Statewide AEM Surveys Project Overview

The Department of Water Resources’ (DWR’s) Statewide Airborne Electromagnetic (AEM) Surveys Project is funded through California’s Proposition 68 and the General Fund. The goal of the project is to improve the understanding of groundwater aquifer structure to support the state and local goal of sustainable groundwater management and the implementation of the Sustainable Groundwater Management Act (SGMA).

During an AEM survey, a helicopter tows electronic equipment that sends signals into the ground which bounce back. The data collected are used to create continuous images showing the distribution of electrical resistivity values of the subsurface materials that can be interpreted for lithologic properties. The resulting information will provide a standardized, statewide dataset that improves the understanding of large-scale aquifer structures and supports the development or refinement of hydrogeologic conceptual models and can help identify areas for recharging groundwater.

DWR collected AEM data in all of California’s high- and medium-priority groundwater basins, where data collection is feasible. Data were collected in a coarsely spaced grid, with a line spacing of approximately 2-miles by 8-miles. AEM data collection started in 2021 and was completed in 2023. Additional information about the project can be found on the Statewide AEM Survey website. See the publication below for an overview of the project and a preliminary analysis of the AEM data.

California’s Statewide Airborne Electromagnetic Surveys and Preliminary Hydrogeologic Interpretations

Survey Areas

AEM data are being collected in groups of groundwater basins, defined as a Survey Area. See Survey Area Map for groundwater subbasins within a Survey Area:

• Survey Area 1: 180/400 Foot Aquifer (partial), East Side (partial), Upper Valley, Forebay Aquifer, Paso Robles, Atascadero (limited), Adelaida (limited), Cuyama Valley.
• Survey Area 2: Scott River Valley, Shasta Valley, Butte Valley, Tulelake, Fall River Valley (limited), Big Valley (Modoc/Lassen County).
• Survey Area 3: Big Valley (Lake County), Ukiah Valley, Santa Rosa Plain, Petaluma Valley, Sonoma Valley.
• Survey Area 4: White Wolf, Kern County, Tulare Lake, Tule, Kaweah.
• Survey Area 5: Pleasant Valley, