Abstract
Physics-based distributed hydrological models that include groundwater are widely used to understand and predict physical and biogeochemical processes within watersheds. Typically, due to computational limitations, watershed modelers minimize the number of elements used in domain discretization, smoothing or even ignoring critical topographic features. We use an idealized model to investigate the implications of mesh refinement along streams and ridges for modeling three-dimensional groundwater flow and transport in mountainous watersheds. For varying degrees of topographic complexity level (TCL), which increases with the level of mesh refinement, and geological heterogeneity, we estimate and compare steady state baseflow discharge, mean age, and concentration of subsurface weathering products. Results show that ignoring lower-order streams or ridges diminishes flow through local flow paths and biases higher the contribution of intermediate and regional flow paths, and biases baseflow older. The magnitude of the bias increases for systems where permeability rapidly decreases with depth and is dominated by shallow flow paths. Based on a simple geochemical model, the concentration of weathering products is less sensitive to the TCL, partially due to the thermodynamic constraints on chemical reactions. Our idealized model also reproduces the observed emergent scaling relationship between the groundwater contribution to streamflow and drainage area, and finds that this scaling relationship is not sensitive to mesh TCL. The bias effects have important implications for the use of hydrological models in the interpretation of environmental tracer data and the prediction of biogeochemical evolution of stream water in mountainous watersheds.
Original language | English |
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Pages (from-to) | 10,313-10,338 |
Journal | Water Resources Research |
Volume | 54 |
Issue number | 12 |
DOIs | |
State | Published - Dec 2018 |
Externally published | Yes |
Funding
This work was supported through funding from the New Mexico Water Resources Research Institute Faculty Water Research Grant, the National Science Foundation (EAR-1015100, EAR-1830172, and CNH-1010516), and the New Mexico EPSCoR Track I (EAR-0814449) awarded to New Mexico Tech. Wang and Gomez-Velez are also funded by the U.S. Department of Energy (DOE), Office of Biological and Environmental Research (BER), as part of BER's Subsurface Biogeochemistry Research Program (SBR). This contribution originates from the SBR Scientific Focus Area (SFA) at the Pacific Northwest National Laboratory (PNNL). We thank ARANZ Geo Limited for kindly providing the Leapfrog academic licenses used to generate the modeling meshes. Mention of trade names or commercial products does not constitute endorsement or recommendation for use. The work is theoretical in nature. It does not use observational data, and the digital elevation model for the Rio Hondo watershed is publicly available from the USGS data portal. This work was supported through funding from the New Mexico Water Resources Research Institute Faculty Water Research Grant, the National Science Foundation (EAR-1015100, EAR-1830172, and CNH-1010516), and the New Mexico EPSCoR Track I (EAR-0814449) awarded to New Mexico Tech. Wang and Gomez-Velez are also funded by the U.S. Department of Energy (DOE), Office of Biological and Environmental Research (BER), as part of BER’s Subsurface Biogeochemistry Research Program (SBR). This contribution originates from the SBR Scientific Focus Area (SFA) at the Pacific Northwest National Laboratory (PNNL). We thank ARANZ Geo Limited for kindly providing the Leapfrog academic licenses used to generate the modeling meshes. Mention of trade names or commercial products does not constitute endorsement or recommendation for use. The work is theoretical in nature. It does not use observational data, and the digital elevation model for the Rio Hondo watershed is publicly available from the USGS data portal.
Funders | Funder number |
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ARANZ Geo Limited | |
Office of Biological and Environmental Research | |
SBR Scientific Focus Area | |
National Science Foundation | EAR-1830172, EAR-0814449, EAR-1015100, 1830172, CNH-1010516 |
U.S. Department of Energy | |
Biological and Environmental Research | |
Stephen F. Austin State University | |
Pacific Northwest National Laboratory | |
New Mexico Water Resources Research Institute, New Mexico State University |