Classification of River Catchments in the Contiguous United States: Code, Dataset, Similarity Patterns, and Resulting Classes

Ciulla, Fabio; Varadharajan, Charuleka

doi:10.15485/1987555

Title: Classification of River Catchments in the Contiguous United States: Code, Dataset, Similarity Patterns, and Resulting Classes

Dataset
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Abstract

This dataset serves as supplementary information for the paper by Ciulla F. and Varadharajan C. A Network Approach for Multiscale Catchment Classification using Traits (see reference 1). It contains environmental and physical catchment traits, such as temperatures, precipitation, land use and human interference, from 9067 sites across the contiguous United States (CONUS). The purpose of this dataset is to provide information for a better trait-based categorization of river catchments in the CONUS using networks as an analytical tool. The traits variables match the ones present in the GAGES-II dataset and the preprocessing steps are described in the Methods section (processed_dataset.csv). Additionally we include the topologies (nodes, edges and clusters, also referred as classes) of the catchment network and traits network generated by said dataset (csv and json files). A series of tables support the information carried by the network providing more detailed descriptions of cluster components (SI1.pdf). A summary of all the plots of clusters of catchments with at least 50 nodes is provided (SI2.pdf). The characteristic traits for each cluster of catchments is presented as z-score (traits_categories_zscores_per_catchment_class.csv). The link to the hydrological behavior of clusters of catchments is displayed by boxplots, each describing a particular river discharge index (SI3.pdf).more »« less

Authors:

Ciulla, Fabio;

Lawrence Berkeley National Laboratory; Lawrence Berkeley National Laboratory
Lawrence Berkeley National Laboratory

Publication Date:: Sun Jan 01 04:00:00 UTC 2023

Research Org.:: Environmental System Science Data Infrastructure for a Virtual Ecosystem; iNAIADS

Sponsoring Org.:: U.S. DOE > Office of Science > Biological and Environmental Research (BER)

Subject:: 54 ENVIRONMENTAL SCIENCES; EARTH SCIENCE > CLIMATE INDICATORS > TERRESTRIAL HYDROSPHERE INDICATORS; EARTH SCIENCE > LAND SURFACE; EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > SURFACE WATER; ESS-DIVE File Level Metadata Reporting Format

OSTI Identifier:: 1987555

DOI:: https://doi.org/10.15485/1987555

Citation Formats


                    Ciulla, Fabio, and Varadharajan, Charuleka. Classification of River Catchments in the Contiguous United States: Code, Dataset, Similarity Patterns, and Resulting Classes.  United States: N. p., 2023. 
        Web.  doi:10.15485/1987555.

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

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                    Ciulla, Fabio, and Varadharajan, Charuleka. 2023.  
"Classification of River Catchments in the Contiguous United States: Code, Dataset, Similarity Patterns, and Resulting Classes".  United States.  doi:https://doi.org/10.15485/1987555.  https://www.osti.gov/servlets/purl/1987555. Pub date:Sun Jan 01 04:00:00 UTC 2023

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@article{osti_1987555,

  title        = {Classification of River Catchments in the Contiguous United States: Code, Dataset, Similarity Patterns, and Resulting Classes},

  author       = {Ciulla, Fabio and Varadharajan, Charuleka},

  abstractNote = {This dataset serves as supplementary information for the paper by Ciulla F. and Varadharajan C. A Network Approach for Multiscale Catchment Classification using Traits (see reference 1). It contains environmental and physical catchment traits, such as temperatures, precipitation, land use and human interference, from 9067 sites across the contiguous United States (CONUS). The purpose of this dataset is to provide information for a better trait-based categorization of river catchments in the CONUS using networks as an analytical tool. The traits variables match the ones present in the GAGES-II dataset and the preprocessing steps are described in the Methods section (processed_dataset.csv). Additionally we include the topologies (nodes, edges and clusters, also referred as classes) of the catchment network and traits network generated by said dataset (csv and json files). A series of tables support the information carried by the network providing more detailed descriptions of cluster components (SI1.pdf). A summary of all the plots of clusters of catchments with at least 50 nodes is provided (SI2.pdf). The characteristic traits for each cluster of catchments is presented as z-score (traits_categories_zscores_per_catchment_class.csv). The link to the hydrological behavior of clusters of catchments is displayed by boxplots, each describing a particular river discharge index (SI3.pdf). Both csv and json files can be read by common text editors but the data contained into them can be better handled using programming languages like python and database oriented libraries like pandas. Pdf files can be read by any pdf reader software.[02-23-2024] Update: The code and datasets necessary to reproduce the results of the study are available as a zipped repository (code_datasets_catchments_similarity.zip).},

  doi          = {10.15485/1987555},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Sun Jan 01 04:00:00 UTC 2023},

  month        = {Sun Jan 01 04:00:00 UTC 2023}

}

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DOI: https://doi.org/10.15485/1987555

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