Tidal networks 1. Automatic network extraction and preliminary scaling features from digital terrain maps


Journal Article

We propose a method of automatic extraction of the tidal channel network from topographic data of marsh and tidal flat lands that uses a combination of a threshold elevation and threshold curvature. Not only the location but also the area of the channel bed is identified. This method differs substantially from that used to identify terrestrial channel networks, and it successfully predicts all of the main channels and nearly all of the smaller tributaries of the channel networks derived from SPOT imagery of the northern Venice Lagoon. Channel network maps of Venice and other sites (Petaluma Marsh in the San Francisco Bay and Barnstable Marsh in Massachusetts) were examined for scaling properties. Because of the large width of the channels relative to a characteristic length of their drainage area, we had to develop procedures for automatically delineating channel width and then for identifying the skeleton of the channel network (the pattern connecting the loci of the channel centerlines) for box-counting analysis. Box-counting dimensions of the network skeleton proved site-dependent and showed finite-size effects. Because of the large widths we also performed a scaling analysis based on the proportions of the total channel bed area occupied by the tidal networks (i.e., a 'fat' fractal analysis). This analysis showed a strong break in scaling between large and small channels. These analyses suggest that tidal channels differ significantly in their scaling relationships from terrestrial systems. In subsequent papers [Rinaldo et al., this issue (a), (b)] we pursue this point much further.

Full Text

Duke Authors

Cited Authors

  • Fagherazzi, S; Bortoluzzi, A; Dietrich, WE; Adami, A; Lanzoni, S; Marani, M; Rinaldo, A

Published Date

  • December 1, 1999

Published In

Volume / Issue

  • 35 / 12

Start / End Page

  • 3891 - 3904

International Standard Serial Number (ISSN)

  • 0043-1397

Digital Object Identifier (DOI)

  • 10.1029/1999WR900236

Citation Source

  • Scopus