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Because of climate change and the scarce availability of natural resources there is a need to develop sustainable intensification strategies intended for optimizing water use in vineyards. In this study, water regime, fertilization and soil management practices were assessed in terms of vineyard water use, by evaluating the inter-row and crop line evapotranspiration (ET) components using the Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC) model in combination with unmanned aerial vehicle multispectral and thermal images taken on five dates throughout the growing season. The application of the METRIC-UAV using high-resolution imagery was proven as a useful tool for evaluating the effects of sustainable intensification strategies on water use of crops where vegetation does not completely cover the soil, identifying the most efficient site-specific strategies for water conservation purposes. Moreover, METRIC-UAV allowed evaluating separately their effects on the inter-row and the crop line. Among the assessed sustainable intensification strategies, the application of mulching provided the highest water savings (- 28%) when compared to traditional soil tillage management, reducing inter-row soil evaporation by 63%, while increasing crop-line ET by 14%. In spite of this, the mulching application did not affect yield, but significantly enhanced water use efficiency (WUE) in terms of grape yield compared to tillage. The adoption of deficit irrigation (DI) strategies did not result in vine water stress that was severe enough to significantly affect crop line ET when compared with fully irrigated (FI) vines. Both DI and FI strategies increased vine water use by 18% and 27%, respectively, as compared to the rainfed regime, with no differences found in the inter-row water consumption. DI and FI, in turn, significantly increased yield as compared to rainfed crops, leading to significant improvements in WUE. In the short term, the application

[Background and aims]: The ever-increasing demand of fresh water from irrigated agriculture and the water scarcity condition that characterizes the Mediterranean region, encourages the adoption of efficient water saving strategies. In this study, the electrical resistivity imaging (ERI) technique was applied for characterizing the mass exchange mechanisms affecting the continuous soil-plant system of heterogeneous micro-irrigated orchards., [Methods]: Time-lapse ERI surveys were carried out in a multi-variety and mixed-age orange orchard located in Eastern Sicily (insular Italy). The time-lapse ERI monitoring was coupled with the use of independent soil water content (SWC) measurements., [Results and conclusions]: A clear relationship between the soil electrical resistivity (ER) and the measured SWC changes was identified in the soil under the mixed-age orchard (with an overall coefficient of determination value of 0.63). Specifically, this study highlights the dependency of SWC dynamics as function of tree age. Overall, an increase in ER was obtained in correspondence to the soil domain where the younger trees were located ( < = 3 years). This behaviour was inferred to result from the higher soil evaporation process active at these locations, due to less vegetation cover of the younger trees and, consequently to their lesser root extension in comparison to the mature trees ( > = 8 years). On the other hand, in mature trees, characterized by denser root biomass, there were more evident decreasing patterns of ER (i.e., greater changes in SWC), due to greater transpiration rates that caused lower initial SWC under these conditions in comparison to the younger trees.

During the last 7 years, within the framework of projects Riego-Asesor, Phertilizer and “Fertirriego de precisión para un manejo sostenible de la horticultura intensiva. Aspectos agronómicos e implicaciones ambientales” we have conducted multiple open field trials in the Campo de Cartagena and multiple greenhouse experiments in Santomera (Murcia), either in pot or hydroponic. The trials with vegetable crops include endive, baby lettuce, romaine lettuce, summer wonder lettuce, Iceberg lettuce, piel de sapo melon, and potato. The overall objective of all these projects was to make a more efficient use of two mayor resources used in agriculture; water and nutrients, with special focus on nitrogen. Here we resume the most notable results of these experiments; i) the amount of irrigation water applied by farmers was tightly adjusted and this amount closely mimics the FAO recommendations and custom-made water balance model named “Riego-Asesor”, ii) a fertigation strategy aimed to match water and fertilizer inputs with plant demand is key in improving water and nitrogen use efficiency, and simple to use decision support system was designed for this goal iii) irrigation frequency/dose plays a critical role in improving water and nitrogen use efficiency, with high frequency of irrigation resulting in higher yield and lower nitrate leaching iv) knowing how the nitrogen source (nitrate/ammonium) affects growth and development in different vegetable crops can be a further step of adjustment to increase nitrogen use efficiency. All this information can be used to designing fertigation strategies in intensive agriculture that match and integrate water and nutrients supplies with the needs of a given crop under a given growing conditions.

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.

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; air temperature, T; relative humidity, RH; wind speed, u; reference evapotranspiration, ET), with in situ agrometeorological observations 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 performance was obtained for T, followed by RH, R, and u for both reanalysis datasets, especially under temperate climate conditions. These performances were translated into slightly higher accuracy of ET estimates by ERA5-Land product, confirming the potential of using reanalysis datasets as an alternative data source for retrieving the ET and overcoming the unavailability of observed agrometeorological data.

