Water transport in agricultural soils estimated by time-lapse electrical resistivity tomography technique

It is well-recognized that soil moisture plays an important role in the management of water resources, as well as soil and crop production. This research proposed the use of time-lapse Electrical Resistivity Tomography (ERT) to overcome the limitations of point-based soil moisture measurement, which often fails to capture detailed spatiotemporal data. ERT is a widely used geophysical technique for the non-destructive exploration of subsurface media’s resistivity. Since the electrical resistivity is sensitive to the water content in soil, the variation of the soil’s resistivity in time and space can be obtained by using this technique that can be correlated to water transport in soil. Thus, using time-lapse ERT for the exploration of water transport in the soil was launched in this study.

This research conducted a time-lapse ERT survey executed in a farm during a sprinkling rainfall. A 50 meters time-lapse ERT survey was employed for 29 days with a hybrid-array configuration at a fallow land. The electrode spacing was 1 meter and measurement were conducted every 2 hours, thus a resistivity section of the land with 50 meters in length and 4 meters in depth was estimated with a period of 2 hours. In addition, five moisture meters were set up in the middle of the ERT survey line and at depths of 10, 20, 30, 50, and 100 cm, respectively. Then, the variation of the resistivity was compared with the precipitation data and the soil moisture readings from the meters. The results showed that the decrease of soil resistivity was consistent with the increase of the precipitation and soil moisture. The water transport rates in soils estimated by this technique and moisture meters were similar, they were 20 mm/hour and 16 mm/hour, respectively.

This study demonstrates that time-lapse ERT is an effective tool for dynamically monitoring water transport in soils. By employing this technique, near real-time 2D soil moisture monitoring becomes feasible, which could significantly enhance the optimization of water resources and crop production, when integrated with an automatic irrigation system.