Continental scale hydrostratigraphy: basin-scale testing of alternative data-driven approaches

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1111/gwat.13357. This is version 1 of this Preprint.

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Authors

Danielle Tijerina-Kreuzer, Jackson Swilley, Hoang Tran, Jun Zhang, Benjamin West, Chen Yang, Laura Condon, Reed Maxwell

Abstract

Integrated hydrological modeling is an effective method for understanding interactions between parts of the hydrologic cycle, quantifying water resources, and furthering knowledge of hydrologic processes. However, these models are dependent on robust and accurate datasets that physically represent spatial characteristics as model inputs. This study evaluates multiple data-driven approaches for estimating hydraulic conductivity and subsurface properties at the continental-scale, constructed from existing subsurface dataset components. Each subsurface configuration represents upper (unconfined) hydrogeology, lower (confined) hydrogeology, and the presence of a vertical flow barrier. Configurations are tested in two large-scale US watersheds using an integrated model. Model results are compared to observed streamflow and steady state water table depth (WTD). We provide model results for a range of configurations and show that both WTD and surface water partitioning are important indicators of performance. We also show that geology data source, total subsurface depth, anisotropy, and inclusion of a vertical flow barrier are the most important considerations for subsurface configurations. While a range of configurations proved viable, we provide a recommended Selected National Configuration 1 km resolution subsurface dataset for use in distributed large-and continental-scale hydrologic modeling.

DOI

https://doi.org/10.31223/X5P392

Subjects

Earth Sciences

Keywords

hydrostratigraphy, data, hydrologic modeling, continental-scale, hydrologic modeling, data, continental-scale

Dates

Published: 2023-09-11 02:36

License

CC-By Attribution-NonCommercial-NoDerivatives 4.0 International

Additional Metadata

Conflict of interest statement:
None

Data Availability (Reason not available):
Data will be publicly available upon publishing.