The sustainability of woody crop agroecosystems requires continued improvements to water, nutrient and soil management. In this work, the combination of resource availability or fertigation dose with soil management practices was tested in a 2 × 2 factorial design in a drip irrigated young almond orchard. The fertigation doses were: the farmer supply at 60% of crop evapotranspiration and full nutrient requirements and the half-farmer supply at 30% of crop evapotranspiration and half nutrient requirements. The soil management practices were: bare soil and cover crops in the inter-row (mixture of grasses and legumes). Tree growth, yield, water and nutrient status, and cover crop biomass and nutrient status were determined, as well as inter-row soil C and N concentration. Results showed that the effect of resource availability was independent of soil management and vice versa. The half farmer treatment reduced tree vegetative growth and yield compared to farmer treatment, due to a negative effect on the water status, without observing a decrease in the concentration of nutrients in leaves or fruit. Trees with cover crop also reduced growth and yield compared to bare soil management. This was due to a nutritional competition, mainly of Ca, Fe, Mn and Zn, rather than to a decline in tree water status. Cover crops sequester up to 1 t/ha/year of carbon but do not increase soil organic carbon, nor soil total nitrogen. Cover crops proved to be efficient in reducing soil nitrate concentration in the topsoil and therefore has potential to prevent its leaching. Deficit fertigation and the use of cover crops can be effective practices to preserve and save water and nutrient resources in Mediterranean agroecosystems, but should be established with caution so as not to compromise the profitability of the orchard.

Yield estimation in vineyards is an essential issue for performing cropping practices to reach the desired production quality or quantity. Sporadic manual measurements have been traditionally made. In the last decade, vegetation indices (VIs) and geometric parameters obtained from unmanned aerial vehicle (UAV) imagery have been related to different vine biophysical features. This research aimed to evaluate the potential of VIs and green canopy cover (GCC; as a measure of plant vigour) obtained from conventional (or red, green, blue; RGB) and multispectral sensors that monitor spatial intraplot variability for yield predictions. The yield components traditionally sampled in an early growth cycle stage (pea berry size) were combined with UAV imagery-based products. The proposed methodology was applied to a vineyard in southeastern Spain during the 2019 and 2020 growing seasons. Rain-fed and irrigated treatments were implemented. Flights were performed throughout the growth cycle using RGB and multispectral cameras mounted on a UAV. Orthoimages were generated. Computer vision techniques were used to segment these orthoimages to obtain vegetation-only masks. Simple and multiple linear regression techniques were evaluated by using VIs alone, VIs combined with GCC and yield components as predictors. The RMSE values ranged from 0.21 kg vine to 0.39 kg vine when yield components, RGB or multispectral VIs were employed. Therefore, with all the advantages that their use entails, RGB and multispectral sensors are a good option for estimating the final yield of vineyards despite calibration being required for each season and grapevine plot.

Water is an essential resource for agriculture, accounting for 40–60% of total water consumption in Europe, mostly used for irrigation [1]. Climate and environmental changes put pressure on the use of water for irrigation, which must reduce water losses and wastages while improving the productivity of irrigated crops [2,3]. Water use optimization is essential for the long-term sustainability of agroecosystems, especially in arid and semi-arid regions, and under the current climate change scenarios (higher air temperatures, more severe drought, and heat waves), since crop yield, quality, and economic viability largely depend on water availability [1,4]. In the case of woody crops, it is a serious concern due to the large extension of these crops in different climatic conditions, the high inputs required for growing them, and the higher water losses due to soil evaporation (i.e., higher bare-soil proportion) in comparison to homogeneous crops. These limitations have driven the research of new strategies for coping with water scarcity, as the development of more efficient irrigation strategies (e.g., subsurface irrigation or regulated deficit irrigation) and sustainable soil management practices (e.g., plastic or vegetation mulching). The aim of this Special Issue is to provide an overview of recent advances in several aspects related to water management in woody crops (i.e., fruit orchards, olive groves, vineyards, citrus, berries, forest stands, shrubs, etc.).

