Search

Determining soil hydraulic and hydrodispersive properties is crucial for the sustainable management of water resources and agricultural land. Due to the local heterogeneity of soil hydrological properties and the lack of fast in-situ measurement techniques, it is hard to assess these properties at the field scale. The present study proposes a methodology based on the integration of Electromagnetic Induction (EMI) and hydrological modeling to estimate soil hydraulic and transport properties at the field scale. To this aim, two sequential water infiltration and solute transport experiments were carried out over a small field plot. The propagation of wetting front and solute concentration along the soil profile was monitored using an EMI sensor (i.e. CMD mini-Explorer), Time Domain Reflectometry (TDR) probes, and tensiometers. Time-lapse apparent electrical conductivity (σa) data obtained from the EMI sensor were inverted to estimate the evolution of the vertical distribution of the bulk electrical conductivity (σb) over time. The σb distributions were converted to water content and solute concentration by using a laboratory calibration, relating σb to water content (θ) and soil solution electrical conductivity (σw). The hydraulic and hydrodispersive properties were then obtained by an optimization procedure minimizing the deviations between the numerical solution of the water flow and solute transport processes and the estimated water contents and concentrations inferred from the EMI results. The EMI-based results were finally compared to the results obtained from the in-situ TDR and tensiometer measurements. In general, the EMI readings lead to underestimated water contents as compared to the TDR data. And yet, the water content changes over time detected by the EMI closely followed those observed by TDR and contain enough information for effective EMI-based reconstructions of water retention and hydraulic conductivity curves for the soil profile. In addition, this allowed us to reproduce the solute concentration distributions and thus the hydro-dispersive properties of the soil profile. Overall, the results suggest that time-lapse EMI measurements could be used as a rapid, non-invasive, field-scale method to assess soil hydraulic and hydro-dispersive properties, which are critical to hydrological models for agro-environmental applications.

Olive mill wastewater (OMW) is a compound originating from oil mills during oil extraction processes. In the Mediterranean area, more than 30 million m3 of OMW are produced each year, which represents 95-97% of the world production. Such volumes of untreated OMW are usually directly disposed of into drainage systems, water bodies (such as streams, lagoons and ponds) or are sprinkled on soils, causing potentially severe environmental problems to soils and groundwater. Consequently, there is a serious waste management problem related to the olive oil industry, because these practices no longer being acceptable. In the case of on-land OMW disposal, the characterization and the identification of this contaminant in soils is a fundamental task especially with a view to maintaining the integrity and quality of agroecosystems. In recent years, soils have been extensively studied to detect contaminants by using various geophysical methods. Among such techniques, time domain reflectometry (TDR) has shown, in different contexts, evident sensitivity and resolution capability for the characterization of contaminated soil sites. In order to further exploit the potential of the TDR technique, in this study we conducted a series of laboratory-controlled tests to explore how OMW influences the dielectric response of contaminated soils. This investigation led to the development of an empirical dielectric model to estimate the presence of OMW in variably saturated-contaminated soils with different textures and pedological features. In particular, the soils selected belong to two typical pedological units in southern Italy which account for approximately 90% of the Italian olive plantations and one of the highest concentrations of the olive oil industry in Italy. In these districts, as well as in other European and Mediterranean countries, there is the controversial habit to spread OMW on soils.

The term non-aqueous phase liquid (NAPL) refers to a group of organic compounds with scarce solubility in water. They are the products of various human activities and may be accidentally introduced into the soil system. Given their toxicity level and high mobility, NAPLs constitute a serious geo-environmental problem. Contaminant distribution in the soil and groundwater contains fundamental information for the remediation of polluted soil sites. The present research explored the possible employment of time domain reflectometry (TDR) to estimate pollutant removal in a silt-loam soil that was primarily contaminated with a corn oil as a light NAPL and then flushed with different washing solutions. Known mixtures of soil and NAPL were prepared in the laboratory to achieve soil specimens with varying pollution levels. The prepared soil samples were repacked into plastic cylinders and then placed in testing cells. Washing solutions were then injected upward into the contaminated sample, and both the quantity of remediated NAPL and the bulk dielectric permittivity of the soil sample were determined. The above data were also used to calibrate and validate a dielectric model (the α mixing model) which permits the volumetric NAPL content (θNAPL; m3 m−3) within the contaminated sample to be determined and quantified during the different decontamination stages. Our results demonstrate that during a decontamination process, the TDR device is NAPL-sensitive: the dielectric permittivity of the medium increases as the NAPL volume decreases. Moreover, decontamination progression can be monitored using a simple (one-parameter) mixing model.

