Climate change and nitrogen (N) pollution are altering biogeochemical and ecohydrological processes in dryland watersheds, increasing N export, and threatening water quality. While simulation models are useful for projecting how N export will change in the future, most models ignore biogeochemical “hotspots” that develop in drylands as moist microsites become hydrologically disconnected from plant roots when soils dry out. These hotspots enable N to accumulate over dry periods and rapidly flush to streams when soils wet up. To better project future N export, we developed a framework for representing hotspots using the ecohydrological model RHESSys. We then conducted a series of virtual experiments to understand how uncertainties in model structure and parameters influence N export. Modeled export was sensitive to the abundance of hotspots in a watershed, increasing linearly and then reaching an asymptote with increasing hotspot abundance. Peak streamflow N was also sensitive to a soil moisture threshold at which subsurface flow from hotspots reestablished, allowing N to be transferred to streams; it increased and then decreased with an increasing threshold value. Finally, N export was generally higher when water diffused out of hotspots slowly. In a case study, we found that when hotspots were modeled explicitly, peak streamflow nitrate export increased by 29%, enabling us to better capture the timing and magnitude of N losses observed in the field. This modeling framework can improve projections of N export in watersheds where hotspots play an increasingly important role in water quality.