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Widespread dieback of Fagus sylvatica has been observed in several areas of Sicily (Italy) in recent decades, often associated with Biscogniauxia nummularia infections. However, the primary drivers of this decline remain debated, with climate change increasingly recognized as a key factor not only in exacerbating tree physiological stress but also in enhancing susceptibility to pathogens. This study addresses this gap by quantifying the impact of climate change on beech decline in the Nebrodi Regional Park using an integrated approach that combines climate reanalysis data (ERA5-Land) and remote sensing (Landsat imagery). Analysis of climatic trends between two climate normals (1961–1990 and 1991–2020) revealed significant increases in temperature, evapotranspiration, and solar radiation, coupled with a decline in relative humidity. NDVI trends indicate a progressive loss of beech vigor since 2009, strongly correlated with decreasing soil moisture and precipitation. Although forest cover has expanded, this does not necessarily indicate improved forest health, as persistent climate stress may compromise tree vitality and increase vulnerability to secondary pathogens such as B. nummularia. These findings highlight the need for adaptive forest management strategies, including selective thinning and species diversification, to enhance resilience against climate change. Future research should prioritize high-resolution satellite imagery (e.g., Sentinel-2) and in situ physiological measurements (e.g., leaf water potential and sap flow) to refine early detection of climate-induced stress and improve conservation strategies for Mediterranean beech forests.

The technological advances of remote sensing (RS) have allowed its use in a number of fields of application including plant disease depiction. In this study, an RS approach based on an 18-year (i.e., 2001–2018) time-series analysis of Normalized Difference Vegetation Index (NDVI) data, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and processed with TIMESAT free software, was applied in Sicily (insular Italy). The RS approach was carried out in four orchards infected by Citrus tristeza virus (CTV) at different temporal stages and characterized by heterogeneous conditions (e.g., elevation, location, plant age). The temporal analysis allowed the identification of specific metrics of the NDVI time-series at the selected sites during the study period. The most reliable parameter which was able to identify the temporal evolution of CTV syndrome and the impact of operational management practices was the “Base value” (i.e., average NDVI during the growing seasons, which reached R2 values up to 0.88), showing good relationships with “Peak value”, “Small integrated value” and “Amplitude”, with R2 values of 0.63, 0.70 and 0.75, respectively. The approach herein developed is valid to be transferred to regional agencies involved in and/or in charge of the management of plant diseases, especially if it is integrated with ground-based early detection methods or high-resolution RS approaches, in the case of quarantine plant pathogens requiring control measures at large-scale level.

The use of hydrogeophysical methods provides insights for supporting optimal irrigation design and management. In the present study, the electrical resistivity imaging (ERI) was applied for monitoring the soil water motion patterns resulting from the adoption of water deficit scenarios in a micro-irrigated orange orchard (Eastern Sicily, Italy). The relationship of ERI with independent ancillary data of soil water content (SWC), plant transpiration (T) and in situ measurements of hydraulic conductivity at saturation (Ks, i.e., using the falling head method, FH) was evaluated. The soil water motion patterns and the maximum wet depths in the soil profile identified by ERI were quite dependent on SWC (R2 = 0.79 and 0.82, respectively). Moreover, ERI was able to detect T in the severe deficit irrigation treatment (electrical resistivity increases of about 20%), whereas this phenomenon was masked at higher SWC conditions. Ks rates derived from ERI and FH approaches revealed different patterns and magnitudes among the irrigation treatments, as consequence of their different measurement scales and the methodological specificity. Finally, ERI has been proved suitable for identifying the soil wetting/drying patterns and the geometrical characteristics of wet bulbs, which represent some of the most influential variables for the optimal design and management of micro-irrigation systems.