Irrigation with Treated Wastewater (TWW) is a well-known and long-established agricultural practice in Palestine. Being a source of water and nutrients, long term use of TWW can lead to imbalances that affect plant development, soil, and groundwater quality. Consequently, irrigation frequency and interval should be properly scheduled, especially when Salts and Fertilizers (FS-TWW) cannot be separated from water.Physically based models may be relevant tools to support an adequate irrigation management with TWW for a simultaneous supply of water and fertilizers assessed pursuant to the effects of TWW on soil properties and water fluxes into and out of the root zone.The present research was conducted in the framework of Non Conventional WAter Re-use in Agriculture in MEditerranean countries (MENAWARA) ENI CBC Med project, with the aim to propose an alternative TWW irrigation management based on both water requirements and allowable thresholds of soil solution electrical conductivity (ECe), to prevent soil salinity using physically-based Hydrus-1D model.To this purpose, a case study in Beit Dajan cultivated with citrus and irrigated with TWW was selected to determine the long term effects of TWW on the soil and on root uptake, considering a two-year (2018-2019) simulations and generating two FS-TWW irrigation scenarios: 1) non-optimized salt supply (NONOPT-FS-TWW) where irrigation volumes fully satisfied crop evapotranspiration demand: 2) optimized salt supply (OPT-FS-TWW) accounting for crop evapotranspiration and respecting allowable thresholds of soil solution electrical conductivity (ECe) by assuming an average soil salinity tolerance in the root zone.Soil water movement, ECe, nitrate and ammonium concentrations were simulated, inputting averaged ten-yearly climate data and soil and water quality data measured at the end of each of the two considered years. The results in terms of soil salinity and root uptake impact are considered to define a proper TWW irrigation management for citrus.The outputs of the scenario OPT-FS-TWW clearly demonstrate the reduction of soil salinity in the root zone, and of water and nutrient fluxes below 60cm, and thus an improvement of water and nutrient uptake, as compared to NON-OPT-FS-TWW scenario.The results suggest that aligning the classical irrigation practices to TWW reuse by considering ECe as an additional variable is appropriate, allows to curb soil salinity, and ensures root water uptake of citrus, although TWW has high salinity levels that may jeopardize plant response after a sequence of irrigation events.

Irrigated agriculture is threatened by soil salinity in numerous arid and semi-arid areas of the world, chiefly caused by the use of highly salinity irrigation water, compounded by excessive evapotranspiration. Given this threat, efficient field assessment methods are needed to monitor the dynamics of soil salinity in salt-affected irrigated lands and evaluate the performance of management strategies. In this study, we report on the results of an irrigation experiment with the main objective of evaluating time-lapse inversion of electromagnetic induction (EMI) data and hydrological modelling in field assessment of soil salinity dynamics. Four experimental plots were established and irrigated 12 times during a 2-month period, with water at four different salinity levels (1, 4, 8 and 12 dS m−1) using a drip irrigation system. Time-lapse apparent electrical conductivity (σa) data were collected four times during the experiment period using the CMD Mini-Explorer. Prior to inversion of time-lapse σa data, a numerical experiment was performed by 2D simulations of the water and solute infiltration and redistribution process in synthetic transects, generated by using the statistical distribution of the hydraulic properties in the study area. These simulations gave known spatio-temporal distribution of water contents and solute concentrations and thus of bulk electrical conductivity (σb), which in turn were used to obtain known structures of apparent electrical conductivity, σa. These synthetic distributions were used for a preliminary understanding of how the physical context may influence the EMI-based σa readings carried out in the monitored transects as well as being used to optimize the smoothing parameter to be used in the inversion of σa readings. With this prior information at hand, we inverted the time-lapse field σa data and interpreted the results in terms of concentration distributions over time. The proposed approach, using preliminary hydrological simulations to understand the potential role of the variability of the physical system to be monitored by EMI, may actually allow for a better choice of the inversion parameters and interpretation of EMI readings, thus increasing the potentiality of using the electromagnetic induction technique for rapid and non-invasive investigation of spatio-temporal variability in soil salinity over large areas.

