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Observed variations in the ground electrical conductivity (σb*) measurements obtained with EMI instruments depend on several soil proxies that infuence crop growth and development such as salinity (σe), contents of water (θw), clay (wc) and organic matter (wom) and bulk density (ρb). However, the relative contributions of all these to σb* are unknown. This knowledge is needed to improve the planning and interpretation of σb* data for precision agriculture applications. Recently, a semi-empirical model has been developed to relate σb* measurements taken with an EM38 device to σe, θw, wc, wom and ρb and also soil temperature (t). In this work this model was subjected to a global sensitivity analysis (GSA) based on the soil data obtained during two surveys carried out, one in summer and the other in autumn, in an ample irrigated area in SE Spain. On the basis of the multiple linear regression meta-models developed for the σb* measurements, these were found to linearly respond to the soil properties (R2 between 0.92 and 0.96) and thus, the GSA could be based on their standardised regression coefcients. According to these, the soil characteristics explain the following percentages of variance in σb* (PV): 30–34 (σe), 8–20 (θw), 32–47 (wc), 0.6–2.6 (wom), 5.7–7.5 (ρb) and 0.3–0.4 (t) with changes from the summer to the autumn season of − 4, − 12 and+15 in the PV explained by the most infuential properties, respectively, σe, θw and wc. The results of the GSA will help the planning and interpretation of σb* measurements for improving crop management.

By using different physical foundations and technologies, many probes have been developed for on-site soil salinity appraisal in the last forty years. In order to better understand their respective technical and practical advantages and constraints, comparisons among probes are needed. In this study, three different probes, based on electrical resistance (ER), electromagnetic induction (EMI), and frequency domain reflectometry (FDR), were compared during a field survey carried out in a large salt-threatened agricultural area. Information about the soil bulk electrical conductivity (&sigma, b) at different depths was obtained with each of the probes and, additionally, other soil properties were also measured depending on the specifications of each instrument and, moreover, determined in samples. On average, the EMI and FDR techniques could be regarded as equivalent for &sigma, b measurement, whereas ER gave higher &sigma, b values. Whatever the case, EMI, and also ER, had to be supplemented with information about soil clay, organic matter, and water mass fractions to attain, despite this effort, poor soil salinity estimations by means of multiple linear regression models (R2 &lt, 0.5). On the contrary, FDR needed only probe data to achieve R2 of 0.7, though root mean standard error (RMSE) was still 1.5 dS m&minus, 1. The extra measurements and calculations that modern electrical conductivity contact probes integrate, specifically, those based on FDR, remarkably increase their ability for soil salinity appraisal, although there is still room for improvement.

Produced water (PW) is the largest by-product of the oil and gas industry. Its management is both economically and environmentally costly. PW reuse for irrigation offers an alternative to current disposal practices while providing water to irrigators in drylands. The aim of this investigation was to evaluate the environmental effects of irrigation with PW. The SALTIRSOIL_M model was used to simulate the irrigation of sugar beet with 15 PWs of a wide range of qualities in four climates of different aridity and on four contrasting soil types. The impacts on soil salinity, sodicity and pH as well as on crop yield and drainage water salinity were estimated. Well-drained soils with low water content at field capacity (Arenosol) are less sensitive to salinisation while a relatively high gypsum content (Gypsisol) makes the soil less vulnerable to both sodification and salinisation. On the contrary, clayey soils with higher water content at field capacity and lower gypsum content must be avoided as the soil structural stability as well as a tolerable soil electrical conductivity for the crop cannot be maintained on the long-term. Soil pH was not found to be sensitive to PW quality. Drainage water quality was found to be closely linked to PW quality although it is also influenced by the soil type. The impact of drainage water on the aquifer must be considered and reuse or disposal implemented accordingly for achieving sustainable irrigation. Finally, increasing aridity intensifies soil and drainage water salinity and sodicity. This investigation highlights the importance of adapting the existing irrigation water quality guidelines through the use of models to include relevant parameters related to soil type and aridity. Indeed, it will support the petroleum industry and irrigators, to estimate the risks due to watering crops with PW and will encourage its sustainable reuse in water-scarce areas.

The melon crop is moderately sensitive to soil salinity and, as a consequence, its yield decreases under saline conditions. Nevertheless, the exposure to moderate salinity also influences the melon quality by improving it, which offers compensation to the farmer. As a consequence, in moderately salt-affected lands, like the traditional irrigation area of the ‘Vega Baja del Segura’ (Alicante, Spain), melons are being grown. In this area the modernization of the secular irrigation system through the replacement of flood by drip systems, is currently being fostered. This fact, however, is generating some controversy, due to the known salt leaching effect that flood irrigation followed by drainage makes in the soil. In this study, the effects of three irrigation systems, namely, drip (DI), subsurface drip (SDI) and flood (FI), on soil salinity and thus, on the yield and quality of the melon, were compared. According to the results, the FI system kept the soil salt levels during the growth period at 4.1 ± 0.3 dS/m, that is, significantly lower than the 4.7 ± 0.2 dS/m attained with the DI and SDI systems. Nevertheless, the DI and, overall, SDI, provided higher and more homogenous soil moisture completely counteracting the effect of salinity as revealed by the soil water potential calculations. As a result, the SDI gave 27 ± 5 Mg/ha of total yield in comparison to 23 ± 2 Mg/ha (DI) and 20 ± 6 Mg/ha (FI). Besides, the SDI system reduced the number of damaged melons, thus additionally contributing to the significant higher marketable yield of the SDI (25 ± 4 Mg/ha) in comparison to the DI (20 ± 1 Mg/ha) and the FI (19 ± 7 Mg/ha). On the contrary, in the SDI treatment the fruit soluble solids content, tritatable acidity and pulp firmness decreased a bit, however, in the sensory evaluation no differences among irrigation treatments were observed.

Soil salinity is an important issue constraining the productivity of irrigation agriculture around the world. The standard method for soil salinity assessment is based on a laboratory method that is cumbersome and gives rise to limitations for data-intensive works. The use of sensors for the assessment of the apparent electrical conductivity (EC) of soils offers a way to overcome these constraints. These sensors are based on three electromagnetic phenomena, namely, electrical resistivity, electromagnetic induction, and reflectometry. Each class of sensors presents its own advantages and drawbacks. In the following chapter, these are presented along with the most popular commercial EC sensors used in nowadays agriculture, equations for the assessment of soil salinity on basis sensor measurements, some examples of application, and present and future development trends.

Irrigation in semi-arid areas can be optimally scheduled using models that maximize accuracy while minimizing data requirements. In this work, the validation of the one-dimensional transient-state SALTIRSOIL_M model able to monthly simulate the soil water content (θ), downward water flux (D), and the electrical conductivity in the saturation extract (ECe) is presented. The θ and the ECe were monthly monitored at 15 and 45cm depth in a plot in commercial production of globe artichoke under semi-arid climate and drip-irrigation in SE Spain during the 2011-2012 growing season. Data on water quality, weather, irrigation management, crop development and soil were also collected and used to simulate the θ, D, and ECe throughout the growing season at both depths with the SALTIRSOIL_M model. Reference and simulations of θ and D reasonably agreed with one another at both depths. ECe at 45cm depth was estimated correctly enough by the model but was underestimated at 15cm depth. The higher concentrations of nitrate, potassium, and hence other cations, which were observed at 15cm as a consequence of fertilization could explain this. The model was subsequently used to estimate the optimum water management in the plot. Use of 325-450mmyr-1 instead of 694mmyr-1, and by means of evenly distributed pulse irrigations instead of continuous ones, would have met the crop evapotranspiration requirements while avoiding excessive drainage, and maintaining soil salinity well below damaging values. © 2014 Elsevier B.V., This work has been performed thank to projects CGL2009-14592-C02-01 and CGL2009-14592-C02-02, program “Juan de la Cierva” (F.Visconti) and scholarship BES-2010-036515 (D. Martínez), all funded by the Ministerio de Ciencia e Innovación from the Government of Spain, and program Val i+d (F. Visconti), funded by Generalitat Valenciana.

