Water scarcity is one of the foremost concerns for the agricultural sector due to limited water resources, increasing water demand, and climate change. Currently, the agricultural sector accounts for 70% of global freshwater withdrawals, and an increase in freshwater withdrawals and use for irrigation is already expected by 2050. In this study, the impact of climate change on crop water demands, and yield losses due to water shortage, were assessed using the Simulation of Evapotranspiration of Applied Water model. This crop-soil–water model was implemented in a typical Mediterranean environment (Sardinia, Italy) across a full range of relevant crops (wheat, barley, sugar beet, potato, lentil, almond, maize, wine grape, table grape, tomato, artichoke, alfalfa, olive, irrigated pasture, and orange). The simulations were driven by climate data from five earth system models dynamically downscaled at 11 km with regional climate models and available from EURO-CORDEX for baseline (1976–2005) and future (2036–2065) climate conditions under RCP2.6, RCP4.5 and RCP8.5 scenarios. Results show that wheat and barley will foresee the most significant increase in water demand of 12%, 13%, and 14% under RCP2.6, RCP4.5 and RCP8.5, respectively, based on the ensemble mean of the climate models. Water demand for almond, maize, wine grape, and pasture were projected to increase by about 5%, 7%, and 4% under RCP2.6, RCP4.5, and RCP8.5, respectively. The increasing crop water demand represents a considerable challenge for water resource management, especially considering the shortage of water supplies and increasing competition with other sectors. This work provides a wide climate risk evaluation across most relevant crops in the Mediterranean environment to support policymakers in developing adaptation strategies and sustainable regional plans, to support food and water securities.

Abstract Climate variability in Colombia threatens water supplies for rice and other crops, highlighting the urgent need for efficient irrigation techniques. This study was conducted over three growing seasons in the Tolima region and evaluated three irrigation techniques: cascade distribution (CD), multiple inlet rice irrigation (MIRI), and alternate wetting and drying combined with MIRI (AWD + MIRI). The focus was on optimizing water usage, sustaining grain yield, and leveraging vegetation indices for irrigation monitoring. Key findings revealed that visual soil moisture monitoring in light-textured soils enabled substantial irrigation reductions. MIRI reduced water usage by 22%–54%, while AWD + MIRI achieved reductions of 48%–65% compared to CD, with no significant grain yield loss. CD, however, demonstrated the lowest water productivity. Vegetation indices measured peaked during the reproductive stage, aligning with maximum biomass. Notably, MIRI consistently exhibited superior vegetation index values, particularly in growing season 2 (GS2) and growing season 3 (GS3), whereas CD underperformed. Variability analyses highlighted Greener area (GGA) as a more sensitive index, whereas Normalized Difference Vegetation Index (NDVI) demonstrated a lower capacity to capture crop variability for irrigation monitoring. These findings emphasize that adopting the most water-efficient irrigation method identified in this study, AWD + MIRI, coupled with GGA monitoring, can enhance water use efficiency without compromising yield. This approach offers a sustainable path forward for Colombian rice cultivation under the growing pressures of climate variability.

Abstract In recent decades, plant-based sensors have been increasingly used to monitor plant water status, detecting water stress and improving irrigation scheduling. Among these sensors, microtensiometer (MT) continuously measures trunk water potential (TWP) supporting real-time monitoring of TWP and in turn plant water need assessment. However, MT response to environmental stimuli as mediated by plant has not yet fully elucidated. This study reports on a two-year experiment modelling the response of MT-based TWP to changing soil water content (SWC) and air vapor pressure deficit (VPD). During summer time, at a commercial kiwifruit vineyard, vines (n = 63) were differentially irrigated (100%, 50%, 25% of full irrigation need) for ~ 52 days and grouped in CTRL, Mild and Severe, respectively. In two vines per group, the TWP was monitored using MT (20-min interval). Parallel VPD and SWC (× 3 FDR probes) were also recorded. During the experiments drought stressed vines were recovered. Across treatments, soil moisture ranged from approx. 40% to 18%, and the corresponding TWP from approx. – 0.01 to – 1.1 MPa. Results show that a piecewise linear regression model explains the relationship between MT-based TWP and the pressure chamber-based stem water potential (SWP) (R 2 = 0.78) showing different slopes when SWP drops below – 1.6 MPa. The response of TWP to changing VPD and SWC was analyzed at daily scale and throughout the season. A model accounting for time-lag between TWP and VPD and for the hysteresis of TWP shows that the diurnal TWP is mostly driven by VPD (R 2 = 0.74) in well-irrigated vines. To explain TWP response in Mild and Severe irrigation treatment, the model also included the SWC term achieving R 2 = 0.66. Potential application of MT for irrigation management along with some limitations (e.g., long-term durability) are also discussed.