Double ring infiltrometer is a simple device used to measure water infiltration rate in the soil, one of the most important hydro physical characteristics and an essential parameter for various applications including: surface irrigation and drainage projects, infiltration or water purification basins, seepage losses at canals, soil leaching at waste storage sites. However, the high spatial variability of a soil makes a single point measurement rarely representative of an entire field. Nonetheless, Double Ring Infiltration tests are tedious, time consuming and require continuous attention, hence limiting the number of tests that may be performed simultaneously on a given site. In the present research, an automated Internet of Things (IoT) double ring infiltrometer (DRI) is developed and validated in a loamy field. It consists of a DRI equipped with an ESP-32 microcontroller chip, a GPS module, a solenoid valve, a DIY conductance water level sensor, and a SD card module powered by a 12 V 11000mAh Li-ion battery charged by a 10 W solar panel. The double ring infiltrometer is designed to calculate the infiltration rate in real time, to store the data with the time stamp and geographical coordinates on an SD card or, to use a cloud service platform to upload the data over the internet. The aim is to facilitate soil infiltration mapping for precision agriculture and to build a soil infiltration inventory that could be used to continuously improve existing soil database. The system was assembled and tested at nine different locations on a loamy soil experimental field. For validation, conventional (manually operated) tests were conducted at the same time. The system proved to be reliable (R2 = 0.99), cost effective (115$) and a hassle-free solution, ideal for multiple soil infiltration measurements.

Management of saline water irrigation at the field scale requires electrical conductivity to be monitored regularly in the generally shallow soil layer explored by plant roots. Non-invasive electromagnetic induction (EMI) sensors might be valuable for evaluating large-scale soil salinity. However, obtaining information on soil surface salinity from depth-integrated EMI measurements requires either an inversion of the electromagnetic signal or an empirical calibration. We opted for an empirical calibration of an EM38 sensor, which requires a reference dataset of local bulk electrical conductivity, σb, for comparison with EMI readings for estimating regression coefficients. We used time-domain reflectometry (TDR) to replace direct sampling for local σbmeasurements. With empirical approaches, the different soil volumes involved with the EMI and TDR sensors become problematic. We resolved this issue by analysing large EMI and TDR datasets recorded at several times along three transects irrigated with water at 1, 3 and 6 dS m−1degrees of salinity. A Fourier filtering technique was applied to remove the high frequency part (at small spatial scales) of the variation in the original data, which was the main source of dissimilarity between the two datasets. Therefore, calibration focused on the lower frequency information only; that is, information at a spatial scale larger than the observation volume of the sensors. We show that information from the TDR observations derives from a combination of local and larger scale heterogeneities, and how it should be managed for calibration of the EMI sensor. Analysis enabled us to identify characteristics of the calibration data that should be included to improve prediction. Highlights: EMI and TDR sensors have different observation volumes and are not immediately comparable. With Fourier filtering the different observation volumes were accounted for in calibration of the EMI data. We improved the empirical calibration between EMI and TDR datasets. We identified criteria to select data series for EMI sensor calibration.

