In the Upper Colorado River Basin (UCRB), hydrology is heavily impacted by interacting processes extending from the atmosphere through the bedrock. Complex terrain and extreme spatial heterogeneity in these processes make an Integrated Process Model (IPM) an essential tool to both interpret observations and fill the observational gaps that will always exist in monitoring the hydrology of mountainous systems.

We present a IPM utilizing WRF, a weather forecasting model, and ParFlow-CLM, a surface through subsurface hydrologic model, over a domain centered over the East River Watershed (ERW), located in the UCRB. Through a series of experiments aimed at simulating water year (WY) 2019, we used four meteorological forcings datasets, three subgrid-scale physics scheme configurations, and two terrain shading options within WRF to determine the relative importance of model structural uncertainty and initial and boundary condition uncertainties on key hydrometeorological metrics, including: precipitation, snowpack, evapotranspiration, groundwater storage, and discharge. Results reveal that subgrid-scale physics configuration contributes to larger spatiotemporal variance in simulated hydrometeorological conditions, whereas variance across meteorological forcing with subgrid-scale physics configurations are more spatiotemporally constrained.

Via comparisons with situ observations and data assimilation products, these initial findings provided us with a path towards a more optimal IPM configuration. However, WY19 observations were limited. Thus, we present an additional analysis of the IPM for WY22 which has a far more comprehensive suite of observations, including radar measurements provided by the DOE’s Surface Atmosphere Integrated Field Laboratory (SAIL) campaign. These new measurements better expose where the model exhibits skill and where it has persistent errors. Our study shows how we can use the IPM to identify the parameterizations in Earth system models to advance integrated mountainous hydrology understanding in the UCRB. It also provides a roadmap for scientific deep-dives into fieldwork needed to inform parameterization development and where systemic model error may influence future hydroclimate projections in mountainous watersheds.