Capacitance sensors such as Decagon 10HS and 5TE are increasingly used for soil water content (θ) estimation. However, their reliability and limitations in clayey soils irrigated with saline waters have not been completely characterized under field conditions. Four levels of soil water content were combined with six levels of soil salinity in twenty-four pots to assess the performance of both sensors in a wide range of soil salinities. A simplified power-law dielectric mixing model was calibrated in the laboratory to estimate the θ of a clay loam soil from the measurements of apparent dielectric permittivity (e{open}b) performed with both sensors. The calibrated equation was subsequently validated for the estimation of θ at two depths in six irrigated salt-threatened soils with clayey textures in SE Spain. The 10HS sensor provides higher estimations of e{open}b than the 5TE. Besides, the 5TE sensor was more sensitive to soil salinity. Consequently, a different calibration was carried out for each sensor. When all the soil salinity treatments were included in the calibrations, the results were poor. However, for soil apparent electrical conductivities below 1.7dSm-1 the 5TE sensor could be calibrated with low prediction errors, and with the calibration parameters b0 and b1 very close to their characteristic values in clayey and mineral soils. In field testing, the 5TE sensors calibrated with the obtained equation provided average correct estimations with an error of ±0.05m3m-3. On the contrary, the 10HS sensor overestimated the soil water content by 0.07m3m-3 on average. The proposed simple calibration equation for the 5TE sensor can be reliably used under field conditions to estimate θ of irrigated clayey soils up to an apparent electrical conductivity of 1.7dSm-1. © 2013 Elsevier B.V., The funding for this work was provided by the Spanish Ministerio de Ciencia e Innovación through projects CGL2009-14592-C02-01 and CGL2009-14592-C02-02, and program “Juan de la Cierva” (F. Visconti) and scholarship BES-2010-036515 (D. Martínez), and Generalitat Valenciana through program Val i+d (F. Visconti). We thank the two anonymous reviewers and joint editor-in-chief for their constructive comments that improved the article.

Soil acidification is a process of degradation that becomes more pronounced as a result of various human activities, but can be controlled through appropriate soil management. Calcium, magnesium and phosphorus deficiencies along with aluminium (Al) toxicity are considered the major constraints to plant growth in acid vineyard soils. The main aim of this work was to develop a model for liming amendment recommendation in acid vineyard soils using two liming materials, dolomite and sugar foam. These were used at three doses: 900, 1800 and 2700kgha(-1) of calcium carbonate equivalent (CCE). Seven soil properties, namely pH in water, pH in 1M potassium chloride (KCl), phosphorus content, base saturation, calcium, magnesium, potassium and aluminium exchangeable contents, were monitored at two soil depths (0-30 and 30-60cm) during 3 years. The association among the soil properties, and with the soil acidity, was investigated through principal component analysis. This resulted in the selection of the aluminium saturation in effective cation exchange capacity (Al%ECEC) as the soil property to be modelled. According to the results of a subsequent analysis of variance (ANOVA), the Al%ECEC strongly depends on the dose (in CCE content) of the liming material independently of its dolomite or sugar foam nature. Besides, the dose effect is different depending on the soil depth and the sampling time. As a result, two quadratic models, one per soil depth and for the time of leaf drop stage, have been proposed to make liming recommendations in acid vineyard soils. These quadratic empirical models are comparable with the known linear Cochrane model using an f value between 1.5 and 2 in the range of doses studied, i.e. able to drop the exchangeable aluminium down to 50%. However, the models proposed in this work further provide (i) different dose recommendations for the arable and deeper soil layers, and (ii) confidence intervals for minimum and maximum additions of liming materials and, specifically, for these important soils dedicated to the growing of vines under Mediterranean conditions.

Aluminium toxicity has been recognized as one of the most common causes of reduced grape yields in vineyard acid soils. The main aim of this study was to evaluate the effect of two liming materials, i.e. dolomitic lime and sugar foam, on a vineyard cultivated in an acid soil. The effects were studied in two soil layers (0-30 and 30-60 cm), as well as on leaf nutrient contents, must quality properties and grape yield, in an agricultural soil dedicated to Vitis vinifera L. cv. ‘Mencía’ cultivation. Data management and analysis were performed using analysis of variance (ANOVA). As liming material, sugar foam was more efficient than dolomitic limestone because sugar foam promoted the highest decrease in soil acidity properties at the same calcium carbonate equivalent dose. However, potassium contents in vines organs, including leaves and berries, seemed to decrease as a consequence of liming, with a concomitant increase in must total acidity. Soil available phosphorus also decreased as a consequence of liming, especially with sugar foam, though no effects were observed in plants. For these reasons fertilization of this soil with K and P is recommended along with liming. Grape yields in limed soils increased, although non-significantly, by 30%. This research has therefore provided an important opportunity to advance in our understanding of the effects of liming on grape quality and production in acid soils.

