Continental Scale Hydrostratigraphy: Comparing Geologically Informed Data Products to Analytical Solutions Article Swipe
Jackson Swilley
,
D. Tijerina
,
Hoang Tran
,
Jun Zhang
,
Chen Yang
,
Laura E. Condon
,
R. M. Maxwell
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1111/gwat.13354
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1111/gwat.13354
This study synthesizes two different methods for estimating hydraulic conductivity (K) at large scales. We derive analytical approaches that estimate K and apply them to the contiguous United States. We then compare these analytical approaches to three‐dimensional, national gridded K data products and three transmissivity (T) data products developed from publicly available sources. We evaluate these data products using multiple approaches: comparing their statistics qualitatively and quantitatively and with hydrologic model simulations. Some of these datasets were used as inputs for an integrated hydrologic model of the Upper Colorado River Basin and the comparison of the results with observations was used to further evaluate the K data products. Simulated average daily streamflow was compared to daily flow data from 10 USGS stream gages in the domain, and annually averaged simulated groundwater depths are compared to observations from nearly 2000 monitoring wells. We find streamflow predictions from analytically informed simulations to be similar in relative bias and Spearman's rho to the geologically informed simulations. R ‐squared values for groundwater depth predictions are close between the best performing analytically and geologically informed simulations at 0.68 and 0.70 respectively, with RMSE values under 10 m. We also show that the analytical approach derived by this study produces estimates of K that are similar in spatial distribution, standard deviation, mean value, and modeling performance to geologically‐informed estimates. The results of this work are used to inform a follow‐on study that tests additional data‐driven approaches in multiple basins within the contiguous United States.
Related Topics
Concepts
Streamflow
Standard deviation
Scale (ratio)
Groundwater
Hydraulic conductivity
Groundwater flow
Geology
Structural basin
Environmental science
Statistics
Hydrology (agriculture)
Soil science
Drainage basin
Mathematics
Aquifer
Geomorphology
Geotechnical engineering
Cartography
Quantum mechanics
Geography
Soil water
Physics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1111/gwat.13354
- OA Status
- green
- Cited By
- 11
- References
- 60
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386760323
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4386760323Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1111/gwat.13354Digital Object Identifier
- Title
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Continental Scale Hydrostratigraphy: Comparing Geologically Informed Data Products to Analytical SolutionsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-09-15Full publication date if available
- Authors
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Jackson Swilley, D. Tijerina, Hoang Tran, Jun Zhang, Chen Yang, Laura E. Condon, R. M. MaxwellList of authors in order
- Landing page
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https://doi.org/10.1111/gwat.13354Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
- OA URL
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https://www.osti.gov/biblio/2007089Direct OA link when available
- Concepts
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Streamflow, Standard deviation, Scale (ratio), Groundwater, Hydraulic conductivity, Groundwater flow, Geology, Structural basin, Environmental science, Statistics, Hydrology (agriculture), Soil science, Drainage basin, Mathematics, Aquifer, Geomorphology, Geotechnical engineering, Cartography, Quantum mechanics, Geography, Soil water, PhysicsTop concepts (fields/topics) attached by OpenAlex
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11Total citation count in OpenAlex
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2025: 5, 2024: 6Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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