Monitoring for temporal changes in soil salinity using electromagnetic induction techniques

Abstract

Electromagnetic induction surveys are often used in practice to estimate field-scale soil salinity patterns, and to infer changing salinity conditions with time. We developed a statistical monitoring strategy that uses electromagnetic induction data and repetitive soil sampling to measure changing soil salinity conditions. This monitoring approach requires (i) the estimation of a conditional regression model that is capable of predicting soil salinity from electromagnetic (EM) survey data, and (ii) the acquisition of new soil samples at two or more previously established survey sites, so that formal tests can be made on the differences between the predicted and observed salinity levels. We examined two test statistics in detail: a test for detecting dynamic spatial variation in the new salinity pattern and a test for detecting a change in the field median salinity level with time. We applied this monitoring and testing strategy to two EM survey-soil salinity data sets collected at multiple points in time from the saline irrigation district of Flumen, Spain, Our results demonstrate that this monitoring approach was successfully able to quantify the temporal changes in the soil salinity patterns occurring within these two fields.