Joint identification of contaminant source location, initial release time, and initial solute concentration in an aquifer via ensemble Kalman filtering

Abstract

When a contaminant is detected in a drinking well, source location, initial contaminant release time, and initial contaminant concentration are, in many cases, unknown; the responsible party may have disappeared and the identification of when and where the contamination happened may become difficult. Although contaminant source identification has been studied extensively in the last decades, we propose—to our knowledge, for the first time—the use of the ensemble Kalman filter (EnKF), which has proven to be a powerful algorithm for inverse modeling. The EnKF is tested in a two-dimensional synthetic deterministic aquifer, identifying, satisfactorily, the source location, the release time, and the release concentration, together with an assessment of the uncertainty associated with this identification.