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#### Agrosal: presentación de un nuevo portal web que trata sobre la salinidad de los suelos agrícolas de regadío. Parte I

- De-Paz, José M.
- Visconti, Fernando
- Moreno, G.
- Molina, M. J.
- Ingelmo Sánchez, F.
- Martínez, D.
- Sánchez, J.

#### Agrosal: presentación de un nuevo sistema online de recomendación del riego en zonas amenazadas por salinización del suelo: Parte II.

- Visconti, Fernando
- Moreno, G.
- Molina, M. J.
- Ingelmo, F.
- Martínez, D.
- Sánchez, J.
- De-Paz, José M.

La agricultura de regadío de la Comunidad Valenciana se caracteriza por una utilización intensiva del suelo y el agua, lo cual amenaza su sostenibilidad. Una de las principales amenazas es la salinización, la cual puede agravarse en los próximos años debido a la aridez del clima en un escenario de cambio climático. Por esta razón es importante disponer de herramientas que permitan planificar los riegos lo más eficientemente posible adaptándose al clima y la calidad del agua en cada momento y lugar, y a la vez asegurando la producción y calidad del cultivo, y protegiendo el medio ambiente. El sistema de ayuda a la decisión accesible en Internet DSS-SALTIRSOIL (www.agrosal.ivia.es) ha sido creado con esta finalidad. En el presente trabajo se presenta un ejemplo de aplicación de esta herramienta para un cultivo de mandarina adulto en Almoradí (Alicante), con el fin de mostrar las principales características de esta aplicación, así como sus capacidades y limitaciones

#### Predictive modelling of soil aluminium saturation as a basis for liming recommendations in vineyard acid soils under Mediterranean conditions

- Angel Olego, Miguel
- De-Paz, José M.
- Visconti, Fernando
- Enrique Garzon, Jose

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.

#### Spatial evaluation of soil salinity using the WET sensor in the irrigated area of the Segura river lowland

- Paz, Jose Miguel de
- Visconti, Fernando
- Rubio, Jose L.

The electrical conductivity of the water within the soil pores (EC(p)) measured with the WET sensor, appears to be a reliable estimate of soil salinity. A methodology combining the use of the WET sensor 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 EC(p) and the saturation-extract electrical conductivity (EC(se)) was assessed by means of correlation analysis. The semivariograms for EC(p) were obtained at three different soil depths. Interpolation techniques, such as ordinary kriging and cokriging, were applied to obtain EC(p) levels in the unknown places. For each one of the soil depths, a model able to predict EC(se) from EC(p) was developed by means of ordinary least squares regression analysis. A good correlation (r = 0.818, p < 0.001) between EC(p) and EC(se) was found. Spherical spatial distribution was the best model to fit to experimental semivariograms of EC(p) at 10, 30, and 50 cm soil depths. Nevertheless, cokriging using the EC(p) 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 EC(se) 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 EC(se) 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.

#### Choice of selectivity coefficients for cation exchange using principal components analysis and bootstrap anova of coefficients of variation

- Visconti, Fernando
- De-Paz, José M.
- Rubio, J. L.

Modellers of the exchange of sodium, potassium, calcium and magnesium in soils have to choose from up to six different equations based on the mass action law paradigm (mainly Gapon, Vanselow, Gaines-Thomas and Kerr) and up to six different binary cation combinations. In this article a methodology to choose the most appropriate equation and binary cation combinations is presented. The combination of six equations with six binary cation combinations resulted in 36 selectivity coefficients. Each one of these was assessed for 133 calcareous illitic soil samples. Six principal components analyses (PCA) were carried out to find out which three binary cation combinations accounted most for the variance of the soil exchange selectivity. Then a bootstrap anova and multiple comparison (MC) procedure with orthogonal contrasts were carried out to compare the coefficients of variation of the selectivity coefficients calculated with each equation. According to the PCA, the three binary cation combinations involving calcium, and expressed with whichever of the equations of Kerr, Vanselow and Gaines-Thomas, accounted most efficiently for the variance of the soil exchange selectivity. According to the bootstrap anova and MC analysis, the Gapon equations, either in analytical concentrations or activities of aqueous cations, provide significantly larger coefficients of variation than the equations of Kerr (either in analytical concentrations or activities of aqueous cations), Vanselow and Gaines-Thomas. The use of the Kerr, Vanselow or Gaines-Thomas equations and the three binary cation combinations involving calcium resulted in the most effective way of modelling the exchange equilibria of sodium, potassium, calcium and magnesium in calcareous illitic soils.

#### An empirical equation to calculate soil solution electrical conductivity at 25 degrees C from major ion concentrations

- Visconti, Fernando
- De-Paz, José M.
- Rubio, J. L.

The electrical conductivity at 25 degrees C (EC(25)) of soil solutions or irrigation waters is the standard property for assessing salinity. Many models for soil salinity prediction calculate the major ion composition of the soil solution. The electrical conductivity of a solution can be determined from its composition through several different empirical equations. An assessment of these equations is necessary to incorporate the most accurate and precise equations in such models. Twelve different equations for the EC(25) calculation were calibrated by means of regression analyses with data from 133 saturation extracts and another 135 1: 5 soil-to-water extracts from a salt-affected agricultural irrigated area. The equations with better calibration parameters were tested with another data set of 153 soil solutions covering a wide range of salt concentrations and compositions. The testing was conducted using the standardized difference t-test, which is a rigorous validation test used in this study for the first time. The equations based on the ionic conductivity decrement given by Kohlrausch's law presented the poorest calibration parameters. The equations founded on the hypothesis that EC(25) is proportional to analytical concentrations had worse calibration and validation parameters than their counterparts based on free-ion concentrations and ionic activities. The equations founded on simpler mathematical relationships generally gave improved validation parameters. The three equations based on the specific electrical conductivity definition presented a mean standardized difference between observations and predictions indistinguishable from zero at the 95% confidence level. The inclusion of the charged ion-pair concentrations in the equation based on free-ion concentrations improved its predictions, particularly at large electrical conductivities. This equation can be reliably used in conjunction with chemical speciation software to assess EC(25) from the ion composition of soil solutions.