The knowledge of the longitudinal dispersivity parameter is necessary to simulate solute transport in porous media. The direct measurement of this parameter is expensive and time consuming. Indirect methods based on the inverse modelling procedure provide an easier and reliable alternative, if measurements of solute concentration and soil water content are available. In this study, Hydrus 1D model was coupled with apparent electrical conductivity measured by means of the simple and rapid electromagnetic induction (EMI) technique in order to determine the longitudinal dispersion parameter in a sandy soil. By means of forward Hydrus 1D simulations the temporal distribution of soil water content in 1 m depth soil profile was obtained. The soil water content and the inverted soil electrical conductivity were implemented in the Rhoades linear equation in order to determine the distribution of the soil solution electrical conductivity. Thereby, the longitudinal distribution parameter was finally determined by carrying out Hydrus 1D inversions. The estimated dispersion parameter was 10.23 cm. The proposed procedure allows to obtain reasonable values of longitudinal dispersion with a good degree of approximation.

The term non-aqueous phase liquid (NAPL) refers to a group of organic compounds with scarce solubility in water. They are the products of various human activities and may be accidentally introduced into the soil system. Given their toxicity level and high mobility, NAPLs constitute a serious geo-environmental problem. Contaminant distribution in the soil and groundwater entails fundamental information for the remediation of polluted soil sites. The present research explored the possible employment of time domain reflectometry (TDR) to estimate pollutant removal in a silt-loam soil that was primarily contaminated with a light hydrocarbon and then flushed with diverse washing solutions. Known mixtures of soil and NAPL were prepared in the laboratory to achieve soil specimens with diverse pollution levels. The prepared soil samples were repacked into plastic cylinders and then placed in testing cells. Washing solutions were then injected upward into the contaminated sample, and both the quantity of remediated oil and the bulk dielectric permittivity of the soil sample were determined. The above data was also used to develop a dielectric model (the α mixing model) which permits the volumetric NAPL content (θNAPL) within the contaminated sample to be determined and quantified during the different decontamination stages. Our results demonstrate that during a decontamination process, the TDR device is NAPL-sensitive: the dielectric permittivity of the medium increases as the NAPL volume decreases. Moreover, decontamination progression can be monitored using a simple (one-parameter) mixing model.

This paper mainly aims to illustrate an irrigation management tool to simulate scheduling of district-level water needs over the course of an irrigation season. The tool is mostly based on a daily model for simulating flow of water (and solutes) in heterogeneous agri-environmental systems (called FLOWS-HAGES). The model produces information on the daily evolution of: soil water contents and pressure potentials in the soil profile, water uptake and actual evapotranspiration, stress periods for each crop, return fluxes to the groundwater and their quality in terms of solute concentrations (e.g., nitrates). FLOWS-HAGES provides a daily list of hydrants to be operated according to water or crop-based criteria. The daily optimal sequence of hydrant use may thus be established by passing the volumes to be delivered on to the model for simulating the hydraulics of the irrigation network, in order to ensure that the discharges flowing inside the network of distribution pipes are delivered under optimal pressure head distribution in the system. All the above evaluations can be carried out in a stochastic framework to account for soil heterogeneity and climate changes. To illustrate the potential of FLOWS-HAGES, a case study was considered for a selected sector of the Irrigation District 10 in the &ldquo, Sinistra Ofanto&rdquo, irrigation system (southern Italy, Apulia region). In a 139 ha area (Sector 6 of the Irrigation District), soil profiles were analyzed for characterization of hydraulic properties variability. Hydraulic properties were determined by a combination of field and laboratory measurements. Model simulations were validated by comparing soil water storage simulated and measured by a sensor based on electromagnetic induction technique. Irrigation water volumes and frequency calculated by the model were compared to the volumes actually supplied by the farmers. Compared to the farmers behavior, the model simulates more frequent irrigations with lower irrigation volumes. Finally, some indexes of irrigation performance were calculated for each farm under study. The resulting maps provide useful information on the spatial distribution of farmer behavior, indicating the abuse or underuse of water as well as the fraction of the water lost by drainage following the irrigation method applied.

