Core Ideas• Upscaling methods compared in situ measures with soil moisture from the SMAP satellite. • The accuracy of SMAP soil moisture products in annual cropland was assessed. • The spatial representativeness of sparse in situ networks was determined.

This paper presents an assessment of the applicability of using RADARSAT-2-derived soil moisture data in the Hydrologic Modelling System developed by the Hydrologic Engineering Center (HEC-HMS) for flood forecasting with a case study in the Sturgeon Creek watershed in Manitoba, Canada. Spring flooding in Manitoba is generally influenced by both winter precipitation and soil moisture conditions in the fall of the previous year. As a result, the soil moisture accounting (SMA) and the temperature index algorithms are employed in the simulation. Results from event and continuous simulations of HEC-HMS show that the model is suitable for flood forecasting in Manitoba. Soil moisture data from the Manitoba Agriculture field survey and RADARSAT-2 satellite were used to set the initial soil moisture for the event simulations. The results confirm the benefit of using satellite data in capturing peak flows in a snowmelt event. A sensitivity analysis of SMA parameters, such as soil storage, maximum infiltration, soil percolation, maximum canopy storage and tension storage, was performed and ranked to determine which parameters have a significant impact on the performance of the model. The results show that the soil moisture storage was the most sensitive parameter. The sensitivity analysis of initial soil moisture in a snowmelt event shows that cumulative flow and peak flow are highly influenced by the initial soil moisture setting of the model. Therefore, there is a potential to utilize RADARSAT-2-derived soil moisture for hydrological modelling in other snow-dominated Manitoba watersheds.