#### SALTIRSOIL: a simulation model for the mid to long-term prediction of soil salinity in irrigated agriculture

- Visconti, Fernando
- De-Paz, José M.
- Rubio, J. L.
- Sanchez, J.

The SALTIRSOIL model predicts soil salinity, sodicity and alkalinity in irrigated land using basic information on soil, climate, crop, irrigation management and water quality. It extends the concept of the WATSUIT model to include irrigation and crop management practices, advances in the calculation of evapotranspiration and new algorithms for the water stress coefficient and calculation of electrical conductivity. SALTIRSOIL calculates the soil water balance and soil solution concentration over the year. A second module, SALSOLCHEM, calculates the inorganic ion composition of the soil solution at equilibrium with soil calcite and gypsum at the soil's CO(2) partial pressure. Results from comparing predicted and experimentally determined concentrations, observations and predictions of pH, alkalinity and calcium concentration in calcite-saturated solutions agree to the second significant figure; in gypsum-saturated solutions the standard difference between observations and predictions is <3% in absolute values. The algorithms in SALTIRSOIL have been verified and SALSOLCHEM validated for the reliable calculation of soil salinity, sodicity and alkalinity at water saturation in well-drained irrigated lands. In simulations for horticultural crops in southeast Spain, soil solution concentration factors at water saturation, quotients of electrical conductivity (EC(25)) at saturation to electrical conductivity in the irrigation water, and quotients of sodium adsorption ratio (SAR) are very similar to average measured values for the area.

#### Comparison of four steady-state models of increasing complexity for assessing the leaching requirement in agricultural salt-threatened soils

- Visconti, Fernando
- Paz, Jose Miguel de
- Rubio, J. L.
- Sanchez, J.

Irrigation scheduling in salt-threatened soils must include an estimation of the leaching requirement (LR). Many models have been developed over the last 40 years for assessing the LR, and they should be compared on common grounds to guide potential users. The LR for salts (LR gamma), chloride (LRCI) and SAR (LRSAR) and therefore the eventual LR was assessed with simple equations and three steady-state computer models of increasing complexity, WATSUIT, SALSODIMAR and SALTIRSOIL. These models were assessed in 30 scenarios characterised by different crops and water qualities in the irrigated area of the Vega Baja del Segura (SE Spain). The simple equations, WATSUIT and SALTIRSOIL calculated quite similar eventual LRs, which were between 0.99 depending on crop species and water quality. The SALSODIMAR gave remarkably higher eventual LRs (between 0.31 and > 0.99). This occurred because SALSODIMAR uses the hypothesis that the saturation extract is more concentrated than the drainage water, contrary to what is assumed by the simple equations or calculated by WATSUIT and SALTIRSOIL. Rainfall, which is not taken into account by the simple equations and WATSUIT, and soil calcite weathering, which is not taken into account by SALSODIMAR, were revealed, respectively, as important and very important aspects to be included in steady-state models. Although the SALTIRSOIL appears to be the most complete model, the simple equations give acceptably similar irrigation doses for many of the situations considered in this study. Irrigation doses lower than presently used could be profitably applied in the Vega Baja del Segura.

#### A combined equation to estimate the soil pore-water electrical conductivity: calibration with the WET and 5TE sensors

- Visconti, Fernando
- Martinez, Delfina
- Jose Molina, Maria
- Ingelmo, Florencio
- Paz, Jose Miguel de

Affordable, commercial dielectric sensors of the frequency domain reflectometry (FDR) and capacitance-conductance (CC) types estimate the dielectric permittivity (epsilon(b)) and electrical conductivity (sigma(b)) of bulk soil. In this work, an equation was obtained to estimate the pore-water electrical conductivity (sigma(p)), which is closely related to the soil salinity in contact with plant roots, from epsilon(b) and sigma(b) data, by combining the simplified dielectric mixing (SDM) model that relates epsilon(b) to the soil volumetric water content (theta), with the Rhoades equation that relates theta and sigma(b) to sigma(p). This equation was calibrated with measurements of epsilon(b) and sigma(b) 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 theta and sigma(p) values. The sp 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 sigma(p) subsequently provided root mean square deviations of 3.1 (WET) and 4.1 (5TE) dSm(-1), which decreased to 1.5 and 2.6 dSm(-1) for theta > 0.22m(3)m(-3), and sigma(b) 0.22m(3) m(-3) and sigma(b) < 3.7 dSm(-1).

#### Principal component analysis of chemical properties of soil saturation extracts from an irrigated Mediterranean area: Implications for calcite equilibrium in soil solutions

- Visconti, Fernando
- De-Paz, José M.
- Luis Rubio, Jose

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, NH(4), K, Mg, Ca, Cl, NO(2), NO(3), SO(4), 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. (C) 2009 Elsevier B.V. All rights reserved.

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