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Topographic Analysis of Wetlandscapes: Fractal Dimension and Scaling Properties

10 pagesPublished: September 20, 2018

Abstract

Wetlands are ubiquitous topographic depressions on landscapes and form critical
elements of the mosaic of aquatic habitats. The role of wetlands in the global hydrological and biogeochemical cycles is intimately tied to their geometric characteristics. We used DEM analysis and local search algorithms to identify wetland attributes (maximum stage, surface area and storage volume) in four wetlandscapes across the United States. We then derived the exceedance cumulative density functions (cdfs) of these attributes for the identified wetlands, applied the concept of fractal dimension to investigate the variability in wetland’ shapes. Exponentially tempered Pareto distributions were fitted to DEM derived wetland attributes. In particular, the scaling exponents appear to remain constant through the progressive water-filling of the landscapes, suggesting self-similarity of wetland geometrical attributes. This tendency is also reproduced by the fractal dimension (D) of wetland shorelines, which remains constant across different water-filling levels. In addition, the variability in D is constrained within a narrow range (1 <D < 1.33) in all the four wetlandscapes. Finally, the comparison between wetlands identified by the DEM-based model are consistent
with actual data.

Keyphrases: DEM analysis, fractal dimension, probability density function, size distribution, Wetland Identification

In: Goffredo La Loggia, Gabriele Freni, Valeria Puleo and Mauro De Marchis (editors). HIC 2018. 13th International Conference on Hydroinformatics, vol 3, pages 217--226

Links:
BibTeX entry
@inproceedings{HIC2018:Topographic_Analysis_of_Wetlandscapes,
  author    = {Leonardo Enrico Bertassello and P. Suresh Rao and Gianluca Botter and Antoine Aubeneau},
  title     = {Topographic Analysis of Wetlandscapes: Fractal Dimension and Scaling Properties},
  booktitle = {HIC 2018. 13th International Conference on Hydroinformatics},
  editor    = {Goffredo La Loggia and Gabriele Freni and Valeria Puleo and Mauro De Marchis},
  series    = {EPiC Series in Engineering},
  volume    = {3},
  pages     = {217--226},
  year      = {2018},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {https://easychair.org/publications/paper/HM2X},
  doi       = {10.29007/c7r5}}
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