Buried Paleo-Channel Detection With a Groundwater Model, Tracer-Based Observations, and Spatially Varying, Preferred Anisotropy Pilot Point Calibration

Abstract

Alluvial sand and gravel (ASG) aquifers are highly heterogeneous and exhibit strong, spatially variable anisotropy, often interspersed by buried paleo-channels of increased hydraulic conductivity. Groundwater flow and solute transport is often characterized by preferential flow caused by anisotropic properties in ASG aquifers. Connected ASG subsurface structures such as buried paleo-channels, however, are difficult to reproduce with commonly used techniques, and anisotropy is rarely considered in applied groundwater models. To ease the notoriously difficult problem of how to consider anisotropy, we propose a novel modeling framework based on calibration of an integrated surface-subsurface hydrological model via spatially varying, preferred anisotropy pilot point inversion. The inversion leverages hydraulic and tracer-based observations representing multiple spatial and temporal scales. We demonstrate the applicability of the framework on a real-world ASG site used for drinking water production, and we quantify the information content of observations to identify connected paleo-channels and provide guidance for optimal field-data acquisition.