Salinization has been identified as a major cause of soil degradation in countries around the Mediterranean. Soil salinization limits agricultural productivity and can ultimately cause desertification and abandonment of the land. Salinization can also affect the quality of both ground and surface water resources, degrade infrastructures, and decrease biodiversity. Such effects represent major negative social, economic, and environmental impacts. The ecological conditions of the Mediterranean region favour salt accumulation in soils. Furthermore, agricultural practices such as irrigation and fertilization may further promote salt accumulation and accelerate land degradation in Mediterranean environments. It is important to understand the processes controlling salinization in order to prevent further soil degradation. Traditional soil sampling methods, which require boreholes for soil sampling and analysis, difficultly lead to a comprehensive answer to this problem. This is because they cover only small and localized sites and may not be representative of the soil properties at the management scales. Furthermore, they are highly time and work consuming, resulting in costly surveys. Geophysical methods provide enormous advantageous compared to traditional methods of soil sampling because they allow for in-depth and non-invasive analysis, covering large areas in less time and at a lower cost. The SALTFREE project is developing a framework for the evaluation of the salinization risk in the management scale, using state-of-the-art electromagnetic (EM) technique, in irrigated production systems in the Mediterranean basin. The project consortium is formed by five partners from four countries around the Mediterranean - Egypt, Italy, Portugal, and Tunisia in the scope of ARIMNET2 program.

Recent research shows how soil information can be generated quickly and cheaply, by using a state-of-the-art electromagnetic (EM) instrument and the inversion method to generate high-resolution EM conductivity images (EMCI). EM instruments have the advantages of being faster, less expensive, and also to collect data easier than the common Electrical Resistivity Tomography (ERT) method, which makes EM adequate to cover a larger area in regional studies. However, the capability of the technique is limited in mapping soil dynamic parameters (i.e. water content, salinity) due to the lack of a time-lapse inversion algorithm. While several time-lapse inversion algorithms have been developed for modeling of time-lapse ERT data in order to reduce the inversion artefact, no attempt has been made to implement a time-lapse inversion algorithm to invert the EM data. Developing a time-lapse inversion algorithm for EM data is, therefore, a determined step forward for application of EM instruments in characterization of the soil's dynamic parameters where a multiple datasets is required. We developed a time-lapse inversion algorithm where a spatiotemporal objective function is minimized and we evaluated the algorithm by performing several synthetic tests. The developed program will be applied to the field data collected in the scope of the SALTFREE project to image spatiotemporal variability of soil salinity. The project consortium is formed by five partners from four countries around the Mediterranean - Egypt, Italy, Portugal, and Tunisia in the scope of ARIMNET2 program and aims to develop a framework for the evaluation of the salinization risk in the management scale.

Reliable parameterizations of water uptake under osmotic stresses depend on the appropriate description of the interacting effects of root distribution and activity over the root zone. These effects should be evaluated under transient salinity conditions. To show that, a crop was irrigated with three salinity inputs using a randomized block design. Root-zone water storage and pressure heads measured at the bottom of the root zone allowed to calculate the evapotranspiration under the different salinity levels imposed. Root densities were measured by direct sampling twice during the growth season. Transpiration was distributed along the root zone according to a Feddes-type sink term and a reduction function accounting for osmotic stress. These data allowed evaluating the effects on the reduction function of (1) the actual salinity and root distributions under different osmotic stress and (2) discontinuous osmotic stress conditions occurring locally in the root zone because of salt leaching. When considering the space–time salinity distribution and the specific root distribution, a unique reduction curve was found, independently of the salinity level of the irrigation water. The effect of discontinuous stress was modelled by introducing (1) a hysteretic behaviour in the salinity reduction function, to be applied only to root compartments actually experiencing discontinuous stress and (2) a scaling factor acting on the whole root zone, based on the ratio of the actual (induced by salinity) to the potential root density. Results suggested that the reduction of transpiration under salinity may be partly caused by irreversible physiological adaption of the roots to saline stress and partly by reduced root density. Copyright © 2014 John Wiley & Sons, Ltd.