This study investigates the main drivers of uncertainties in simulated irrigated maize yield under historical conditions as well as scenarios of increased temperatures and altered irrigation water availability. Using APSIM, MONICA, and SIMPLACE crop models, we quantified the relative contributions of three irrigation water allocation strategies, three sowing dates, and three maize cultivars to the uncertainty in simulated yields. The water allocation strategies were derived from historical records of farmer’s allocation patterns in drip-irrigation scheme of the Genil-Cabra region, Spain (2014–2017). By considering combinations of allocation strategies, the adjusted R values (showing the degree of agreement between simulated and observed yields) increased by 29% compared to unrealistic assumptions of considering only near optimal or deficit irrigation scheduling. The factor decomposition analysis based on historic climate showed that irrigation strategies was the main driver of uncertainty in simulated yields (66%). However, under temperature increase scenarios, the contribution of crop model and cultivar choice to uncertainty in simulated yields were as important as irrigation strategy. This was partially due to different model structure in processes related to the temperature responses. Our study calls for including information on irrigation strategies conducted by farmers to reduce the uncertainty in simulated yields at field 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.

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.

En las últimas décadas se han realizado grandes avances para ajustar la dosis de riego a aplicar las necesidades hídricas promedio de una parcela, tendiendo hacia un riego de precisión. El siguiente reto que aborda el proyecto Preciriego es tener en cuenta la variabilidad en las parcelas para ajustar el riego a las posibles diferencias existentes. Mientras en cultivos herbáceos más extensivos y bajo riego por aspersión con Pivots este desafío ha sido ya abordado, se han realizado menos trabajos en cultivos leñosos y riego por goteo. En esta comunicación se integran técnicas de teledetección de rango cercano utilizando drones y modelos hidráulicos de precisión para llevar a cabo una zonificación de un viñedo comercial para definir tres zonas con distintos índices de vigor vegetativo. Posteriormente, se ha aplicado un riego diferencial para cada zona de modo que, manteniendo la dosis promedio establecida de unos 1000 m3/ha, la misma ha sido aplicada de forma diferencial en función del vigor de las cepas. Para ello se ha variado el diseño agronómico del riego, utilizando distintas distancias entre goteros en función de la zonificación realizada. De este modo, sin tener que sectorizar ni aplicar tiempos o frecuencias de riego distintas para cada zona, la pluviosidad de la instalación fue distinta. Dicha estrategia de riego de precisión ha sido validada en campo, demostrando que las zonas de mayor vigor vegetativo han aprovechado mejor la mayor dotación de riego empleada teniendo una mayor producción frente a otras zonas con menor desarrollo vegetativo donde se ha considerado que la productividad de las cepas podía estar limitada por otros factores al margen del riego. Otra de las ventajas del sistema de riego de precisión radica en la automatización de la programación llevada a cabo desarrollada mediante nuevos programadores con posibilidad de tele‐lectura y fácil instalación en parcela. La puesta en práctica de los sistemas de riego de precisión sigue adelante en el pr

This paper presents a novel methodology for identifying homogeneous areas within high-frequency drip-irrigated orchards and for defining the most sensitive and resistant areas of the field to water stress. The methodology proposed here is based on the assessment of water status at the tree level during mild water stress using remote sensing derived indicators which provide valuable information about the spatial distribution of the response to water stress within an orchard. The areas more resistant to water stress will maintain a good water status, while those prone to water stress will develop initial symptoms of water deficit. The study was performed over three different peach orchards that were evaluated from 2 to 3 years. Water status was monitored using high-resolution thermal imagery acquired before and after the onset of water stress. The Thermal Sensitivity Index (TSI), derived from the difference of the CWSI and the cumulated reference evapotranspiration between the two dates, demonstrated to be well related to the increase of stem water potential. The spatial distribution of TSI enables the identification of sensitive areas within a peach orchard, a first step for establishing precision drip irrigation programs.

