Abstract. Mountain hydrology is controlled by interacting processes extending from the
atmosphere through the bedrock. Integrated process models (IPMs), one of the
main tools needed to interpret observations and refine conceptual models of
the mountainous water cycle, require meteorological forcing that simulates
the atmospheric process to predict hydroclimate then subsequently impacts
surface–subsurface hydrology. Complex terrain and extreme spatial
heterogeneity in mountainous environments drive uncertainty in several key
considerations in IPM configurations and require further quantification and
sensitivity analyses. Here, we present an IPM using the Weather Research and
Forecasting (WRF) model which forces an integrated hydrologic model,
ParFlow-CLM, implemented over a domain centered over the East River
watershed (ERW), located in the Upper Colorado River basin (UCRB). The ERW
is a heavily instrumented 300 km2 region in the headwaters of the UCRB
near Crested Butte, CO, with a growing atmosphere-through-bedrock
observation network. Through a series of experiments in the water year 2019
(WY19), we use four meteorological forcings derived from commonly used
reanalysis datasets, three subgrid-scale physics scheme configurations in
WRF, and two terrain shading options within WRF to test the relative
importance of these experimental design choices for key hydrometeorological
metrics including precipitation and snowpack, as well as evapotranspiration,
groundwater storage, and discharge simulated by the ParFlow-CLM. Our
hypothesis is that uncertainty from synoptic-scale forcings produces a much
larger spread in surface–subsurface hydrologic fields than
subgrid-scale physics scheme choice. Results reveal that the WRF subgrid-scale
physics configuration leads to larger spatiotemporal variance in simulated
hydrometeorological conditions, whereas variance across meteorological
forcing with common subgrid-scale physics configurations is more
spatiotemporally constrained. Despite reasonably simulating precipitation, a
delay in simulated discharge peak is due to a systematic cold bias across
WRF simulations, suggesting the need for bias correction. Discharge shows
greater variance in response to the WRF simulations across subgrid-scale
physics schemes (26 %) rather than meteorological forcing (6 %).
The topographic radiation option has minor effects on the watershed-average
hydrometeorological processes but adds profound spatial heterogeneity to
local energy budgets (±30 W m−2 in shortwave radiation and 1 K air
temperature differences in late summer). This is the first presentation of
sensitivity analyses that provide support to help guide the scientific
community to develop observational constraints on atmosphere-through-bedrock
processes and their interactions.