Accurate partitioning of precipitation into infiltration and runoff is a fundamental objective of land surface models tasked with characterizing the surface water and energy balance. Temporal variability in this partitioning is due, in part, to changes in pre-storm soil moisture, which determine soil infiltration capacity and unsaturated storage. Utilizing the NASA Soil Moisture Active Passive Level-4 soil moisture product in combination with streamflow and precipitation observations, we demonstrate that land surface models (LSMs) generally underestimate the strength of the positive rank correlation between pre-storm soil moisture and event runoff coefficients (i.e., the fraction of rainfall accumulation depth converted into stormflow runoff during a storm event). Underestimation is largest for LSMs employing an infiltration-excess approach for stormflow runoff generation. More accurate coupling strength is found in LSMs that explicitly represent sub-surface stormflow or saturation-excess runoff generation processes.