Permafrost contains liquid pore water even at subzero temperatures, and the partitioning between pore ice and unfrozen water governs its mechanical and hydrological properties. Resolving this partitioning at depth and across short lateral distances remains challenging because direct subsurface observations are spatially sparse. Here, we apply active-source multichannel analysis of surface waves (MASW) using a long-term distributed acoustic sensing (DAS) cable and conventional geophone arrays at five sites along a ~2 km transect in Utqiagvik, Alaska, that captures a transition from a disturbed roadside environment to the Arctic coast. Shear-wave velocity profiles are converted to seismically inferred unfrozen pore water content (<em>S_w</em>) using a load-bearing effective-medium framework and compared against a depth-dependent reference constructed from local borehole temperatures and laboratory freezing curves measured on permafrost cores. Departures from this reference are spatially organized. The DAS-derived departure metric increases toward the coastal end of the transect, while the geophone-derived profiles show greater variability but also identify the site closest to the coast (Tundra 4) as having the largest departure. At this site, the DAS-derived profile remains higher than the temperature reference through much of the deeper section. These results suggest that temperature and shallow laboratory measurements alone do not fully explain the observed permafrost structure, particularly beneath water-rich coastal tundra surfaces characterized by ponds and lakes. The framework introduced here provides a transferable approach for integrating seismic, thermal, and laboratory data to characterize spatially variable permafrost at depth in locations where the reference estimate process would be expected to deviate most from true subsurface conditions.