[EN]: Recently important advances have been made to adjust the irrigation dose to apply the average plot water needs tending towards precision irrigation. The next challenge that the Preciriego project addresses is to take into account the variability in the plots to adjust the irrigation to the possible existing differences. While in more extensive herbaceous crops and under sprinkler irrigation with Pivots this challenge has already been addressed, less work has been done with woody crops under drip irrigation. In this communication, close-range remote sensing techniques are integrated using drones and precision hydraulic models to carry out a zoning of a commercial vineyard to define three zones with different vegetative vigour indexes. Subsequently, a differential irrigation has been applied for each zone so that, maintaining the established average dose of about 1000 m3 / ha, water was applied differentially depending on the vine vigour. For this, the agronomic irrigation design has been varied, using different distances between drippers depending on the zoning carried out. In this way, without having to sectorize or apply different irrigation times or frequencies for each zone, the watering application for each zone was different. This precision irrigation strategy has been validated in the field, showing that the areas with the highest vegetative vigour have made better use of the greater irrigation application, having a higher production compared to other areas with less vegetative development. In the low vigour areas, it has been considered that the vine productivity could be limited by factors other than irrigation. Another advantage of the precision irrigation system lies in the automation of the programming carried out by means of new programmers with the possibility of remote-reading and easy installation on the plot. The implementation of precision irrigation systems continues in the Preciriego project with other trials underway in woody and horticultu, [ES]: En las últimas décadas se han realizado grandes avances para ajustar la dosis de riego a aplicar las necesidades hídricas promedio de una parcela, tendiendo hacia un riego de precisión. El siguiente reto que aborda el proyecto Preciriego es tener en cuenta la variabilidad en las parcelas para ajustar el riego a las posibles diferencias existentes. Mientras en cultivos herbáceos más extensivos y bajo riego por aspersión con Pivots este desafío ha sido ya abordado, se han realizado menos trabajos en cultivos leñosos y riego por goteo. En esta comunicación se integran técnicas de teledetección de rango cercano utilizando drones y modelos hidráulicos de precisión para llevar a cabo una zonificación de un viñedo comercial para definir tres zonas con distintos índices de vigor vegetativo. Posteriormente, se ha aplicado un riego diferencial para cada zona de modo que, manteniendo la dosis promedio establecida de unos 1000 m3/ha, la misma ha sido aplicada de forma diferencial en función del vigor de las cepas. Para ello se ha variado el diseño agronómico del riego, utilizando distintas distancias entre goteros en función de la zonificación realizada. De este modo, sin tener que sectorizar ni aplicar tiempos o frecuencias de riego distintas para cada zona, la pluviosidad de la instalación fue distinta. Dicha estrategia de riego de precisión ha sido validada en campo, demostrando que las zonas de mayor vigor vegetativo han aprovechado mejor la mayor dotación de riego empleada teniendo una mayor producción frente a otras zonas con menor desarrollo vegetativo donde se ha considerado que la productividad de las cepas podía estar limitada por otros factores al margen del riego. Otra de las ventajas del sistema de riego de precisión radica en la automatización de la programación llevada a cabo desarrollada mediante nuevos programadores con posibilidad de tele‐lectura y fácil instalación en parcela. La puesta en práctica de los sistemas de riego de precisión sigue adelante en

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 identification and recognition of the land processes are of vital importance for a proper management of the ecosystem functions and services. However, on-ground land uses/land covers (LULC) characterization is a time-consuming task, often limited to small land areas, which can be solved using remote sensing technologies. The objective of this work is to investigate how the different MODIS NDVI seasonal parameters responded to the main land processes observed in Europe in the 2000-2018 period; characterizing their temporal trend; and evaluating which one reflected better each specific land process. NDVI time-series were evaluated using TIMESAT software, which extracted eight seasonality parameters: amplitude, base value, length of season, maximum value, left and right derivative values and small and large integrated values. These parameters were correlated with the LULC changes derived from COoRdination of INformation on the Environment Land Cover (CLC) for assessing which parameter better characterized each land process. The temporal evolution of the maximum seasonal NDVI was the parameter that better characterized the occurrence of most of the land processes evaluated (afforestation, agriculturalization, degradation, land abandonment, land restoration, urbanization; R2 from 0.67-0.97). Large integrated value also presented significant relationships but they were restricted to two of the three evaluated periods. On the contrary, land processes involving CLC categories with similar NDVI patterns were not well captured with the proposed methodology. These results evidenced that this methodology could be combined with other classification methods for improving LULC identification accuracy or for identifying LULC processes in locations where no LULC maps are available. Such information can be used by policy-makers to draw LULC management actions associated with sustainable development goals. This is especially relevant for areas where food security is at stake and w

A novel ArcGIS toolbox that applies the Mapping Evapotranspiration with Internalized Calibration model was developed and tested in a semi-arid environment. The tool, named METRIC-GIS, facilitates the pre-processing operations and the automatic identification of potential calibration and pixels review. The energy balance components obtained from METRIC-GIS were contrasted with those from the original METRIC version (R2 = 1; RMSE = 0 W m−2 or mm day−1 for ETc) Additionally, an irrigated scheme located at southern Spain was considered for assessing Kc variability in the maize fields with METRIC-GIS. The identified spatial variability was mainly due to differences in irrigation regimes, crop management practices, and planting and harvesting dates. This information is critical for developing irrigation advisory strategies that contribute to the area sustainability. The developed tool facilitates data input introduction and reduces computational time by up to 50%, providing a more user-friendly alternative to other existing platforms that use METRIC.

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.

