Continental-scale evaluation of a fully distributed coupled land surface and groundwater model, ParFlow-CLM (v3.6.0), over Europe

Abstract. High-resolution large-scale predictions of hydrologic states and fluxes are important for many multi-scale applications, including water resource management. However, the existing global- to continental-scale hydrological models applied at coarse resolution neglect more complex processes such as lateral surface groundwater flow, thereby not capturing smaller-scale processes. Applications high-resolution physically based integrated often limited watershed scales, neglecting mesoscale climate effects on cycle. We implemented an integrated, coupled land model, ParFlow-CLM version 3.6.0, over a pan-European model domain 0.0275∘ (∼3 km) resolution. The simulates three-dimensional variably saturated groundwater-flow-solving Richards equation overland flow with two-dimensional kinematic wave approximation, which is fully exchange A comprehensive evaluation multiple variables discharge, soil moisture (SM), evapotranspiration (ET), snow equivalent (SWE), total storage (TWS), table depth (WTD) resulting from 10-year (1997–2006) simulation was performed using in situ remote sensing (RS) observations. Overall, uncalibrated showed good agreement simulating river discharge 176 gauging stations across Europe (average Spearman's rank correlation (R) 0.77). At local scale, well ET (R>0.94) against eddy covariance observations but relatively large differences SM WTD (median R values 0.7 0.50, respectively) when compared networks groundwater-monitoring-well data. performance varied between hydroclimate regions, best RS datasets being shown semi-arid arid regions most variables. Conversely, largest modeled (e.g., SM, SWE, TWS) humid cold regions. Our findings highlight importance both local-scale evaluations better understanding distributed uncertainties energy continental scales different large-scale, setup also forms basis future studies provides reference change impact projections climatology forecasting considering flows.