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Hydrologic modeling and field data for studying the role of subsurface critical zone structure on hydrological partitioning


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Type: Resource
Storage: The size of this resource is 787.3 KB
Created: Oct 17, 2023 at 9:03 p.m.
Last updated: Oct 23, 2023 at 1:16 p.m. (Metadata update)
Published date: Oct 23, 2023 at 1:16 p.m.
DOI: 10.4211/hs.d1537789fea8421aa3fe1cd2ec155b57
Citation: See how to cite this resource
Sharing Status: Published
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Abstract

This dataset contains the codes and data used in the manuscript “Influence of Subsurface Critical Zone Structure on Hydrological Partitioning in Mountainous Headwater Catchments” submitted to Geophysical Research Letters. The software requirement are summarized in requirement.txt; hydrologic modeling input data are in the folder TLnewtest2sfb2; the observation data used in the simulation are indicated as comments in the python scripts. Note that the hydrologic modeling was run in HPC (Linux system) with parallel computing.

Below are the abstract of the manuscript:
“Headwater catchments play a vital role in regional water supply and ecohydrology, and a quantitative understanding of the hydrological partitioning in these catchments is critically needed, particularly under a changing climate. Recent studies have highlighted the importance of subsurface critical zone (CZ) structure in modulating the partitioning of precipitation in mountainous catchments; however, few existing studies have explicitly taken into account the 3D subsurface CZ structure. In this study, we designed realistic synthetic catchment models based on seismic velocity-estimated 3D subsurface CZ structures. Integrated hydrologic modeling is then used to study the effect of the shape of the weathered bedrock bottom on various hydrologic fluxes and storages in mountainous headwater catchments. Numerical results show that the shape of the weathered bedrock bottom not only affects the magnitude but also the peak time of both streamflow and subsurface dynamic storage.”

Subject Keywords

Coverage

Spatial

Coordinate System/Geographic Projection:
WGS 84 EPSG:4326
Coordinate Units:
Decimal degrees
Longitude
-116.1401°
Latitude
43.7302°

Content

Credits

Funding Agencies

This resource was created using funding from the following sources:
Agency Name Award Title Award Number
National Science Foundation RAPID: Monitoring subsurface water storage dynamics associated with the 2023 extreme snowfall events in precipitation-limited systems EAR#2330004

How to Cite

Chen, H., Q. Niu, J. P. McNamara, A. N. Flores (2023). Hydrologic modeling and field data for studying the role of subsurface critical zone structure on hydrological partitioning, HydroShare, https://doi.org/10.4211/hs.d1537789fea8421aa3fe1cd2ec155b57

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/
CC-BY

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