Articles
IrriDesk: an automatic irrigation decision support system which integrates crop modelling with sensors and remote sensing data
Article number
1409_19
Pages
135 – 142
Language
English
Abstract
Precision irrigation is the key to driving water use efficiency.
The aim of this research was to demonstrate the suitability of a decision support system (DSS) built under the emerging paradigm of the Internet of Things (IoT) and digital twins for the automated scheduling of irrigation of a commercial vineyard.
The system incorporated the adoption of a regulated deficit irrigation (RDI) strategy and the assimilation in near real time of estimates of Sentinel-2 biophysical variables.
In addition, simulations of water balance variables such as actual evapotranspiration (ETa) obtained from the digital twin were compared with remote sensing surface energy balance (SEB) estimations.
The Sentinel-2 fraction of absorbed photosynthetically active radiation (FAPAR) was regressed with the modelled daily fraction of intercepted PAR (FIPAR), giving a root-mean-square deviation (RMSD) of 0.21 and 0.13 for rows oriented at 140 and 100°, respectively.
An adaptive response of the DSS system allowed spontaneous adjustments and the application of different amounts of water in different irrigation sectors in order to maintain the predefined levels of water status throughout the growing season.
Simulations of the ETa obtained with the digital twin compared with that estimated through remote sensing SEB models showed an RMSD of 0.98 mm day‑1.
The aim of this research was to demonstrate the suitability of a decision support system (DSS) built under the emerging paradigm of the Internet of Things (IoT) and digital twins for the automated scheduling of irrigation of a commercial vineyard.
The system incorporated the adoption of a regulated deficit irrigation (RDI) strategy and the assimilation in near real time of estimates of Sentinel-2 biophysical variables.
In addition, simulations of water balance variables such as actual evapotranspiration (ETa) obtained from the digital twin were compared with remote sensing surface energy balance (SEB) estimations.
The Sentinel-2 fraction of absorbed photosynthetically active radiation (FAPAR) was regressed with the modelled daily fraction of intercepted PAR (FIPAR), giving a root-mean-square deviation (RMSD) of 0.21 and 0.13 for rows oriented at 140 and 100°, respectively.
An adaptive response of the DSS system allowed spontaneous adjustments and the application of different amounts of water in different irrigation sectors in order to maintain the predefined levels of water status throughout the growing season.
Simulations of the ETa obtained with the digital twin compared with that estimated through remote sensing SEB models showed an RMSD of 0.98 mm day‑1.
Authors
J. Bellvert, A. Pelechá, M. Pamies-Sans, J. Virgili, J. Casadesús
Keywords
precision irrigation, digital twin, evapotranspiration, Sentinel-2 FAPAR
Online Articles (64)