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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 σb measurements. 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−1 degrees 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. [ABSTRACT FROM AUTHOR]

Abstract: This study has investigated the possibility for monitoring simultaneously and continuously the relationship between the macroscopic crop response and the evolution of water content, electrical conductivity and root density along the soil profile during the whole growing season of a tomato crop under different salinity treatments. Water storages measured by TDR sensors were used for calculating directly the actual water uptake by the root system along the whole soil profile under the different salinity levels imposed during the experiments. It was observed that during irrigation with saline water the salt content increased along the whole profile but that it tended to accumulate quite uniformly below the 20cm in the case of the 4 dSm-1 treatment and at depth between 15 and 25cm in the case of the 8dSm-1 salinity treatment. Compared to the reference freshwater treatment, the evapotranspiration under salinity treatments started to decrease at a threshold value of the time-depth average electrical conductivity (EC) of soil water of about 3dSm-1. Based on the results of soil and plant monitoring, the root uptake process was simulated by using a model for water and solute flow in the soil-plant-atmosphere continuum. This way, the root activity reduction at each depth-node was calculated as a function of the salinity (and eventually water) stress. This enabled relating the distribution of higher/lower activity of root uptake along the soil profile in response to the actual distribution of salts. [Copyright &y& Elsevier]

Abstract: In recent years, several studies have been conducted both in saturated and unsaturated soils to detect non-aqueous phase liquid (NAPL) hydrocarbon contamination in soils and groundwater by means of the time domain reflectometry (TDR) technique. This technique is widely used for measuring the dielectric permittivity and bulk electrical conductivity of multiphase systems. Only accurate knowledge of the dielectric response of soil matrix- water-NAPL (saturated condition) or soil matrix-air-water-NAPL (unsaturated condition) systems can allow the volumetric NAPL content (θNAPL) to be determined in the soil. This paper investigates the influence of NAPL contamination (corn oil, a non-volatile and non-toxic NAPL, was used) on TDR measurement in a volcanic soil, relating dielectric permittivity of the multiphase soil system to volumetric fluid content θf (i.e. water+NAPL). The soil samples were oven dried at 105°C and passed through a 2mm sieve. Known quantities of soil, water and oil were mixed and repacked into plastic cylinders (15cm high and 9.5cm in diameter); 40 different combinations of water and oil were tested, with θNAPL varying from 0.05 to 0.40 by 0.05cm3/cm3 increments. A volumetric mixing model with three (soil matrix-water-NAPL) or four (soil matrix-air-water-NAPL) phases permitted conversion from a dielectric permittivity domain into a θf domain. The results show that, the amount of contaminant in soil can be inferred if the total volume of pore fluid θf and the dielectric permittivity of the contaminated soil are known. Further work will be built on this initial study, concentrating on: i) enhancing the model linkage and validating it with new laboratory results; ii) validating the developed TDR interpretation tool with field results. [Copyright &y& Elsevier]