Water erosion is a severe threat to soil resources, especially on cultivated lands, such as vineyards, which are extremely susceptible to soil losses. In this context, management practices aiming at reducing erosion risks must be favored. This current study aimed at estimating soil losses in two vineyards under Atlantic climatic conditions (Galicia, North West Spain). The capacity of two management practices for reducing soil erosion was tested and compared with tilled soil in the inter-rows: (i) application of mulching, and (ii) maintaining native vegetation. Soil losses were assessed using erosion pins and micro-plots. In addition, the improved stock unearthing method (ISUM) was employed in one of the vineyards to estimate soil remobilization since plantation. Soil loss rates in one of the vineyards were lower when soil was managed under mulching (0.36 Mg ha−1) and native vegetation (0.42 Mg ha−1), compared to tilled soil (0.84 Mg ha−1). Sediment losses measured in the second vineyard ranged between 0.21 and 0.69 Mg ha−1, depending on the treatment, but no clear conclusions could be drawn. Long-term soil loss, as estimated by ISUM, was of the same order of magnitude than that obtained by erosion pins and micro-plots. In both vineyards, soil loss rates were lower than those registered in Mediterranean vineyards, and were below the limit for sustainable erosion in Europe. Nevertheless, soil management practices alternative to tillage in the inter-row might reduce erosion risks under Atlantic climate conditions.

Climate change will intensify water scarcity, and therefore irrigation must be adapted to save water. Operational tools that provide watering recommendations to end-users are needed. This work presents a new tool, Irrigation-Advisor (IA), which is based on weather forecasts and is able to separately determine soil evaporation and crop transpiration, and thus is adaptable to a broad range of agricultural situations. By calculating several statistical indicators, IA was tested against the FAO-56 crop evapotranspiration (ETcFAO) methodology using local crop coefficients. Additionally, IA recommendations were compared with current standard practices by experienced farmers (F). Six field experiments with four widely cultivated species (endive, lettuce, muskmelon and potato) were performed in Southeast Spain. Irrigation water applied, crop yield, aboveground biomass and water productivity were determined. Crop water needs underestimations (5%–20%) were detected when comparing IA against ETcFAO, although the index of agreement proved reasonable adjustments. The IA recommendations led to water savings up to 13% when compared to F, except for lettuce, with a 31% surplus in irrigation when using IA. Crop yield was not compromised and water productivity was increased by IA. Therefore, IA mimicked the farmers0 irrigation strategies fairly well without deploying sensors on-site. Nevertheless, improvements are needed for increasing the accuracy of IA estimations.

The recent technical improvements in the sensors used to acquire images from land surfaces has made possible to assess the performance of the energy balance models using unprecedented spatial resolutions. Thus, the objective of this work is to evaluate the response of the different energy balance components obtained from METRIC model as a function of the input pixel size. Very high spatial resolution airborne images (≈50 cm) on three dates over olive orchards were used to aggregate different spatial resolutions, ranging from 5 m to 1 km. This study represents the first time that METRIC model has been run with such high spatial resolution imagery in heterogeneous agricultural systems, evaluating the effects caused by its aggregation into coarser pixel sizes. Net radiation and soil heat flux showed a near insensitive behavior to spatial resolution changes, reflecting that the emissivity and albedo respond linearly to pixel aggregation. However, greater discrepancies were obtained for sensible (up to 17%) and latent (up to 23%) heat fluxes at spatial resolutions coarser than 30 × 30 m due to the aggregation of non-linear components, and to the inclusion of non-agricultural areas in such aggregation. Results obtained confirm the good performance of METRIC model when used with high spatial resolution imagery, whereas they warn of some major errors in crop evapotranspiration estimation when medium or large scales are used.

Climate change will intensify water scarcity, and therefore irrigation must be adapted to save water. Operational tools that provide watering recommendations to end-users are needed. This work presents a new tool, Irrigation-Advisor (IA), which is based on weather forecasts and is able to separately determine soil evaporation and crop transpiration, and thus is adaptable to a broad range of agricultural situations. By calculating several statistical indicators, IA was tested against the FAO-56 crop evapotranspiration (ETcFAO) methodology using local crop coefficients. Additionally, IA recommendations were compared with current standard practices by experienced farmers (F). Six field experiments with four widely cultivated species (endive, lettuce, muskmelon and potato) were performed in Southeast Spain. Irrigation water applied, crop yield, aboveground biomass and water productivity were determined. Crop water needs underestimations (5%–20%) were detected when comparing IA against ETcFAO, although the index of agreement proved reasonable adjustments. The IA recommendations led to water savings up to 13% when compared to F, except for lettuce, with a 31% surplus in irrigation when using IA. Crop yield was not compromised and water productivity was increased by IA. Therefore, IA mimicked the farmers′ irrigation strategies fairly well without deploying sensors on-site. Nevertheless, improvements are needed for increasing the accuracy of IA estimations.

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.