This paper deals with the issue of monitoring the spatial distribution of bulk electrical conductivity, σb, in the soil root zone by using electromagnetic induction (EMI) sensors under different water and salinity conditions. To deduce the actual distribution of depth-specific σb from EMI apparent electrical conductivity (ECa) measurements, we inverted the data by using a regularized 1-D inversion procedure designed to manage nonlinear multiple EMI-depth responses. The inversion technique is based on the coupling of the damped Gauss–Newton method with truncated generalized singular value decomposition (TGSVD). The ill-posedness of the EMI data inversion is addressed by using a sharp stabilizer term in the objective function. This specific stabilizer promotes the reconstruction of blocky targets, thereby contributing to enhance the spatial resolution of the EMI results in the presence of sharp boundaries (otherwise smeared out after the application of more standard Occam-like regularization strategies searching for smooth solutions). Time-domain reflectometry (TDR) data are used as ground-truth data for calibration of the inversion results. An experimental field was divided into four transects 30 m long and 2.8 m wide, cultivated with green bean, and irrigated with water at two different salinity levels and using two different irrigation volumes. Clearly, this induces different salinity and water contents within the soil profiles. For each transect, 26 regularly spaced monitoring soundings (1 m apart) were selected for the collection of (i) Geonics EM-38 and (ii) Tektronix reflectometer data. Despite the original discrepancies in the EMI and TDR data, we found a significant correlation of the means and standard deviations of the two data series; in particular, after a low-pass spatial filtering of the TDR data. Based on these findings, this paper introduces a novel methodology to calibrate EMI-based electrical conductivities via TDR direct measurements. This calibration strategy consists of a linear mapping of the original inversion results into a new conductivity spatial distribution with the coefficients of the transformation uniquely based on the statistics of the two original measurement datasets (EMI and TDR conductivities).

This paper dealt with the calibration of an EMI sensor for monitoring the time dynamics of root zone salinity under irrigation with saline water. Calibration was based on an empirical multiple regression approach largely adopted in the past and still applied in practice for its relative simplicity. Compared to the more complex inversion approaches, it requires an independent dataset of local σb measured within discrete depth intervals, to be compared to horizontal and vertical electrical conductivity (ECaH and ECaV) readings for estimating the parameters of the empirical regression equations. In this paper, we used time domain reflectometry (TDR) readings to replace direct sampling for these local σb measurements. When using this approach, there is the important issue of taking into account the effect of the different sensor observation volumes, making the readings not immediately comparable for empirical calibration. Accordingly, a classical Fourier’s filtering technique was applied to remove the high frequency part (at small spatial scale) of the original data variability, which, due to the different observation volume, was the main source of dissimilarity between the two datasets. Thus, calibration focused only on the lower frequency information, that is, the information at a spatial scale larger than the observation volume of the sensors. By this analysis, we showed and quantified the degree to which the information of the set of TDR readings came from a combination of local and larger scale heterogeneities and how they have to be manipulated for use in EMI electromagnetic induction sensor calibration.

Interpreting and predicting the evolution of non-point source (NPS) pollution of soil and surface and subsurface water from agricultural chemicals and pathogens, as well as overexploitation of groundwater resources at regional scale, are continuing challenges for natural scientists. Accordingly, in this study we present a regional-scale modeling approach for vadose zone solute leaching that is based on stochastic application of a deterministic vadose zone model describing the water flow and solute transport processes in the unsaturated zone using the Richards equation (RE) and the advective-dispersive equation (ADE), respectively. The stochastic framework (Monte Carlo technique) allows accounting for uncertainty in the vulnerability outputs. As the approach is built on physically-based equations, it may be extended to the predictions of water fluxes (i.e., groundwater recharge) in the vadose zone. The approach relies on available datasets coming from different sources (detailed pedological informa...

