<p>Population rise and economic growth put additional pressure on global water resources, especially in the Mediterranean Island states that have a long history of aridity and water management challenges. In Crete, Greece, 81.2% of total water consumption is attributed to the agricultural sector, with olive trees covering 64.2% of the total cultivated land. Simulation and applied studies have shown that Irrigation Decision Support Systems (IDSS) can reduce water consumption from 10 (Fotia et al., 2021) to 34% (Phogat et al., 2014). Here we examine the feasibility of optimizing such a IDSS for deficit irrigation while maintaining olive crop yield. Experiments are conducted in the DRIP Project infrastructure (Daliakopoulos et al., 2020; Petousi et al., 2018) including an olive grove of 90 10 year-old trees and 5 20m3 lysimeters planted with olive trees from the same olive grove. The infrastructure includes a precision irrigation system comprised of FDR soil moisture sensors, microclimatic stations, and smart irrigation schedulers. The CROPWAT model (Smith et al., 2002) is calibrated using data from 5 irrigation treatments ranging from overirrigation to rainfed cultivation. Field measurements included stomatal conductance [mmol cm-2 s-1], relative chlorophyl fluorescence [Fv/Fm], leaf relative water content [%], leaf area [%], pruning weight [kg], and yield [kg]. Results clearly highlight the differences in olive tree physiological parameters in deficit irrigation treatments and the lack of significant yield benefit in over-irrigation, while the modeling study can estimate exact irrigation scheduling for incorporation with the IDSS.</p><p><strong>Acknowledgments</strong></p><p>This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH-CREATE-INNOVATE (project code: T1EDK-03372)</p><p><strong>References</strong></p><p>Daliakopoulos, I. Ν., Papadimitriou, D., Matsoukas, T., Zotos, N., Moysiadis, H., Anastasopoulos, K., Mavrogiannis, I., & Manios, T. (2020). Development and Preliminary Results from the Testbed Infrastructure of the DRIP Project. Proceedings, 30(1), 64.
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https://doi.org/10.3390/w13141954</p><p>Petousi, I., Daliakopoulos, I. N., Matsoukas, T., Zotos, N., Mavrogiannis, I., & Manios, T. (2018). DRIP: Development of an Advanced Precision Drip Irrigation System for Tree Crops. TERRAENVISION s, 1, 2018–2.
https://terraenvision2018.eu/abstracts/export.php?id=269</p><p>Phogat, V., Skewes, M. A., Cox, J. W., Sanderson, G., Alam, J., & Šimůnek, J. (2014). Seasonal simulation of water, salinity and nitrate dynamics under drip irrigated mandarin (Citrus reticulata) and assessing management options for drainage and nitrate leaching. Journal of Hydrology, 513, 504–516.
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