Abstract. 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.
Assessing the dynamics of soil salinity with time-lapse inversion of electromagnetic data guided by hydrological modelling
