Environmental and Agro-Economic Sustainability of Olive Orchards Irrigated with Reclaimed Water under Deficit Irrigation

This study explores the effects of the adoption of reclaimed water (RW) as source of irrigation in conjunction with the application of deficit irrigation strategies in an olive orchard (different genotypes) located within the “Valle dei Margi” farmhouse (Eastern Sicily). Specifically, the RW was obtained in situ by treating the wastewater coming from the farmhouse throughout a treatment wetland system (TW). The effects of RW on crop water status (CWS) was assessed by conducting plant-based measurements (i.e., leaf water potential, Ψ, and leaves relative water content, RWC) and determining satellite-based biophysical indicators. An economical and environmental evaluation of the proposed sustainable irrigation practices was carried out by using the life cycle assessment (LCA) approach.The RW quality showed high variability due to fluctuations in the number of customers at the farmhouse during the Covid-19 pandemic period. However, high removal efficiency of the overall TW was reached even if the RW quality did not always accomplish with the limits of the Italian regulations. A strong impact in the variation of Ψ was observed among the olive orchard under the different water regimes, evidencing how CWS performances are greatly conditioned by the genotype. However, no differences in leaves RWC and in satellite-based biophysical indicators were detected, despite the severe water deficit imposed (i.e., 50% of irrigation water reduction). Finally, the results of the LCA analysis underlined that the use of RW may permit to obtain important gains both in economic and environmental terms, thus representing a valid strategy for the olive cultivation

Comparing the use of ERA5 reanalysis dataset and ground-based agrometeorological data under different climates and topography in Italy

Study region: The study region is represented by seven irrigation districts distributed under different climate and topography conditions in Italy. Study focus: This study explores the reliability and consistency of the global ERA5 single levels and ERA5-Land reanalysis datasets in predicting the main agrometeorological estimates commonly used for crop water requirements calculation. In particular, the reanalysis data was compared, variable-by-variable (e.g., solar radiation, R-s; air temperature, T-air; relative humidity, RH; wind speed, u(10); reference evapotranspiration, ET0), with in situ agrometeorological obser-vations obtained from 66 automatic weather stations (2008-2020). In addition, the presence of a climate-dependency on their accuracy was assessed at the different irrigation districts. New hydrological insights for the region: A general good agreement was obtained between observed and reanalysis agrometeorological variables at both daily and seasonal scales. The best perfor-mance was obtained for T-air, followed by RH, R-s, and u(10) for both reanalysis datasets, especially under temperate climate conditions. These performances were translated into slightly higher accuracy of ET0 estimates by ERA5-Land product, confirming the potential of using reanalysis datasets as an alternative data source for retrieving the ET0 and overcoming the unavailability of observed agrometeorological data

Assessing the use of ERA5-Land reanalysis and spatial interpolation methods for retrieving precipitation estimates at basin scale

