Towards a better representation of the subsurface across the continental US : developing hydraulic conductivity datasets for integrated hydrologic models

Abstract

Groundwater is the largest source of accessible freshwater, accounts for over 30% of total water use worldwide, and is intrinsically connected to land-surface processes. Groundwater flow is largely influence by hydraulic gradients and the properties of the porous media, such as hydraulic conductivity. The methods by which hydraulic conductivity is measured vary greatly among local, regional, and global scale measurements. Local-scale measurements can be made through borehole tests, and large-scale conductivity values are regularly regarded as the geometric mean of local-scale measurements. Effective conductivity values vary greatly with scale, leading to uncertainty in aggregated representations. Borehole and survey data gaps exist spatially which further exacerbated observational data limitations for informing aggregated estimates. This creates a scale dependent challenge that relies upon a variety of data types, each with its own inherent limitations. The work presented here improves current regional permeability estimations by developing a new continental-scale hydraulic conductivity product. A previously published approach for estimating hydraulic conductivity from morphologic patterns was adapted and extended to the continental US. The geometric mean value from the new hydraulic conductivity product are comparable to existing continental-scale datasets. The density distribution of values from the new product shows less bimodality than other products, though exhibits an East-West trend. This indicates that the methodology captures more heterogeneity in conductivity values than other methods. The product developed here joins a growing number of products that improve our hydrologic understanding of North America. It will serve as a community resource for populating large scale models which will improve our understanding of how water flows through the Earth’s crust.