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Point data for four case studies related to testing of multi-order hydrologic position

Metadata Updated: July 6, 2024

The location of a point (or pixel) within the conterminous U.S. can be assigned based on its position relative to the Nation’s stream network. Two metrics are recognized: lateral position (LP) and distance from stream to divide (DSD). And given that a point can have different positions in different hydrologic orders the term multi-order hydrologic position (MOHP) is used to describe the ensemble of hydrologic positions. LP and DSD were developed for nine hydrologic orders across the conterminous U.S. (Belitz and others, 2019; Moore and others, 2019). Four case studies are presented here that were used for evaluating the utility of MOHP in the context of random forest machine learning (Belitz and others, 2019). Two of the case studies evaluate categorical response variables: geomorphic province in the Central Valley of California (Faunt, 2009) and physiographic province in the conterminous U.S. (Fenneman and Johnson, 1946). The other two case studies evaluated depth to the water table (DTW), which is a continuous variable. DTW for these two cases were determined from: 1) a numerical simulation model of the groundwater flow system in the Fox-Wolf-Peshtigo area located to the west of Lake Michigan (Juckem and others, 2017); and 2) observed values in Wisconsin (Fan and others, 2013). The point data for each of the four case studies include: land surface elevation, the 18 MOHP metrics (LP and DSD for nine hydrologic orders), and the appropriate response variable. Latitude and longitude are also included for the purposes of plotting. The case studies show that some MOHP metrics serve as indicators of hydrologic process and others as indicators of location. MOHP is shown to have utility as a predictor variable across a large range of scales (50,000 to 8,000,000 square kilometers). Four comma-separated values (.csv) data tables are included in this data release: 1) CVAL_sampsites_mohp.csv -- Central Valley, California 2) FPR_sampsites_mohp.csv -- Fenneman Physiographic Regions 3) FWP_sampsites_mohp.csv -- Simulated depth-to-water in the Fox-Wolf-Peshtigo model area 4) WIOBS_sampsites_mohp.csv -- Observed depth-to-water throughout Wisconsin

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

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Dates

Metadata Created Date June 1, 2023
Metadata Updated Date July 6, 2024

Metadata Source

Harvested from DOI EDI

Additional Metadata

Resource Type Dataset
Metadata Created Date June 1, 2023
Metadata Updated Date July 6, 2024
Publisher U.S. Geological Survey
Maintainer
@Id http://datainventory.doi.gov/id/dataset/127f2a1be230c09641819bc275291171
Identifier USGS:5ced4d1de4b02eb068de9227
Data Last Modified 20200826
Category geospatial
Public Access Level public
Bureau Code 010:12
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://datainventory.doi.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id 3bfa8468-7d71-4327-ab7c-59cd08f32b6c
Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
Harvest Source Title DOI EDI
Metadata Type geospatial
Old Spatial -125.33203125000001,24.766784522874453,-66.79687500000001,49.66762782262194
Publisher Hierarchy White House > U.S. Department of the Interior > U.S. Geological Survey
Source Datajson Identifier True
Source Hash d98e88aa97c2cf3c84892d7d8ffc16ff4725928c7775d49b9558594395f8815b
Source Schema Version 1.1
Spatial {"type": "Polygon", "coordinates": -125.33203125000001, 24.766784522874453, -125.33203125000001, 49.66762782262194, -66.79687500000001, 49.66762782262194, -66.79687500000001, 24.766784522874453, -125.33203125000001, 24.766784522874453}

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