The Role of Snowmelt and Subsurface Heterogeneity in Headwater Hydrology of a Mountainous Catchment in Colorado: A Model‐Data Integration Approach

Journal Article · Wed Oct 22 00:00:00 EDT 2025 · Water Resources Research

DOI:https://doi.org/10.1029/2025wr040651· OSTI ID:3014172

Wang, Lijing ^[1]; Xu, Zexuan ^[2]; Wang, Chen ^[3]; Thibaut, Robin ^[2]; Ulrich, Craig ^[2]; Sprenger, Matthias ^[4]; Uhlemann, Sebastian ^[5]; Wu, Yuxin ^[2]; King, Evan ^[6]; Wainwright, Haruko ^[7]; Carroll, Rosemary W. H. ^[8]; Beutler, Curtis ^[9]; Williams, Kenneth H. ^[2]; Dafflon, Baptiste ^[2]

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1. University of Connecticut, Storrs, CT (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
2. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
3. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); University of Pennsylvania, Philadelphia, PA (United States)
4. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); North Carolina State University, Raleigh, NC (United States)
5. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); University of Bremen (Germany)
6. Massachusetts Institute of Technology (MIT), Cambridge, MA (United States)
7. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Massachusetts Institute of Technology (MIT), Cambridge, MA (United States)
8. Desert Research Institute (DRI), Reno, NV (United States)
9. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Rocky Mountain Biological Laboratory, Crested Butte, CO (United States)

Mountainous headwater streams are sustained by both snowmelt‐driven streamflow and groundwater discharge in the Upper Colorado River Basin. However, predicting headwater stream discharge magnitude and peak flow timing is challenging in mountainous terrains, where snowmelt rates vary with vegetation type and elevation, and heterogeneous subsurface physical properties influence groundwater storage and its release. We used a model‐data integration approach to investigate the roles of snowmelt and subsurface structure in stream discharge and groundwater level. We ran an ensemble of 100 integrated surface‐subsurface hydrologic models for a mountainous headwater catchment near Crested Butte, Colorado, USA. We also evaluated and calibrated these models against observed data sets, including snow depth measurements using distributed temperature probes, stream discharge, and groundwater levels. Calibration with multiple data sources using neural density estimators has further constrained uncertainty in subsurface properties and snowmelt rates. Results indicated that observed slower snowmelt rates in evergreen forests delayed the peak flow and baseflow onset. In upstream areas with lower subsurface permeability, water was stored within the subsurface but was not released as interflow or shallow groundwater flow, and thereby not contributing to downstream streamflow during recession limb periods. Double peaks in groundwater occurred in areas with spatial subsurface heterogeneity, in our case due to the contrast between granodiorite and Mancos shale. These process‐based insights into groundwater and snowmelt dynamics in mountainous headwaters will help improve predictions of headwater hydrology.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: National Energy Research Scientific Computing Center (NERSC); USDOE Office of Science (SC), Basic Energy Sciences (BES). Scientific User Facilities (SUF); USDOE Office of Science (SC), Biological and Environmental Research (BER). Earth & Environmental Systems Science (EESS)
• Grant/Contract Number: AC02-05CH11231
• OSTI ID: 3014172
• Journal Information: Water Resources Research, Journal Name: Water Resources Research Journal Issue: 10 Vol. 61; ISSN 1944-7973; ISSN 0043-1397
• Publisher: American Geophysical Union (AGU)
• Country of Publication: United States
• Language: English