An adjusted satellite-based model was proposed with the aim of improving spatially distributed evapotranspiration (ET) estimates under plant water stress conditions. Remote sensing data and near surface geophysics information, using electrical resistivity tomography (ERT), were used in a revised version of the original dual crop coefficient (Kc) FAO-56 approach. Sentinel 2-A imagery were used to compute vegetation indices (VIs) required for spatially estimating ET. The potentiality of the ERT technique was exploited for tracking the soil wetting distribution patterns during and after irrigation phases. The ERT-derived information helped to accurately estimate the wet exposed fraction (few) and therefore the water evaporated from the soil surface into the dual Kc FAO-56 approach. Results, validated by site-specific ET measurements (ETEC) obtained using the eddy covariance (EC) technique, showed that ERT-adjusted ET estimates (ETERT) were considerably reduced (15%) when compared with the original dual Kc FAO-56 approach (ETFAO), soil evaporation overestimation being the main reason for these discrepancies. Nevertheless, ETFAO and ETERT showed overestimations of 64% and 40% compared to ETEC. This is because both approaches determine ET under standard conditions without water limitation, whereas EC is able to determine ET even under soil water deficit conditions. From the comparison between ETEC and ETERT, the water stress coefficient was experimentally derived, reaching a mean value for the irrigation season of 0.74. The obtained results highlight how new technologies for soil water status monitoring can be incorporated for improving ET estimations, particularly under drip irrigation conditions.

Modeling soil-water regime and solute transport in the vadose zone is strategic for estimating agricultural productivity and optimizing irrigation water management. Direct measurements of soil hydraulic properties, i.e., the water retention curve and the hydraulic conductivity function, are often expensive and time-consuming, and represent a major obstacle to the application of simulation models. As a result, there is a great interest in developing pedotransfer functions (PTFs) that predict the soil hydraulic properties from more easily measured and/or routinely surveyed soil data, such as particle size distribution, bulk density (ρb), and soil organic carbon content (OC). In this study, application of PTFs was carried out for 359 Sicilian soils by implementing five different artificial neural networks (ANNs) to estimate the parameter of the van Genuchten (vG) model for water retention curves. The raw data used to train the ANNs were soil texture, ρb, OC, and porosity. The ANNs were evaluated in their ability to predict both the vG parameters, on the basis of the normalized root-mean-square errors (NRMSE) and normalized mean absolute errors (NMAE), and the water retention data. The Akaike’s information criterion (AIC) test was also used to assess the most efficient network. Results confirmed the high predictive performance of ANNs with four input parameters (clay, sand, and silt fractions, and OC) in simulating soil water retention data, with a prediction accuracy characterized by MAE = 0.026 and RMSE = 0.069. The AIC efficiency criterion indicated that the most efficient ANN model was trained with a relatively low number of input nodes.

This paper reports a study on the performance of a multistage constructed wetland (CW) system adopted for winery wastewater and on the analysis of its suitability for irrigation reuse. The CW system treats about 3 m3·day−1 of wastewater produced by a small winery located in Sicily (insular Italy). Wastewater samples were collected at the CW inlet and outlet for physical–chemical and microbiological quality characterization. CW efficiency was evaluated on the basis of water quality improvement and of the achievement of Italian and EU irrigation reuse regulation limits. The CW system showed Chemical Oxygen Demand (COD) and Total Suspended Solids (TSS) mean removal rates of about 81% and 69%, and a maximum removal of about 99% (for both COD and TSS) occurred during grape harvest phase. The CW removal efficiencies for nutrients were 56% for TN and 38% for PO4-P, considering their low average concentrations at CW inlet. The CW system evidenced an effluent average quality compatible with the limits imposed by the Italian regulation and EU proposal regulation on the minimum requirement for water reuse. The CW vegetated area showed regular growth and vegetative development; phytotoxicity phenomena were not detected. The results of the study suggest the important role of CW systems in the treatment of winery wastewater and for their subsequent reuse in agriculture.

Accurate estimation of actual crop evapotranspiration (ETa) is crucial for effective irrigation management, especially in regions facing growing water scarcity. This study evaluates the performance of the Simple Algorithm for Evapotranspiration Retrieving (SAFER) in a Mediterranean citrus orchard using remote sensing and Eddy Covariance (EC) data. The model was calibrated using local flux tower data from 2021 to 2022. The results show strong agreement between observed and modeled ETa during the wet season, with excellent statistical metrics (R2 = 0.89 and 0.85; r = 0.95 and 0.92; RMSE = 0.95 mm day−1 and 0.91 mm day−1; bias = −0.94 mm day−1 and 0.53 mm day−1 for 2021 and 2022, respectively), confirming the reliability of SAFER under well-watered conditions. However, the model performance decreased significantly during the dry season, R2 = 0.352 and 0.167; r = −0.593 and 0.408; RMSE = 0.86 mm day−1 and 0.68 mm day−1; bias = 0.01 mm day−1 and 0.38 mm day−1 for 2021 and 2022, respectively, likely due to the limited capacity of vegetation indices to detect plant physiological stress under water deficit conditions. SAFER detected spatial variability in ETa across the orchard, highlighting its potential for irrigation zoning. Comparisons with studies in tropical and semi-arid regions demonstrated consistency in mid-season ETa estimates, supporting the model’s adaptability. Despite reduced accuracy under drought conditions, SAFER remains a cost-effective and reliable tool for ETa monitoring during optimal growth periods. Overall, it shows strong potential as a remote sensing-based tool for sustainable crop management, though dry-season applications require additional stress-adjustment factors.

This paper presents the results of an experiment carried out in Southern Italy (Sicily) on the estimation evapotranspiration (ET) in pilot constructed wetlands planted with different species (Chrysopogon zizanioides, Myscanthus x giganteus, Arundo donax, Phragmites australis, and Cyperus papyrus). In the two monitored growing seasons, reference ET0 was calculated with the Penman-Monteith formula, while actual ET and crop coefficients were measured through a water balance and the FAO 56 approach, respectively. The highest average seasonal ET value was observed in Phragmites australis (17.31 mm d−1) followed by Arundo donax (11.23 mm day−1) Chrysopogon zizanioides (8.56 mm day−1), Cyperus papyrus (7.86 mm day−1), and Myscanthus x giganteus (7.35 mm day−1). For all plants, crop coefficient values showed different patterns in relation to growth stages and were strongly correlated with phenological parameters. Myscanthus x giganteus and Arundo donax showed a water use efficiency values significantly higher than those observed for the other tested species. Results of this study may contribute to select appropriate plant species for constructed wetlands located in semi-arid regions, especially when the use of reclaimed water and/or the use of aboveground biomass are planned.

This study reports an up-to-date summary of the principal barriers still limiting reclaimed water use for agriculture in Italy, and particularly in Sicily. Moreover, it provides a geographic informative system (GIS)-based procedure for evaluating the potential treated wastewater (TW) reuse in the Sicilian region as a decision support system for its management. The survey, based on possible economic, morphologic, and design solutions, evidenced a feasible integration of several wastewater treatment plants (WWTPs) with irrigation areas, allowing the water availability enhancement. Overall, the potential volume of TW by WWTPs (connected to irrigation districts) is 163 × 106 m3 year−1, while the water deficit is 66 × 106 m3 year−1. The feasibility of TW reuse in Sicily was also analysed at the light of the World Health Organization microbial risk assessment. Escherichia coli (E. coli) analyses mostly accomplished these guidelines while conflicting with the restrictive Italian standards. Despite several limiting factors (restrictive legislations, high distance and unfavourable slope between WWTPs and irrigable areas, high monitoring and distribution costs) still hamper the exploitation of reclaimed water use in Sicilian agriculture, some solutions were identified to implement this practice.

The study aims to identify the responses of citrus orchards (C. sinensis (L.) Osbeck), grown under typical Mediterranean climatic conditions, to deficit irrigation (DI) regimes applied over more than a decade (2010-2020). In particular, the DI regimes were declined at the study site in terms of sustained deficit irrigation, regulated deficit irrigation, partial drying of the root-zone, with increasing severity of the water deficit, from 25% to 50% of the crop evapotranspiration, using surface and sub-surface micro-irrigation techniques. Long-term monitoring was set up for identifying the main processes acting at the soil-plant-atmosphere continuum (SPAC) level through direct in situ measurements of mass and energy fluxes (i.e., via micrometeorological technique) and the estimation of ETc and transpiration fluxes (i.e., via sap flow method), and the soil-plant-water processes (via geoelectrical techniques). In addition, the main physiological, qualitative, and quantitative parameters were evaluated since the beginning of the experiment. The results of the long-term experiment demonstrated the great adaptability of the crop species to sustain even the highest water reductions without substantial alterations of the main marketable productive and qualitative characteristics, evidencing the importance of controlling the SPAC dynamics for correctly applying the water restriction regimes.