Monitoring for Temporal Changes in Soil Salinity using Electromagnetic Induction Techniques

struments have received the most attention for field- scale agricultural applications, particularly the EM-38. Electromagnetic induction surveys are often used in practice to In 1992, Diaz and Herrero discussed the monitoring estimate field-scale soil salinity patterns, and to infer changing salinity of soil salinity conditions with time in two fields using conditions with time. We developed a statistical monitoring strategy EM-38 survey data. In their study, both EM-38 and that uses electromagnetic induction data and repetitive soil sampling sample soil salinity data were collected at multiple to measure changing soil salinity conditions. This monitoring approach requires (i) the estimation of a conditional regression model that is points in time within each field. The focus of the study capable of predicting soil salinity from electromagnetic (EM) survey was to examine various ways that one might use the data, and (ii) the acquisition of new soil samples at two or more multistage EM-38 survey data to monitor and predict previously established survey sites, so that formal tests can be made the time-dependent changes occurring in the field-scale on the differences between the predicted and observed salinity levels. soil salinity conditions. Their data sets are rather unique We examined two test statistics in detail: a test for detecting dynamic in that they represent one of the few published data spatial variation in the new salinity pattern and a test for detecting sets where both EM-38 and soil salinity data have been a change in the field median salinity level with time. We applied this acquired at multiple points in time from within the monitoring and testing strategy to two EM survey-soil salinity data same fields. sets collected at multiple points in time from the saline irrigation A comprehensive statistical methodology for the pre- district of Flumen, Spain. Our results demonstrate that this monitoring diction of soil salinity using EM signal data was sug- approach was successfully able to quantify the temporal changes in gested by Lesch et al. (1995a,b). This prediction ap- the soil salinity patterns occurring within these two fields. proach was based on the development of field-specific multiple linear regression models that could be used to predict soil salinity levels from EM-38 survey data.