Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 28, issue 7
Articles | Volume 28, issue 7
https://doi.org/10.5194/hess-28-1617-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-1617-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 28, issue 7
Research article
 | Highlight paper
 | 
11 Apr 2024
Research article | Highlight paper |  | 11 Apr 2024

A network approach for multiscale catchment classification using traits

Fabio Ciulla and Charuleka Varadharajan

Data sets

Classification of River Catchments in the Contiguous United States: Code, Dataset, Similarity Patterns, and Resulting Classes Fabio Ciulla and Charuleka Varadharajan https://doi.org/10.15485/1987555

GAGES-II: Geospatial Attributes of Gages for Evaluating Streamflow J. A. Falcone https://doi.org/10.3133/70046617

Model code and software

Classification of River Catchments in the Contiguous United States: Code, Dataset, Similarity Patterns, and Resulting Classes Fabio Ciulla and Charuleka Varadharajan https://doi.org/10.15485/1987555

Video abstract

A Network Approach for Multiscale Catchment Classification using Traits Fabio Ciulla https://doi.org/10.5446/66892

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Executive editor
This paper introduces recent methods to cluster catchments that is based on traits with an application on a very important dataset (over 9000 catchments using 274 traits). The method proposed open many research perspectives in the fields of hydrology, environmental sciences and other disciplines.
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Short summary
We present a new method based on network science for unsupervised classification of large datasets and apply it to classify 9067 US catchments and 274 biophysical traits at multiple scales. We find that our trait-based approach produces catchment classes with distinct streamflow behavior and that spatial patterns emerge amongst pristine and human-impacted catchments. This method can be widely used beyond hydrology to identify patterns, reduce trait redundancy, and select representative sites.
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