Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Skip to content

National Multi Order Hydrologic Position (MOHP) Predictor Data for Groundwater and Groundwater-Quality Modeling

Metadata Updated: July 6, 2024

Multi Order Hydrologic Position (MOHP) raster datasets: Distance from Stream to Divide (DSD) and Lateral Position (LP) have been produced nationally for the 48 contiguous United States at 30-meter and 90-meter cell resolution for stream orders 1 through 9. These data are available for testing as predictor variables for various regional and national groundwater-flow and groundwater-quality statistical models. For quicker downloads, these data are available here nationally at a 90-meter cell resolution, as well as on the National Spatial Data Infrastructure (NSDI) Node at the higher 30-meter cell resolution (
https://water.usgs.gov/GIS/metadata/styles/landingPage/national_MOHP_Predictor.xml ). The concept behind MOHP is that for any given point on the earth’s surface there is the potential for longer and longer groundwater flow paths as one goes deeper and deeper beneath the land surface. These increasing depths correspond to increasing stream orders. Or in other words, with increasing depth these paths of groundwater flow travel further from divides to point of discharge which are to increasingly larger streams of higher stream order.
DSD – Raster – Distance from Stream to Divide (DSD) rasters have cell values equal to the sum of the shortest distance to the stream or associated waterbody plus the shortest distance to the matching Thiessen divide. There are 9 rasters for streams orders 1 through 9. Units are in meters. LP – Raster -- the lateral position (LP) raster has cell values equal to the shortest distance to the stream or associated waterbody divided by the DSD. There are 9 rasters for streams orders 1 through 9. Combined, these two factors, DSD and LP, provide a measure or description of potential distance of groundwater flow to any location along the groundwater flow path.

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.

Downloads & Resources

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/2c374421a62925dc5e575d1683490ea7
Identifier USGS:5b4e34dfe4b06a6dd180272e
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 09ffbff1-db4a-4593-9510-83804e1a110c
Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
Harvest Source Title DOI EDI
Metadata Type geospatial
Old Spatial -127.857240873,23.2443912389,-65.3748244399,51.5120922457
Publisher Hierarchy White House > U.S. Department of the Interior > U.S. Geological Survey
Source Datajson Identifier True
Source Hash c1a4f7e5cd86fd571e24ce749a4b761a5fc541a4a208ddd3fcdf8f01e4f72eab
Source Schema Version 1.1
Spatial {"type": "Polygon", "coordinates": -127.857240873, 23.2443912389, -127.857240873, 51.5120922457, -65.3748244399, 51.5120922457, -65.3748244399, 23.2443912389, -127.857240873, 23.2443912389}

Didn't find what you're looking for? Suggest a dataset here.