Precipitation data availability plays a crucial role in many climatic, hydrological and agricultural-related applications. In this study, the use of alternative data sources (i.e. interpolation methods and ERA5-Land reanalysis data) was combined for improving the spatially distributed precipitation estimates at the Simeto river basin, located in Eastern Sicily (Italy). A total of 51 rain gauges were used to generate a monthly precipitation dataset for the reference period 2002–2019. Among the 6 tested interpolation methods, Natural Neighbour was the method that predicted precipitation the best at monthly level with a Distance between Indices of Simulation and Observation (DISO) of 0.51. Radial Basis Functions and Inverse Distance Weighting provided the highest precipitation accuracies, respectively, for winter and autumn (with DISO values of 0.44 and 0.50, respectively), and for spring and summer seasons (with DISO values of 0.50 and 0.63, respectively). Underestimations on the ERA5-Land precipitation estimates were observed when compared to the most accurate interpolation methods both at monthly (25%) and seasonal temporal scales (21% in winter and summer, 36% in autumn), with the exception for spring. The performance was significantly improved when the interpolation estimates were corrected with local observations (with RMSD values ranging from 35.29 mm to 26.46 mm at monthly scale, and from 23.33–55.34 mm to 23.15–37.88 mm at seasonal level). The spatial distribution of the estimation errors associated to precipitation obtained from ERA5-Land reanalysis revealed a significant positive correlation (p value <0.05) with the altitude variation in each ERA5-Land cell within the basin under study. These results confirm the good performance on the combined use of alternative precipitation data sources, while adjustments are required to reduce site-specific uncertainties due to local microclimatic conditions occurring at the basin scale.This study was supported by the Italian Ministry for University and Research within the Research Project of National Relevance (PRIN 2017) entitled “INtegrated Computer modeling and monitoring for Irrigation Planning in Italy - INCIPIT”. The authors wish to thank the Servizio Informativo Agrometeorologico Siciliano (SIAS) and the Autorità di Bacino del distretto idrografico della Sicilia and in particular Dr. Luigi Pasotti for providing the observed precipitation data. J.M. Ramírez-Cuesta acknowledges the postdoctoral financial support received from the Juan de la Cierva Postdoctoral Program by the Spanish Ministry for Science and Innovation (IJC2020-043601-I)

Influence of short-term surface temperature dynamics on tree orchards energy balance fluxes

Land surface temperature (LST) plays an essential role in developing and applying precision agriculture protocols, especially for calculating crop evapotranspiration (ETc) by surface energy balance (SEB) approaches; and for determining crop water status. However, LST is quite dependent on the meteorological conditions, which can rapidly vary. This variability, together with the limited meterological data acquisition frequency in most weather stations, can lead to the miscalculation of the SEB components, especially relevant when used for irrigation purposes. The present study assessed the temporal dynamic of LST in a very short period of time (20-minutes) through the acquisition of multiple thermal imagery. Additionally, a combination of SEB approach with Eddy Covariance technique was performed for quantifying the effect that LST variations have on the sensible (H) and latent (LE) heat fluxes. Even under steady meteorological conditions, temporal variations in LST of 3.5 and 4.0 K were observed for tree canopy and sunny bare soil surfaces, respectively. These LST oscillations reached values of about 7.8 and 17.9 K for tree canopies and bare soil when heterogeneous meteorological conditions were observed (i.e. cloud presence). Such LST differences translated into H and LE differences of about 26 and 19%, respectively; with variations up to 5 (for H) and 2.7 times (for LE) under fast-varying meteorological conditions. The obtained results suggest the necessity of acquiring thermal imagery when steady meteorological conditions exist or, otherwise, ensuring the collection of instantaneous meteorological data for applying post-processing corrections. This is of importance when incorporating the obtained ETc maps into precision irrigation protocols.This study was supported by the Research Project of National Relevance (PRIN 2017) titled “INtegrated Computer modeling and monitoring for Irrigation Planning in Italy - INCIPIT”; and by the project PRECIRIEGO RTC-2017-6365-2 financed by AEI with FEDER co-funds. The authors thank the Consiglio per la Ricerca in agricoltura e l’analisi dell’Economia Agraria, Centro di Ricerca Olivicoltura, Frutticoltura e Agrumicoltura (CREA-OFA) for their hospitality at the experimental site. J.M.R.-C. and D.V. acknowledge the postdoctoral financial support received from Juan de la Cierva Spanish Postdoctoral Program (IJC2020-043601-I), and from Programma Operativo Nazionale (PON) “Attraction and International Mobility” (AIM) 1848200-2 initiative, respectively

Electrical resistivity imaging for monitoring soil water motion patterns under diferent drip irrigation scenarios

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 (K, 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 (R = 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. K 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.The authors wish to thank Servizio Informativo Agrometeorologico Siciliano (SIAS) for weather data and the personnel of Centro di Ricerca Olivicoltura, Frutticoltura e Agrumicoltura of the Italian Council for Agricultural Research and Agricultural Economics Analyses (CREA-OFA, Acireale) for their hospitality at the field site. The work was carried out in the frame of the PON Attraction and International Mobility (AIM) 1848200-2 initiative (D.V.). Open access funding provided by Università degli Studi di Catania within the CRUI-CARE Agreemen

