Canada has the world�s longest coastline that is increasingly battered by large storms and hurricanes that cause extensive erosion, seawater flooding, and aquifer salinization. Existing techniques to monitor coastal flooding and terrestrial impacts are prohibitively expensive, have limited spatiotemporal resolution, and are restricted to disciplinary silos. In this study, we use heat as an inexpensive tracer of seawater infiltration and morphologic change on two low-elevation, sand islands in Nova Scotia and Prince Edward Island. High-energy, dynamic beaches are instrumented with transects of high-precision sediment temperature rods (AlphaMach, TrodX). Ancillary data to assess morphologic change and coastal flooding, salinization, and flushing were collected along these transects using drone-based LiDAR and co-located piezometers instrumented with conductivity, temperature, and depth (CTD) loggers. Multi-depth temperature data were processed with, VFLUX2, a MATLAB time-series analysis code to create quantitative time series of morphologic change and vertical infiltration fluxes. In September 2022, Hurricane Fiona impacted Atlantic Canada and caused pronounced SWI and morphologic change. Our novel dataset captured this event and revealed thermal disturbances that were interpreted to quantify morphologic change and seawater intrusion. Seawater flooding resulted in cold pulses that precisely indicate the timing and rate of vertical saltwater intrusion observed in CTD loggers. Erosion and accretion changed the thickness of overlying sediments and caused sharp changes in diel temperature signals propagation. We demonstrate that thermal time series can quantitatively track coastal change and provide a cost-effective opportunity to increase the spatiotemporal resolution of coastal monitoring in the age of pronounced environmental change.