Articles | Volume 26, issue 15
https://doi.org/10.5194/hess-26-3989-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-3989-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
04 Aug 2022
Research article | Highlight paper |
| 04 Aug 2022
| 04 Aug 2022
Bedrock depth influences spatial patterns of summer baseflow, temperature and flow disconnection for mountainous headwater streams
US Geological Survey, Observing Systems Division, Hydrologic Remote Sensing Branch, 11 Sherman Place, Unit 5015, Storrs CT 06269, USA
Phillip Goodling
US Geological Survey, Maryland-Delaware-District of Colombia Water
Science Center, 5522 Research Park Drive, Catonsville MD 21228, USA
Zachary C. Johnson
US Geological Survey, Washington Water Science Center, 934 Broadway, Suite 300, Tacoma WA 98402, USA
Karli M. Rogers
US Geological Survey, Eastern Ecological Science Center, 11649 Leetown Road, Kearneysville WV 25430, USA
Nathaniel P. Hitt
US Geological Survey, Eastern Ecological Science Center, 11649 Leetown Road, Kearneysville WV 25430, USA
Jennifer B. Fair
US Geological Survey, Eastern Ecological Science Center, 11649 Leetown Road, Kearneysville WV 25430, USA
US Geological Survey, New England Water Science Center, 10 Bearfoot
Road, Northborough MA 01532, USA
Craig D. Snyder
US Geological Survey, Eastern Ecological Science Center, 11649 Leetown Road, Kearneysville WV 25430, USA
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Cited
14 citations as recorded by crossref.
- Effects of episodic stream dewatering on brook trout spatial population structure N. Hitt et al. 10.1111/fwb.14287
- Taking heat (downstream): Simulating groundwater and thermal equilibrium controls on annual paired air–water temperature signal transport in headwater streams Z. Johnson et al. 10.1016/j.jhydrol.2024.131391
- Train, Inform, Borrow, or Combine? Approaches to Process‐Guided Deep Learning for Groundwater‐Influenced Stream Temperature Prediction J. Barclay et al. 10.1029/2023WR035327
- Diel temperature signals track seasonal shifts in localized groundwater contributions to headwater streamflow generation at network scale D. Rey et al. 10.1016/j.jhydrol.2024.131528
- How quickly do brook trout lose long-term thermal acclimation? M. O'Donnell et al. 10.1016/j.jtherbio.2025.104103
- Empirical stream thermal sensitivity cluster on the landscape according to geology and climate L. McGill et al. 10.5194/hess-28-1351-2024
- Utility of an Instantaneous Salt Dilution Method for Measuring Streamflow in Headwater Streams K. Rogers et al. 10.1111/gwat.13437
- Exploring landscape and geologic controls on spatial patterning of streambank groundwater discharge in a mixed land use watershed K. Jackson et al. 10.1002/hyp.15112
- Annual, seasonal, and monthly baseflow trend in an arid area in Loss Plateau, China Y. Sun et al. 10.2166/ws.2023.322
- Groundwater-Surface water interactions research: Past trends and future directions D. Irvine et al. 10.1016/j.jhydrol.2024.132061
- Declines in Brook Trout Abundance Linked to Atmospheric Warming in Maryland, USA N. Hitt et al. 10.3390/hydrobiology3040019
- A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed M. Behbahani et al. 10.1016/j.jhydrol.2025.134139
- Evaluation of daily stream temperature predictions (1979–2021) across the contiguous United States using a spatiotemporal aware machine learning algorithm J. Diaz et al. 10.1016/j.envsoft.2025.106655
- Assessing the informativeness of a coupled surface–subsurface watershed model for understanding debris flow: a hydrological perspective H. Wang et al. 10.1080/02626667.2024.2362303
14 citations as recorded by crossref.
- Effects of episodic stream dewatering on brook trout spatial population structure N. Hitt et al. 10.1111/fwb.14287
- Taking heat (downstream): Simulating groundwater and thermal equilibrium controls on annual paired air–water temperature signal transport in headwater streams Z. Johnson et al. 10.1016/j.jhydrol.2024.131391
- Train, Inform, Borrow, or Combine? Approaches to Process‐Guided Deep Learning for Groundwater‐Influenced Stream Temperature Prediction J. Barclay et al. 10.1029/2023WR035327
- Diel temperature signals track seasonal shifts in localized groundwater contributions to headwater streamflow generation at network scale D. Rey et al. 10.1016/j.jhydrol.2024.131528
- How quickly do brook trout lose long-term thermal acclimation? M. O'Donnell et al. 10.1016/j.jtherbio.2025.104103
- Empirical stream thermal sensitivity cluster on the landscape according to geology and climate L. McGill et al. 10.5194/hess-28-1351-2024
- Utility of an Instantaneous Salt Dilution Method for Measuring Streamflow in Headwater Streams K. Rogers et al. 10.1111/gwat.13437
- Exploring landscape and geologic controls on spatial patterning of streambank groundwater discharge in a mixed land use watershed K. Jackson et al. 10.1002/hyp.15112
- Annual, seasonal, and monthly baseflow trend in an arid area in Loss Plateau, China Y. Sun et al. 10.2166/ws.2023.322
- Groundwater-Surface water interactions research: Past trends and future directions D. Irvine et al. 10.1016/j.jhydrol.2024.132061
- Declines in Brook Trout Abundance Linked to Atmospheric Warming in Maryland, USA N. Hitt et al. 10.3390/hydrobiology3040019
- A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed M. Behbahani et al. 10.1016/j.jhydrol.2025.134139
- Evaluation of daily stream temperature predictions (1979–2021) across the contiguous United States using a spatiotemporal aware machine learning algorithm J. Diaz et al. 10.1016/j.envsoft.2025.106655
- Assessing the informativeness of a coupled surface–subsurface watershed model for understanding debris flow: a hydrological perspective H. Wang et al. 10.1080/02626667.2024.2362303
Latest update: 09 Sep 2025
Executive editor
As also stated by both reviewers, this work is important and timely. It combines data from several sources to highlight the role of fine-scale hydrogeological features on hydrological processes. As nicely stated by reviewer 2: “The work addresses important questions regarding the description of connectivity and interaction between groundwater and surface water in mountainous catchments. The authors develop in their paper an interesting vision at the interfaces between geomorphology, hydrology and hydroecology (principally fish habitats)
As also stated by both reviewers, this work is important and timely. It combines data from...
Short summary
The geologic structure of mountain watersheds may control how groundwater and streamwater exchange, influencing where streams dry. We measured bedrock depth at 191 locations along eight headwater streams paired with stream temperature records, baseflow separation and observations of channel dewatering. The data indicated a prevalence of shallow bedrock generally less than 3 m depth, and local variation in that depth can drive stream dewatering but also influence stream baseflow supply.
The geologic structure of mountain watersheds may control how groundwater and streamwater...
