Background electrical resistivity tomography data, 2019

Electrical resistivity Tomography (ERT) is a direct current geophysical method that is used to estimate the subsurface distribution of the electrical resistivity (measured in ohm-meters, or ohm-m) of a material, and is based on the assumption that measured electric potentials (voltages) near current carrying electrodes are influenced by the electrical resistivities of the underlying material (Zohdy and others, 1974; Day-Lewis and others, 2008). Bulk resistivity is controlled by lithology, porosity, degree of saturation, chemistry of groundwater, and the conductivity of earth materials at the surface. If the degree of saturation is the only expected variable, as is the case near the groundwater replenishment and reuse project (GRRP) facility, groundwater infiltration paths can be identified with sequential ERT surveys. Data from two ERT surveys (YVHDWW_L1 and YVHDWW_L2) were collected orthogonal to each other in May and September of 2019 to determine background resistivity values downslope of the GRRP facility prior to release of reclaimed wastewater to the infiltration ponds. The resistivity data are presented in native .stg format, as well as topographic data for each electrode in .trn format.

Data and Resources

Field Value
accessLevel public
bureauCode {010:12}
catalog_@context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
catalog_conformsTo https://project-open-data.cio.gov/v1.1/schema
catalog_describedBy https://project-open-data.cio.gov/v1.1/schema/catalog.json
identifier USGS:5ef4e89682ced62aaae69246
metadata_type geospatial
modified 20201002
old-spatial -116.376600, 34.128400, -116.371400, 34.132800
publisher U.S. Geological Survey
publisher_hierarchy Department of the Interior > U.S. Geological Survey
resource-type Dataset
source_datajson_identifier true
source_hash efb09a95b3870a7332085a7cfa9ac0f2ffaeb726
source_schema_version 1.1
spatial {"type": "Polygon", "coordinates": [[[-116.376600, 34.128400], [-116.376600, 34.132800], [ -116.371400, 34.132800], [ -116.371400, 34.128400], [-116.376600, 34.128400]]]}
theme {geospatial}
Groups
  • AmeriGEOSS
  • National Provider
  • North America
Tags
  • amerigeo
  • amerigeoss
  • california
  • ckan
  • electrical-resistivity-imaging
  • environment
  • geo
  • geophysics
  • geoscientificinformation
  • geoss
  • groundwater
  • groundwater-flow
  • joshua-tree-north
  • national
  • north-america
  • san-bernardino-county
  • united-states
  • usgs-5ef4e89682ced62aaae69246
  • yucca-valley-north
isopen False
license_id notspecified
license_title License not specified
maintainer Christopher P Ely
maintainer_email cpely@usgs.gov
metadata_created 2025-11-22T00:07:09.371907
metadata_modified 2025-11-22T00:07:09.371910
notes Electrical resistivity Tomography (ERT) is a direct current geophysical method that is used to estimate the subsurface distribution of the electrical resistivity (measured in ohm-meters, or ohm-m) of a material, and is based on the assumption that measured electric potentials (voltages) near current carrying electrodes are influenced by the electrical resistivities of the underlying material (Zohdy and others, 1974; Day-Lewis and others, 2008). Bulk resistivity is controlled by lithology, porosity, degree of saturation, chemistry of groundwater, and the conductivity of earth materials at the surface. If the degree of saturation is the only expected variable, as is the case near the groundwater replenishment and reuse project (GRRP) facility, groundwater infiltration paths can be identified with sequential ERT surveys. Data from two ERT surveys (YVHDWW_L1 and YVHDWW_L2) were collected orthogonal to each other in May and September of 2019 to determine background resistivity values downslope of the GRRP facility prior to release of reclaimed wastewater to the infiltration ponds. The resistivity data are presented in native *.stg format, as well as topographic data for each electrode in *.trn format.
num_resources 2
num_tags 19
title Background electrical resistivity tomography data, 2019