The apparent dielectric constant, e, of many agricultural soils, measurable with the Time Domain Reflectometry (TDR) method, may be used to estimate soil water content, u, with the Topp's empirical model. However, organic soils and those of volcanic origin do not obey this model, which has been termed ''universal''. In particular, volcanic soils have singular physical properties in terms of bulk density, porosity, surface area, and variable charge essentially arising from the state of structural aggregation of particles of the solid mineral phase. After drying and/or intensive long-term tillage in arid and semi-arid climate, properties of these soils tend to change irreversibly. These modifications affect pore-sizes distribution and more stable larger size aggregates are formed. This in turn modifies porosity, surface area, variable charge, thus changing the dielectric characteristics and the relationship u(e) of the porous system. In this paper we compare the dielectric properties of two horizons of a volcanic-vesuvian soil profile. u(e) experimental relationships were measured in the laboratory on 16 undisturbed soil samples taken from Ap and Bw horizons of the soil profile. The subsoil Bw has kept its physical characteristics, typical of a volcanic soil having better expressed andic features. By contrast, topsoil Ap has been intensively cultivated and has altered its properties, partially losing its andic features. Physically based dielectric approaches explicitly taking into account the contribution of the changed properties are necessary for comparing the dielectric properties of the two soil horizons. The experimental u(e) were thus interpreted by using Maxwell-De Loor's approach and the so-called a-model which both consider soil as a multiphase system. The Topp's model was also used for evaluating its interpretative capability for the two soil horizons. By using the multiphase models in their three- and four-phases (including the effect of the bound-water) configurations on both the unaltered subsoil and the altered topsoil, it was possible separating the contribution of thedifferent physical factors mainly involved in determining the singular dielectric properties of volcanic soils. In terms of model comparisons, we found no major differences between the three- and four-phase versions of the Maxwell-De Loor's and a-models, thus demonstrating the substantial irrelevance of the bound-water on the dielectric properties of the investigated volcanic soils. Besides, this confirms the strength of the completely physically based Maxwell-De Loor's model for interpreting soil dielectric propertieswithout using any fitting parameters.

Solute transport parameters are known to be scale-dependent due mainly to the increasing scale of heterogeneities with transport distance and with the lateral extent of the transport field examined. Based on a transect solute transport experiment, in this paper we studied this scale dependence by distinguishing three different scales with different homogeneity degrees of the porous medium: the observation scale, transport scale and transect scale. The main objective was to extend the approach proposed by van Wesenbeeck and Kachanoski to evaluating the role of textural heterogeneities on the transition from the observation scale to the transport scale. The approach is based on the scale dependence of transport moments estimated from solute concentrations distributions. In our study, these moments were calculated starting from time normalized resident concentrations measured by time domain reflectometry (TDR) probes at three depths in 37 soil sites 1 m apart along a transect during a steady state transport experiment. The Generalized Transfer Function (GTF) was used to describe the evolution of apparent solute spreading along the soil profile at each observation site by analyzing the propagation of the moments of the concentration distributions. Spectral analysis was used to quantify the relationship between the solid phase heterogeneities (namely, texture and stones) and the scale dependence of the solute transport parameters. Coupling the two approaches allowed us to identify two different transport scales (around 4–5 m and 20 m, respectively) mainly induced by the spatial pattern of soil textural properties. The analysis showed that the larger transport scale is mainly determined by the skeleton pattern of variability. Our analysis showed that the organization in hierarchical levels of soil variability may have major effects on the differences between solute transport behavior at transport scale and transect scale, as the transect scale parameters will include information from different scales of heterogeneities.