A stand-alone remote sensing approach based on the use of the optical trapezoid model for detecting the irrigated areas

Under the current water scarcity scenario, the promotion of water saving strategies is essential for improving the sustainability of the irrigated agriculture. In particular, high resolution irrigated area maps are required for better understanding water uses and supporting water management authorities. The main purpose of this study was to provide a stand-alone remote sensing (RS) methodology for mapping irrigated areas. Specifically, an unsupervised classification approach on Normalized Difference Vegetation Index (NDVI) data was coupled with the OPtical TRApezoid Model (OPTRAM) for detecting actual irrigated areas without the use of any reference data. The proposed methodology was firstly applied and validated at the Marchfeld Cropland region (Austria) during the irrigation season 2021, showing a good agreement with an overall accuracy of 70%. Secondly, it was applied at the irrigation district Quota 102,50 (Italy) for the irrigation seasons 2019–2020. The results of the latter were instead compared with the data declared by the Reclamation Consortium, finding an overestimation of irrigated areas of 21%. In conclusion, this study suggests an easy-to-use approach, eventually independent of reference data such as agricultural statistical surveys or records and replicable under different agricultural settings in continental or Mediterranean climates to support stakeholders for regular estimation of irrigated areas in different growing years or detecting eventual unauthorized water uses. However, some uncertainties should be considered, needing further analyses for improving the accuracy of the proposed approach.This study was supported by the Research Project of National Relevance (PRIN 2017) entitled “INtegrated Computer modeling and monitoring for Irrigation Planning in Italy - INCIPIT” and by the research project “Strategie per migliorare l’efficienza d’uso dell’acqua per le colture mediterranee” (SaveIrriWater) Linea 2 Ricerca di Ateneo 2020–22 (Università degli Studi di Catania).Peer reviewe

Adaptation of citrus orchards to deficit irrigation strategies

In this study, the adaptation characteristics of orange trees, related to the application over a decade of deficit irrigation (DI) strategies, have been explored. To this purpose, the analysis of a minimal dataset composed of physiological information (stem water potential - Ψ and sap flow - SF measurements), yield (fruits number and weight) and qualitative parameters (titratable acidity, TA; and total soluble solids, TSS) was performed with reference to the last irrigation seasons (i.e. 2018–19). The applied irrigation treatments were the following: sustained deficit irrigation (SDI); regulated deficit irrigation (RDI); partial root-zone drying (PRD), each distributing a water deficit of about 19%, 29% and 52%, respectively, compared to the control treatment (FI) supplying the full irrigation level (100% ET). In general, higher water use efficiencies (WUE) have been obtained in DI treatments, which guarantee greater water savings (up to 50%), without affecting yield and quality characteristics. In particular, the most stressed treatment (PRD), while reaching the lowest Ψ values (− 1.8 to − 2.0 MPa), as also shown by SF versus Ψ clusters, resulted in WUE values for yield (WUE), TA (WUE) and TSS (WUE) parameters of approximately 2.6, 2.9, and 3.1 times greater than FI, respectively. Overall, this study allowed identifying the cumulative adaptation characteristics of the orange trees under study to the application of long-term DI strategies and showing that trees were able to achieve yields and qualitative features similar to those obtained with FI, even after 10 years of application of deficient irrigation regimes.The work was carried out in the frame of Programma Operativo Nazionale (PON) “Attraction and International Mobility” (AIM) 1848200-2 initiative (D.V.) and within the project “Strategie per migliorare l’efficienza d’uso dell’acqua per le colture mediterranee” (SaveIrriWater) Linea 2 Ricerca di Ateneo 2020–22 (Universit` a degli Studi di Catania). J.M.R.-C. acknowledges the postdoctoral financial support received from Juan de la Cierva Spanish Postdoctoral Program (FJC2018-037196-I