Process-based models could be used to predict the soil saturated extract salinity from extractable ion contents. However, a rigorous validation of such models for this purpose had not been carried out. A process-based model to predict the main inorganic ion composition, electrical conductivity, and pH of the saturated paste extract from extractable ion contents was developed step by step. The model development started from the principle of matter conservation in the soil solution as it concentrates from the 1:5 to the saturated paste extract. The need to include new hypotheses in the model was studied through calculation and analysis of standardised differences between measurements and model predictions. Therefore, best estimates of saturation paste extract properties occurred after taking into account the following: (i) free equilibration of the soil solution with the minerals calcite and gypsum under CO2 partial pressure of the saturated paste; (ii) further equilibration of the soil solution with the exchange complex; and (iii) determination of salt contents within the diffuse double layer (DDL) of the soil colloids, i.e. the anion exclusion. The last was necessary because the extracts where the determination of soil extractable anions (1:5 extracts), cations, and cation exchange capacity (CEC) were carried out were separated from their suspensions through centrifugation. Therefore, the reliable prediction of soil saturated paste extract salinity demands data on soil extractable ion contents, CEC, and the quantification of salts within the DDL. © 2012 CSIRO.

12 páginas, 13 figuras, 5 tablas., The knowledge of the soil saturated hydraulic conductivity (Ks) is essential for irrigation management purposes and for hydrological modelling. Several attempts have been done to estimate Ks in base of a number of soil parameters. However, a reliable enough model for qualitative Ks estimation based on the expert assessment of field characteristics had not been developed up to date. Five field characteristics, namely macroporosity (M), stoniness (S), texture (T), compaction (C) and sealing (L), in addition to tillage (G) were carefully assessed according to three classes each, in 202 sites in an agricultural irrigated area in Eastern Mediterranean Spain. After the evaluation of field characteristics, a single ring infiltrometer was used to determine the Ks value as the solution of the infiltration equation when the steady state was reached. The distribution of the Ks was assessed and five classes with 10-fold separations in class limits were defined accordingly. The relationships among site characteristics and Ks were analyzed through a correspondence analysis (CA). Next, an ordered logistic regression model (OLRM) for the prediction of the Ks class was developed. The CA revealed that, though tightly related, the set of six site characteristics should not be simplified into a smaller set, because each characteristic explains a significantly different aspect of Ks. Consequently, the OLRM was based on the six characteristics, which presented the following order of importance: L > M > G > T > C > S. According to the cross-validation of the OLRM the hit probability for the prediction of the Ks class attained an average value of 50%, which increased to 63% for the highest class of Ks. Moreover, wrong estimation of the Ks class exceeded the +-1 range only in 3% of sites. Therefore, a reliable enough assessment of Ks can be based on the expert assessment of field characteristics in combination with an OLRM., This work has been done in the framework of projects CGL2006-13233-CO2-01 and CGL2006-13233-CO2-02. The authors acknowledge the Ministerio de Educación y Ciencia from Spain their financial support. We would like to thank the two anonymous reviewers for their constructive comments.

10 páginas, 9 figuras, 6 tablas., The electrical conductivity of the water within the soil pores (ECp) measured with the WET sensor, appears to be a reliable estimate of soil salinity. A methodology combining the use of the WETsensor along with geostatistics was developed to delimit and evaluate soil salinity within an irrigated area under arid to semiarid Mediterranean climate in SE Spain. A systematic random sampling of 104 points was carried out. The association between ECp and the saturation-extract electrical conductivity (ECse) was assessed by means of correlation analysis. The semivariograms for ECp were obtained at three different soil depths. Interpolation techniques, such as ordinary kriging and cokriging, were applied to obtain ECp levels in the unknown places. For each one of the soil depths, a model able to predict ECse from ECp was developed by means of ordinary least squares regression analysis. A good correlation (r = 0.818, p < 0.001) between ECp and ECse was found. Spherical spatial distribution was the best model to fit to experimental semivariograms of ECp at 10, 30, and 50cm soil depths. Nevertheless, cokriging using the ECp of an adjacent soil depth as an auxiliary variable provided the best results, compared to ordinary kriging. An analytical propagation-error methodology was found to be useful to ascertain the contribution of the spatial interpolation and ordinary least squares analysis to the uncertainty of the ECse mapping. This methodology allowed us to identify 98% of the study area as affected by salinity problems within a rooting depth of 50 cm, with the threshold of ECse value at 2 dS m–1. However, considering the crops actually grown and 10% potential reduction yield, the soil-salinity- affected area decreased to 83%. The use of sensors to measure soil salinity in combination with geostatistics is a cost-effective way to draw maps of soil salinity at regional scale. This methodology is applicable to other agricultural irrigated areas under risk of salinization., This article is a result of a research project GV 0461/2006 funded by Conselleria de Agricultura Pesca i Alimentacio of Valencian Community. We also thank the anonymous reviewers for their fruitful comments.