Regional-scale studies on groundwater vulnerability assessment of non-point source agrochemical contamination suffer either from no evaluation of uncertainty in data output, in that of qualitative modelling, or from prohibitively costly computational efforts, in that of deterministic modelling. By contrast, a methodology is presented here which integrates a solute transport model based on transfer function (TF) and a geographic information system (GIS). The methodology (1) is capable of solute concentration estimation at a depth of interest within a known error confidence class, (2) uses available soil survey and climatic and irrigation information and requires minimal computational cost for application and (3) can dynamically support decision-making through thematic mapping. Raw data (coming from different sources) include: i) water table depth, ii) soil texture properties, iii) land use, and iv) climatic information with reference to a study area located in southern Italy. Such information has been then manipulated in order to generate data required for the subsequent hydrological modelling. Simulated breakthrough curves were generated for each soil textural class. They are texture-based travel time probability density functions (TFtb), describing the leaching behaviour of soil profiles with similar soil hydrological properties. The latter, in turn, were estimated by indirect estimation techniques such as pedotransfer functions (PTFs) to overcome the trouble of intensive in situ and/or laboratory determinations of soil hydraulic and hydrodispersive properties, which are generally lacking for regional-scale studies. Results showed large differences in the magnitude of the different travel times and related uncertainties among different profiles. The lower or higher vulnerability was found to be mainly related to the average silt content of the soil profiles.

We present follow-up work to previous work extending the classical rigid (RGD) approach formerly proposed by Gerke and van Genuchten, to account for shrinking effects (SHR) in modeling water flow and solute transport in dual-permeability porous media. In this study we considered three SHR scenarios, assuming that aggregate shrinkage may change either: (i) the hydraulic properties of the two pore domains, (ii) their relative fractions, or (iii) both hydraulic properties and fractions of the two domains. The objective was to compare simulation results obtained under the RGD and the SHR assumptions to illustrate the impact of matrix volume changes on water storage, water fluxes, and solute concentrations during an infiltration process bringing an initially dry soil to saturation and a drainage process starting from an initially saturated soil. For an infiltration process, the simulated wetting front and the solute concentration propagation velocity, as well as the water fluxes and water and solute exchange rates, for the three SHR scenarios significantly deviated from the RGD. By contrast, relatively similar water content profiles evolved under all scenarios during drying. Overall, compared to the RGD approach, the effect of changing the hydraulic properties and the weight of the two domains according to the shrinkage behavior of the soil aggregates induced a much more rapid response in terms of water fluxes and solute travel times, as well as a larger and deeper water and solute transfer from the fractures to the matrix during wetting processes.

Contamination of soils with non-aqueous phase liquids (NAPL) constitutes a serious geo-environmental problem, given the toxicity level and high mobility of these organic compounds. To develop effective decontamination methods, characterisation and identification of contaminated soils are needed. The objective of this work is to explore the potential of dielectric permittivity measurements to detect the presence of NAPLs in soils. The dielectric permittivity was measured by Time Domain Reflectometry method (TDR) in soil samples with either different volumetric content of water (θw) and NAPL (θNAPL) or at different stages during immiscible displacement test carried out with two different flushing solutions. A mixing model proposed by Francisca and Montoro, was calibrated to estimate the volume fraction of contaminant present in soil. Obtained results, showed that soil contamination with NAPL and the monitoring of immiscible fluid displacement, during soil remediation processes, can be clearly identified from dielectric measurements. © 2013, Copyright A. Comegna et al.

Scale-dependence of solute transport parameters in soil is known to be mainly due to the increasing scale of heterogeneities with transport distance and with the lateral extent of the transport field examined. The main objective of this study was evaluating the role of stones and texture on the transition of local scale to the transport scale. The soil in question contains a significant internal heterogeneity in terms of texture and stones, changing with depth and along the horizontal extent of the experimental area. Spectral analysis was used to quantify the relationship between the solid phase heterogeneities and the scale dependence of the solute transport parameters.. In our study, the moments of BTCs were calculated starting from time-normalized resident concentrations, obtained by time domain reflectometry (TDR) probes at different depths in several soil sites along a transect. The Generalized Transfer Function was used to describe the evolution of solute spreading along the soil profile at each observation site by analyzing the propagation of the moments of the concentration distributions. Our analysis showed that the organization in hierarchical levels of soil variability may have major effects on the differences between solute transport behaviour at transport scale and transect scale, as the transect scale parameters will include information from different scales of heterogeneities.