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| Type: | Resource | |
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| Created: | Feb 11, 2022 at 10:35 p.m. | |
| Last updated: | Feb 14, 2022 at 3:21 p.m. (Metadata update) | |
| Published date: | Feb 14, 2022 at 3:21 p.m. | |
| DOI: | 10.4211/hs.4871ac7e869d40d8ad05cf02ae545cd5 | |
| Citation: | See how to cite this resource |
| Sharing Status: | Published |
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| Views: | 1151 |
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Abstract
Water age and flow pathways should be related; however, it is still generally unclear how integrated catchment runoff generation mechanisms result in streamflow age distributions at the outlet. Lapides et al. (2021) combined field observations of runoff generation at the Dry Creek catchment with StorAge Selection (SAS) age models to explore the relationship between streamwater age and runoff pathways. Dry Creek is an intensively monitored catchment in the northern California Coast Ranges with a Mediterranean climate and thin subsurface critical zone. Due to limited storage capacity, runoff response is rapid (~1-2 hours), and total annual streamflow consists predominantly of saturation overland flow, based on field mapping of saturated extents and runoff thresholds. Even though SAS modeling reveals that streamflow is younger at higher wetness states, flow is still typically older than one day. Because streamflow is mostly overland flow, this means that a significant portion of overland flow must not be event-rain but instead derive from older groundwater returning to the surface, consistent with field observations of exfiltrating head gradients, return flow through macropores, and extensive saturation days after storm events. We conclude that even in a landscape with widespread overland flow, runoff pathways may be longer than anticipated, with implications for contaminant delivery and biogeochemical reactions. Our findings have implications for the assumptions built into classic hydrograph separation inferences, namely, whether overland flow consists of new water.
For this work, we translated SAS modeling code in Matlab from Benettin and Bertuzzo (2018) to Python and provide here a set of code for SAS modeling in Python and example data for Dry Creek, CA produced for the SAS modeling publication by Lapides et al. (2021).
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Related Resources
| This resource updates and replaces a previous version | Lapides, D. A. (2021). Calculating streamwater age using StorAge Selection functions at Dry Creek, CA, HydroShare, https://doi.org/10.4211/hs.13244d68f3e74452a8bbcb5d8860768c |
| This resource has been replaced by a newer version | Lapides, D. A., W. J. Hahm, D. M. Rempe, W. E. Dietrich, D. Dralle (2022). Calculating streamwater age using StorAge Selection functions at Dry Creek, CA, HydroShare, https://doi.org/10.4211/hs.f2c9289de92a41f5b5ca0590bfbe4ad1 |
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| Name | Organization | Address | Phone | Author Identifiers |
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| W. Jesse Hahm | UC Berkeley | |||
| David Dralle | US Forest Service | CA, US | ||
| Daniella Marie Rempe | University of Texas at Austin | |||
| William Dietrich | University of California, Berkeley |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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