Global Overview of Continental Shelf Geomorphology Based on the SRTM30_PLUS 30-Arc Second Database

We report the results of a multivariate analysis of geomorphic features occurring on the global continental shelf that were mapped based on the Shuttle Radar Topography Mapping (SRTM30_PLUS) 30-arc sec database. The analysis was based on 11 input variables as follows: (1) the mean continental shelf depth; (2) mean shelf break depth; (3) mean shelf width; (4) percent area of low relief shelf; (5) percent area of medium relief shelf; (6) percent area of high relief shelf; (7) percent area of glacial troughs; (8) percent area of shelf valleys; (9) percent area of basins perched on the shelf; (10) the percent of submarine canyons that are shelf-incising; and (11) the percent area of coral reef. For the analysis the global shelf was divided into 551 reporting blocks, each approximately 500 km in along-shelf length. Eight shelf morphotypes were defined by multivariate analysis of the 11 input variables, and they can be grouped into four broad categories: narrow-shallow shelves; wide-flat shelves; intermediate shelves; and deep-glaciated shelves. There is a negative correlation between shelf width and active plate margins, although there are examples of most shelf morphotypes occurring on both active and passive margins. Glaciation plays a major role in determining shelf geomorphology and characterizes around 21 % of the global shelf. In particular, we find a very strong correlation between mean shelf depth and the percentage area of glacial troughs, indicative of the role played by glaciation and glacial erosion in shaping the global shelf. Coral reef growth is an important factor for one morphotype, which covers 427,000 km2 or about 1.3 % of all continental shelves. The hypsometric curve for mean shelf depth exhibits a peak at a depth of 40 m that coincides with a persistent position of sea level during the last 500,000 years based on one published sea level curve. The geomorphic characterization and classification of the continental shelf at a global scale could be advanced using predictive modeling tools (for tidal sand banks, for example) but is otherwise dependent upon improved resolution bathymetric data becoming available.