EGU23-5186, updated on 22 Feb 2023
https://doi.org/10.5194/egusphere-egu23-5186
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Precision Irrigation Scheduling through High Frequency Data Monitoring. Implementation in Apple Orchard Cultivations - central Greece.

Ioannis Tsakmakis1, Konstantinos Babakos1, Anna Chatzi1, Vassilios Pisinaras1, Cosimo Brogi2, Heye Bogena2, Olga Dombrowski2, and Andreas Panagopoulos1
Ioannis Tsakmakis et al.
  • 1Soil and Water Resources Institute, Hellenic Agricultural Organization “DEMETER”, Sindos-Thessaloniki, Greece (a.panagopoulos@swri.gr)
  • 2Agrosphere (IBG-3), Institute of Bio- and Geosciences, Forschungszentrum Jülich GmbH, Jülich, Germany (h.bogena@fz-juelich.de)

Pinios River Basin in central Greece (PRB) is region of highly productive agriculture where irrigation intensification and climate change have caused a significant depletion of groundwater resources. In the framework of the EU-Horizon 2020 project ATLAS, a precision irrigation scheduling service has been developed that aims at improving irrigation water management at the field scale. Such service is intended to protect crops from water stress by keeping the soil moisture (SM) in the root zone above the maximum allowable deficit (MAD). The presented approach is developed in two highly instrumented apple orchard pilot fields (~1.2 ha extent each) located at the Pinios Hydrologic Observatory ILTER site in PRB. In each pilot field and for two consecutive cultivation periods (2021 and 2022), intensive monitoring of meteorological parameters plus SM in 12 locations and at three depths (5, 20, 50 cm) was performed. To determine the time and volume of the next irrigation event, the forecast of meteorological variables for the next six days provided by the Global Forecast Model (GFS) was included in the service. The irrigation service performance was evaluated via comparison of the model estimated crop evapotranspiration (ETc) values against the SM content distribution monitored by the cluster of the installed SM sensors. The potential service contribution to reduce irrigation water consumption was assessed via comparison of the modelled irrigation water demands against the actual water consumption monitored at the irrigation blocks that divide each field. Statistical metrics demonstrate a good agreement between modeled crop evapotranspiration (ETc) and the monitored SM dynamics as captured by the SM sensors. Comparisons between the calculated irrigation demands and the actual water consumption monitored at the irrigation blocks of the pilot fields show that irrigation water applied in the fields may be reduced from 15% up to 50% or more in some instances, without considerably impacting crop health and yield. On the contrary, significant gains may be achieved on water saving and consequently on energy consumption to abstract irrigation water, thus contributing considerably to the region’s water-energy-food nexus sustainability.

How to cite: Tsakmakis, I., Babakos, K., Chatzi, A., Pisinaras, V., Brogi, C., Bogena, H., Dombrowski, O., and Panagopoulos, A.: Precision Irrigation Scheduling through High Frequency Data Monitoring. Implementation in Apple Orchard Cultivations - central Greece., EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-5186, https://doi.org/10.5194/egusphere-egu23-5186, 2023.