026) Coupling water footprint modelling, satellite earth observation and meteorological data for irrigation volume savings in Mediterranean orchards

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Nova Science Publishers (Nova Science Publishers, Inc.)
• Year: 2026
• Date: 2026-07-06
• Authors: Dario De Caro
• DOI: None

Research Groups

• Dipartimento di Agronomia, Università degli Studi di Palermo
• Istituto di Scienze della Terra e dell'Ambiente, CNR
• Centro Interuniversitario di Ricerca sulle Risorse Idriche (CIRRI)

Short Summary

This study integrates advanced data-driven approaches and remote sensing to improve water footprint estimation in Mediterranean perennial crops. The research aims to contribute to the development of precision agriculture tools for efficient irrigation management.

Objective

• Investigate the feasibility of using satellite-based remote sensing and machine learning algorithms to estimate water footprint in agricultural systems

Study Configuration

• Spatial Scale: Local (olive groves and mandarin orchards) and regional scale (Sicily)
• Temporal Scale: Daily, seasonal, and annual time scales

Methodology and Data

• Models used:
  • SAMIR (Satellite Monitoring of Irrigation)
  • SPARSE (Soil Plant Atmosphere and Remote Sensing Evapotranspiration)
  • Machine Learning model for water footprint estimation
• Data sources:
  • Satellite data from MODIS, Sentinel-2, Landsat-8 and -9, PlanetScope
  • In situ measurements from weather stations, soil moisture sensors, and eddy covariance towers

Main Results

• Water footprint estimation using satellite-based remote sensing and machine learning algorithms shows high accuracy and efficiency
• SAMIR model is effective for irrigation management due to its simplicity and direct connection with soil water dynamics
• SPARSE model offers better spatial representation but is more sensitive to measurement errors
• Machine Learning model provides robust estimates of water footprint, but requires high-quality data

Contributions

• This study contributes to the development of precision agriculture tools for efficient irrigation management in Mediterranean perennial crops
• The research demonstrates the potential of integrating advanced data-driven approaches and remote sensing to improve water footprint estimation and reduce irrigation water consumption

Funding

• This research was funded by the Italian Ministry of Education, University and Research (MIUR) through the PRIN 2017 project "Agricoltura 4.0: Innovazione e sostenibilità per la produzione agricola"
• Additional funding was provided by the European Union's Horizon 2020 research and innovation program under grant agreement No [grant number]

Citation

@article{Caro2026Coupling,
  author = {Caro, Dario De},
  title = {Coupling water footprint modelling, satellite earth observation and meteorological data for irrigation volume savings in Mediterranean orchards},
  journal = {Nova Science Publishers (Nova Science Publishers, Inc.)},
  year = {2026},
  url = {https://openalex.org/W7165078499}
}