Assessing The Dynamics Of Soil Salinity With Time-Lapse Inversion Of Electromagnetic Data Guided By Hydrological Modelling

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 (sigma(a)) data were collected four times during the experiment period using the CMD Mini-Explorer. Prior to inversion of time-lapse sigma(a) 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 (sigma(b)), which in turn were used to obtain known structures of apparent electrical conductivity, sigma(a). These synthetic distributions were used for a preliminary understanding of how the physical context may influence the EMI-based sigma(a) readings carried out in the monitored transects as well as being used to optimize the smoothing parameter to be used in the inversion of sigma(a) readings. With this prior information at hand, we inverted the time-lapse field sigma(a) 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.