Optimization of ERT Surveys for Monitoring Transient Hydrological Events Using Perturbation Sensitivity and Genetic Algorithms

Abstract

A simple yet powerful algorithm is presented for the optimal allocation of electrical resistivity tomography (ERT) electrodes to maximize measurement quality. The algorithm makes use of a definition of the sensitivity of an ERT array to a series of subsurface perturbations. An objective function that maximizes the average sensitivity of a survey comprised of a large number of arrays is defined. A simple genetic algorithm is used to find the optimal ERT survey if there is a limited time allowed for survey. We further show that this approach allows for user definition of the sensitivity distribution within the targeted area. Results show clear improvement in the sensitivity distribution. The total sensitivity of the optimized survey compared with typically used surveys composed of one array type. This improved sensitivity will allow for more accurate monitoring of static and transient vadose zone processes. Furthermore, the algorithm presented may be fast enough to allow for real‐time optimization during time‐lapse surveys.