The Role of Snowmelt and Subsurface Heterogeneity in Headwater Hydrology of a Mountainous Catchment in Colorado: A Model‐Data Integration Approach
Abstract 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. Plain Language Summary Mountainous headwater streams are an important source of water for ecosystems and communities downstream. In snow‐dominated mountainous watersheds with extended dry summer periods, they are fed by both melting snow and groundwater, but predicting when and how much water will flow into them is challenging. This is because mountainous watersheds have complex subsurface structures that store and release groundwater differently, as well as complex snowmelt dynamics that vary with elevation and vegetation. To better understand what controls streamflow in these headwater streams, we combined real‐world measurements, such as snow depth, streamflow, and groundwater levels, with computer models that simulate how water moves through soil and rock or flows over the land surface. Our study, conducted in one mountainous headwater catchment near Crested Butte, Colorado, USA, showed that evergreen forests slow down snowmelt and thereby delay peak streamflow. We also found that in areas where subsurface layers have low permeability, water is stored but does not easily flow into streams after snowmelt seasons. By improving our understanding of how snowmelt and groundwater contribute to streamflow, this research helps us predict water availability more accurately in mountainous headwater catchments. Key Points Slower snowmelt rates under evergreen forests delay peak streamflow and thereby the onset of baseflow in headwater streams Lower subsurface permeability in upstream areas slows groundwater release and results in a smaller recession limb of streamflow Spatial subsurface heterogeneity leads to a second groundwater peak, and the timing is controlled by subsurface and snowmelt heterogeneity
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- US Department of Energy; USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23), Climate and Environmental Sciences Division (SC-23.1 )
- Grant/Contract Number:
- AC02-05CH11231
- OSTI ID:
- 3014172
- Journal Information:
- Water Resources Research, Journal Name: Water Resources Research Journal Issue: 10 Vol. 61
- Country of Publication:
- United States
- Language:
- English
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