Designing and optimizing an Electrical Resistivity Tomography (ERT) time lapse acquisition for mapping hedgerow impacts on water transfers

Hedgerows have an a priori beneficial influence on hillslope hydrology in the context of climate change. Thanks to their root network, they enhance the infiltration of rainwater or upcoming runoff (Wallace et al., 2021). However, the fate of the water that infiltrates under the hedgerows has not been quantified: evapotranspiration, runoff, groundwater recharge, subsurface runoff to the watercourse. This is a crucial question to better understand the role of hedgerows in hillslope hydrology and the fate of associated contaminants. In this context, we plan to deploy a hydrogeophysical study based on Electrical Resistivity Tomography (ERT) time lapse to investigate the infiltration processes beneath a hedgerow located on a long-term observatory catchment near Lyon, France (Lagouy et al., 2015). Time-lapse ERT has significantly developed in recent years to provide quantitative measurements of subsurface properties and relevant information on hydrological processes, particularly water infiltration into soils (Brunet et al., 2011). Yet geophysical experimental setups are often designed heuristically and seldom optimized a priori (i.e. without specific optimization procedure beforehand). In our case, considering that the development of Open Source resistivity meter such as Ohmpi (Clement et al., 2020) will make it possible to monitor hydrological processes intensively, the aim is to optimize our acquisition strategy to obtain a compromise between the best image and a minimal acquisition time.

In order to ensure that our experimental hydrogeophysical setup is « data worth » and optimized for our field applications, we adapted a classical numerical approach to generate data (referred to as numerical experiments) to size and design our experimental parametrization of an ERT acquisition. Therefore, we investigate the unit of electrode spacing in order to (i) achieve the desired optimal resolution beneath the hedgerow (to enhance the monitoring of hydrological flows), (ii) maintain a sufficient depth of investigation (to visualize water table fluctuations and to study the soil and root properties of the hedgerows), and (iii) select the most appropriate electrode configuration (Wenner, Dipole-dipole, Schlumberger) for the specific studied site. To validate this approach, we simulated resistivity anomalies similar to those expected in the field (as the result of soil heterogeneity or soil wetting due to rainfall events and preferential flows). These simulations were rendered by ERT after the inversion step and compared to the prescribed field of electrical resistivity. The objective was to determine if we could detect these types of resistivity heterogeneities and which resistivity gaps were detectable. Besides these considerations, several key questions arise regarding the time of experimental design. Specifically, we tested different sequencing strategies to optimize measurements and minimize acquisition time. Finally, field tests will be conducted to validate this « data worth » experiment and validate the gain in acquisition time while minimizing the loss in ERT image rendering.

References

Brunet et al., 2010, Journal of Hydrology, 10.1016/j.jhydrol.2009.10.032.

Clément et al. 2020, HardwareX, 10.1016/j.ohx.2020.e00122.

Lagouy et al., 2015, 10.17180/OBS.YZERON.

Wallace et al., 2021, Hydrological Processes, 10.1002/hyp.14098.