Extreme Water Levels (EWL) are exerting increasing pressure on the more than 1,800 coastal and estuarine military installations maintained by the Department of Defense (DoD). As sea levels rise, these installations become increasingly vulnerable, in a way that depends not only on global patterns of change but also regional variability in mean sea level (MSL), vertical land motion (VLM), tides, storm surge, and local hydrodynamic responses. Typically, EWL and tidal datums are derived by statistical analysis of observational records, ideally from the vicinity of the investigation site. However, most DoD sites are not equipped with tide gauges. Thus, current EWL and their vertical datums are based on interpolations from sparse datasets often recorded hundreds of miles away and not necessarily representative of the local conditions. To improve the Defense Regional Sea Level (DRSL) database of tidal datums and EWL, this research will develop a holistic approach that hindcasts sea levels and tidal datums at any location worldwide using remote sensing and in situ measurements coupled with information on contributing processes and their forcing and interaction. By hindcasting sea level via physical and empirical relationships, the project team will significantly enhance the existing DRSL database temporally and spatially, reducing uncertainties in EWL estimates and their vertical datums to levels commensurate with DRSL applications.
This project will enhance the existing DRSL database of sea level and tidal datums with a combination of a more extensive (newly digitized) set of tide gauge records and a novel modeling framework that simulates sea level in the absence of observations based on the three individual components; MSL, storm tides (that is: tides + surges), and VLM. The modeling framework leverages a combination of global (numerical and data-driven) models of MSL and storm surge with localized estimates of tidal variability and VLM based on satellite and in situ measurements and hydrodynamic modeling. The approach accounts explicitly for small-scale variability in under-sampled regions by evaluating the effects of geometry, river flow, wind, and local VLM (e.g., subsidence induced by groundwater pumping or compaction), which will ultimately lead to an improved representation of the spatial and temporal variability in tidal datums and EWL.
This project will provide a comprehensive data- and physics-driven sea level hindcast of 60+ years with authoritative geodetic datums. These data products will allow DoD managers and planners to undertake screening-level exposure assessments and make decisions based on EWL with substantially reduced uncertainties, even at ungauged sites. The increased record length from leveraging historical observations and model hindcasts will also allow to derive EWL associated with longer return periods, such as assessments at sites with critical infrastructure. Local-scale variations in EWL and VLM will enable identifying and prioritizing critical needs. While the approach is designed specifically to support exposure and vulnerability assessments at DoD-managed sites, the approach is applicable at any location and will generate a database supporting a wide range of global climate-resilience efforts.