Ponencia presentada en el 6th International Conference on Sensitivity Analysis of Model Output celebrado en Milan (Italia) del 19 al 22 de julio de 2010, SALTIRSOIL is a model for the prediction of soil salinity, sodicity and alkalinity in irrigated well-drained lands. These three characteristics are respectively assessed through the electrical conductivity and the sodium adsorption ratio of the soil saturation extract (ECse and SARse), and the pH of the soil saturated paste (pHsp). A global sensitivity analysis (GSA) was carried out to ascertain what input variables are more influential on these three outputs. The standardised regression coefficients of the linear regression analyses were used to calculate sensitivity measures. The irrigation water quality represented by ECiw and SARiw is the most influential factor on salinity and sodicity calculation, i.e. ECse and SARse respectively, while the carbon dioxide partial pressure so is on alkalinity (pHsp). Next there are the variables featuring the soil water balance: rainfall, average annual basal crop coefficient and reference evapotranspiration., The authors thank the Spanish Ministry of Science and Innovation for their financial support through projects CGL2006-13233-CO2-01 and CGL2006-13233-CO2-02. Fernando Visconti also thank the Valencian local government for a research scholarship in the framework of grant UCAM 2005020112.

11 páginas, 7 figuras, 7 tablas., Many empirical equations have been developed to predict the properties of saturation extracts, primarily electrical conductivity, from the properties of soil water extracts of 1 to 5 ratio. Soil water 1:5 extracts are more rapidly and reproducibly prepared than saturation extracts. However, the electrical conductivity of saturation extracts (ECse) is the benchmark to assess soil salinity. Analysis of the information provided by the electrical conductivity of soil 1:5 extracts (EC1:5) is a prerequisite to guide equation development and to use EC1:5 for soil salinity assessment. A total of 135 soil samples were taken from 39 sites at up to four different depths per site, down to a maximum depth of 95 cm in an irrigated agricultural area in SE Spain. Soil 1:5 extracts obtained from each sample were analysed for twelve chemical properties: concentration of sodium, ammonium, potassium, magnesium, calcium, chloride, nitrite, nitrate, sulphate, alkalinity and electrical conductivity. A principal component analysis (PCA) was applied to the correlation matrix of the log-transformed data set. The equilibrium status of 1:5 extracts with regard to gypsum was assessed with the chemical speciation programme SALSOLCHEMIS. The soil gypsum content was determined by using an adaptation of the classical method of total dissolution of soil gypsum, adequate to determine low gypsum contents, i.e. lower than 2%. Three principal components, accounting for 82% of the variance in the correlation matrix, were retained after eigenvector extraction. The first component accounted for 53% of the variance and was interpreted as representing the extract salinity due to gypsum dissolution. The second component accounted for 16% of the variance and was interpreted as representing the component of the extract salinity due to salts more soluble than gypsum, such as sodium and chloride salts. The information about soil salinity is split in two components in the 1:5 extracts, which are not easily resolved, whereas only one salinity component was obtained in the saturation extracts. The EC1:5 is a reliable property to estimate ECse, with a 95% confidence interval of ±1.2 dS m−1, only when it is lower than 1 dS m−1. When EC1:5 is higher than 2.4 dS m−1 it could also be reliably used to estimate soil salinity only if the 1:5 extract is gypsum-saturated, which is highly probable when the soil gypsum content is higher than 1.5%, or when the saturation extract is not gypsumsaturated, situation which happens when soil gypsum content is lower than 0.2%. When the EC1:5 is between 1 and 2.4 dS m−1, it provides poor information about the ECse, which could be between 4 and 14 dS m−1 unless the soil gypsum content is negligible, i.e. lower than 0.2%. The usefulness of the EC1:5 to estimate soil salinity can be extended when it is used in conjunction with an estimate of soil gypsum content. The development of more than one equation to estimate ECse from EC1:5 depending on soil gypsum content is recommended., We thank the Conselleria de Medi Ambient from the Generalitat Valenciana for funding this research through project GV 0461/2006. We would also like to thank the two anonymous reviewers, and editor-in-chief for their fruitful comments and indications, which improved the article.

