Evaluating long‐term One‐Way Atmosphere‐Hydrology simulations and the impacts of Two‐Way coupling in four mountain watersheds

Abstract

Joint hydrologic‐atmospheric model frameworks offer novel insights into the terrestrial hydrologic cycle and the potential for improved predictive capabilities for stream discharge and other hydrologic fluxes. In this study, we examine both one‐ and two‐way coupled integrations of the Weather Research and Forecasting (WRF v3.8.1) atmospheric and WRF‐Hydro (v5.0) hydrologic models for four 1000–2000 km2 snow‐dominated mountain watersheds (1500–2100 m mean elevation) in Idaho's Rocky Mountains. In watersheds where anthropogenic withdrawals are minimal (3 of 4 watersheds), we simulate stream discharge with high confidence (KGE > 0.63) for a 20 year period in the uncoupled scenarios, and find that WRF winter precipitation accumulations have less than 15% average error for all but two of the fourteen comparison NRCS Snotel sites. However, annual streamflow biases are highly correlated (r2 > 0.8 in some cases) with the annual errors in WRF cold‐season precipitation, suggesting that process representation of winter orographic precipitation limits hydrologic predictability. In the second part of the study, we evaluate the potential for ‘two‐way’ model coupling to influence hydrologic predictability by examining a 2 month case‐study period with active spring season convective precipitation. We quantify the impacts of resolving hillslope‐scale soil water redistribution on the ABL, and find that while resolving overland and saturated subsurface soil moisture flow influences soil moisture distributions and surface energy fluxes, the impact on precipitation is non‐systematic, as precipitation is generally atmospherically controlled during the study period. Consequently, future efforts should focus on improving winter orographic process representation, as streamflow is highly sensitive to errors in these processes.

Preface – special issue on “coupled atmosphere‐hydrological processes: Novel system developments and cross‐compartment evaluations”

“…Rudisill et al (2022) performed a fully coupled simulation of the hydrologically enhanced Weather Research and Forecasting (WRF‐Hydro) model, which accounts for the lateral terrestrial water flow not represented in the original WRF land‐surface model. They examined four Rocky Mountains snow‐dominated catchments with a two‐month case study in spring characterized by convective events, adopting the CTPHILow framework (Findell & Eltahir, 2003) to evaluate land‐atmosphere coupling.…”

“…Authors focusing on soil moisture‐precipitation feedback at the catchment scale did not find generally significant enhancements. For their snow‐dominated study region, Rudisill et al (2022) concluded that a fully coupled framework, though impacting heat fluxes and temperatures, likely has a small added value for discharge prediction and water budgets at annual timescales, given that precipitation is atmospherically controlled. Similar results were found by Furnari et al (2022) in their Mediterranean study region, with only a slight impact on hydrological model enhancement, especially when shoreward moisture transport from the sea is the dominant process.…”

“…Despite being a crucial topic in a warming climate, enhanced modelling of snow‐related processes is not explored deeply in the special issue. While some other contributions considered study areas with significant snow events (e.g., Rummler et al, 2022), only Rudisill et al (2022) explicitly highlighted the snow‐dominated nature of their analysed catchments. The authors emphasized the uncertainty of forcing input in these situations.…”

“…, onlyRudisill et al (2022) explicitly highlighted the snow-dominated nature of their analysed catchments. The authors emphasized the uncertainty of forcing input in these situations.…”

Ramifications of groundwater model in WRF/Noah‐MP coupled system: Effects on soil‐moisture and regional climate simulation

“…They highlighted that land‐atmosphere coupling is sensitive to changes in subsurface moisture. Rudisill et al (2022) demonstrated that saturated subsurface moisture influences soil moisture distributions along with surface energy fluxes. Their study used two‐way coupled WRF‐Hydro model setup.…”