NGDC Tsunami Inundation Gridding Project

Data Sources

The DEMs are developed using the best available digital data. Shoreline, bathymetric, topographic, and shoreline-crossing data (e.g., Figure 1) are obtained from numerous federal and state government agencies, academic institutions, and private companies (e.g., Table 2).

Data sets must be assessed for quality and accuracy both within each data set, and between data sets to ensure consistency and gradual topographic transitioning along the edges of data sets. Data sets are converted into ESRI ArcGIS shape files for viewing and evaluating with ArcMap. The data are collected by numerous methods, in different terrestrial environments, and at various scales and resolutions. For some important bathymetric and topographic features there are no digital data, necessitating hand digitizing of these features for inclusion in the tsunami inundation grids (see Problems Encountered, below).

Processing Procedures

Figure 2 illustrates the sequence of procedures used in developing the tsunami inundation grids. After initial evaluation of the digital datasets obtained by NGDC, it is necessary to shift the data to common horizontal and vertical datums.

These shifts are accomplished using the software package FME. The relationships between vertical datums (e.g., Mean High Water, Mean Lower Low Water, Mean Sea Level) in some gridding regions have been established and incorporated into the VDatum software tool developed jointly by NOAA's Office of Coast Survey and National Geodetic Survey. VDatum can be utilized to transform the data into Mean High Water (MHW), the vertical datum chosen for tsunami inundation modeling. In other areas, PMEL provides gridded surfaces that represent differences in vertical datums or relationships established from prior investigations. In the remaining areas it is necessary for NGDC to calculate vertical datum relationships from local tide station values.

Some datasets have data point spacings much greater than that required for the 1/3 to 1 arc-second (~10 to 30 meter) tsunami inundation grids. For example, shoreline-crossing beach profiles typically have point spacings on the order of one meter, however, the profiles may be spaced hundreds of meters apart. These datasets need to separately "surfaced" with Generic Mapping Tools (GMT) software to infill regions between the well-defined beach profiles with consistent elevation data values. The resulting "pre-grids" are closely cropped to the spatial extent of the data coverage area to prevent extrapolation into areas covered by other datasets. Many National Ocean Service (NOS) inland water-body surveys also have data point spacings significantly greater than that required for the grids; data points from these surveys are gridded with ESRI ArcCatalog to a distance of 5 grid cells so that the river channels and harbors are well defined. Deep-water NOS surveys typically have data points up to a kilometer or more apart. These surveys are also pre-gridded using ArcCatalog to interpolate between soundings.

Mismatches between datasets are most common with the NOS hydrographic surveys, many of which date from the early to mid 20th century. This is especially true where geomorphologic and anthropogenic change has modified inland water-bodies. For example, modern dredging of the Atlantic Intracoastal Waterway by the U.S. Army Corps of Engineers has significantly deepened that channel. Similarly, many river channels have migrated such that the recent topographic LiDAR data mismatches the older NOS surveys (e.g., Figure 3).

Satellite imagery viewable with Google Earth is used to help assess the current morphology of suspect features before a determination is made as to which dataset to edit.

Figure 4 illustrates the problem of features without representation in any available digital dataset. One significant tsunami-affecting feature in the Myrtle Beach region is a recently built jetty at the entrance of Murrells Inlet. This feature is not represented in NOS hydrographic surveys of the inlet or in USGS National Elevation Dataset (NED) topography but is visible in satellite imagery. NGDC chose to digitize this feature as two, 1-meter elevation lines, and excise NOS soundings in their immediate vicinity. Google Earth satellite imagery and current NOS navigation charts were used to accurately locate the jetty.

Other problems include anomalous data values within datasets. These may result from problems during data collection or initial processing and generally cannot be rectified by NGDC; these data points are usually excised prior to gridding.

A "slope" map is also generated (e.g., Figure 6), which highlights changes in slope that should reflect natural morphology rather than artificial features at the edges of datasets.

Close inspection of the DEMs reveals artificial features that necessitate reevaluation of the data and regridding. For direct comparison of elevation values, bench marks and points, typically local highs with specified elevations are extracted from USGS topographic charts and compared to DEM cell values in corresponding locations. More exact evaluations utilize tide stations within the gridding region (e.g., Table 4), consisting of known elevations above MHW that can be directly compared with the corresponding elevations extracted from the DEMs. In this instance, the benchmark elevations are not used in the gridding process.