10 páginas, 6 figuras, 6 tablas., Calcite equilibrium characterisation of soil solutions is needed in order to provide soil salinity modellers with reliable solubility constants in solutions where the hypothesis of equilibrium can be accepted. A total of 134 soil samples were taken from 39 sites at 2, 3, or 4 depths per site, down to a maximum depth of 95 cm, during a survey in the irrigated agricultural area of the Segura River Lowland (SE Spain). Soil saturation extracts obtained from each sample were analysed for thirteen chemical properties: Na, NH4, K, Mg, Ca, Cl, NO2, NO3, SO4, alkalinity, chemical oxygen demand, and electrical conductivity. A principal component analysis (PCA) was then done on the correlation matrix from the log-transformed data set. Three principal components, accounting for 76% of the variance in the correlation matrix, were retained after eigenvector extraction. These components were interpreted as representing salinisation, soil superficiality as opposed to soil depth, and fertilisation status. Sodium, chloride, magnesium, calcium and sulphate concentrations were highly correlated with the first principal component and were interpreted as explaining the variance in electrical conductivity of the soil saturation extracts, and by proxy soil salinity. Alkalinity, pH, chemical oxygen demand, and nitrite were correlated with the second principal component. Nitrate, potassium and ammonium concentrations were correlated with the third principal component, and their variation in soil was independent of soil saturation extract salt content and soil depth. According to the interpretation of the second principal component, soil saturation extracts are further than the solutions in the saturated pastes from being in equilibrium with calcite. The calcite oversaturation status of soil saturation extracts is related to soil organic matter content., We thank the Conselleria de Medi Ambient from the Generalitat Valenciana for funding this research through project GV 0461/2006. We also thank the two anonymous reviewers for their fruitful comments.

Affordable, commercial dielectric sensors of the frequency domain reflectometry (FDR) and capacitance-conductance (CC) types estimate the dielectric permittivity (εb) and electrical conductivity (σb) of bulk soil. In this work, an equation was obtained to estimate the pore-water electrical conductivity (σp), which is closely related to the soil salinity in contact with plant roots, from εb and σb data, by combining the simplified dielectric mixing (SDM) model that relates εb to the soil volumetric water content (θ), with the Rhoades equation that relates θ and σb to σp. This equation was calibrated with measurements of εb and σb obtained with the Delta-T WET (FDR) and the Decagon 5TE (CC) sensors, in 20 pots filled with a clay loam soil and arranged as combinations of four levels of soil moisture with five levels of soil salinity. The calibrations were performed against reference θ and σp values. The σp was calculated with the chemical equilibrium model SALSOLCHEMEC and used as a more reliable reference than the electrical conductivity of the soil wetting water. For both sensors, the SDM model on the one hand, and the Rhoades equation on the other, provided the most accurate estimations using the least number of parameters regarding their respective alternatives, i.e. the third-order polynomial and the Hilhorst equation. The combined equation for estimation of σp subsequently provided root mean square deviations of 3.1 (WET) and 4.1 (5TE) dSm-1, which decreased to 1.5 and 2.6dSm-1 for θ >0.22m3 m-3, and σb 0.22m3 m-3 and σb

Optimizing water use in vineyards is crucial for ensuring the sustainability of viticulture in semi-arid regions, and this may be achieved by minimizing direct water evaporation from the soil through the use of mulching. In this context, the current study aimed at assessing the combined effects of the vine-row application of an organic mulch (vine prunings) and no-tillage under two water regimes on soil properties, plant water and nutritional status, yield and must composition of grapevine (Vitis vinifera L.) cv. Bobal grown under semi-arid conditions. For this purpose, a field experiment in a split-plot design was carried out for three years (2016–2018) in a mature Bobal vineyard located in Eastern Spain. Two soil management strategies (tillage and organic mulching with no-tillage) were assessed under two water regimes (rainfed and deficit drip irrigation) with four replications per combination. Vine responses were determined by measuring midday stem water potential, leaf nutrient concentrations, pruning weight, yield components and grape composition. Soil properties were assessed at the end of the experiment. Mulching and no-tillage positively affected vine water status under both water regimes, resulting in reductions in grape phenolic composition. Interactive effects of both water regime and soil management on water use efficiency were found. Regardless of soil management practice, irrigation increased yield and pruning weight when compared to rainfed conditions. Soil management had slight effects on vine nutritional status. At the end of the experiment, soil compaction increased and infiltration decreased as a consequence of mulching and no-tillage. Organic mulch and no-tillage improved vine water status, however, considering the final soil surface compaction and low water infiltration rate, longer-term studies are necessary to assess the sustainability of combining both practices., This work was supported by the Spanish Ministry of Economy and Competitiveness (MINECO) with FEDER co-financing [grant number AGL2017-83738-C3-3] and the EU by H2020 project SHui [grant number 773903]. Cajamar and Lucio Gil de Fagoaga for facilitating the experimental field.