This paper compares and contrasts UAS-based Structure from Motion (SfM) and TLS survey methods as applied to evaluate the impacts of, and recovery from, the extreme El Niño 2015-16 on the seasonal geomorphic and sediment budget responses of an embayed, high-energy beach-dune system on the central coast of British Columbia, Canada. TLS and UAS mapping campaigns over a two-year period provided seasonal bare-earth digital terrain models (DTMs) and orthophoto mosaics. Spatial-temporal change detection methods were used to quantify volumes of significant erosion and deposition within the beach-dune system. The frequency and magnitude of erosive events and aeolian activity were also estimated from oblique, time-lapse photography. During the 2015-16 El Niño season, elevated water levels and storm waves eroded the foredune and lowered the beach surface by ~ 1m. Erosion was greatest in the middle of the beach with dune scarping of over 2m where wave energy was focused. Minor accretion occurred during the summer of 2016 on the upper beach, and ramp rebuilding was observed mostly from slumping and avalanching of existing dune sands. The following winter 2017 storm season led to minor erosion on the beach and extensive incipient dune development and sand ramp recovery fronting the foredune to an extent close to pre-El Niño elevations. Comparison of change surfaces between methods revealed limitations in the SfM method, namely due to vegetation effects on DTM generation, which limit its ability to detect change in the coastal environment. The costs, time, logistics, and accuracy for both SfM and TLS survey methodologies for coastal geomorphic change detection analysis is also evaluated. Combined, the UAS and SfM workflow provides a competitive solution to more expensive and time-consuming survey methods, such as TLS and aerial LiDAR, but its utility and accuracy is highly dependent on research objectives and post-processing techniques.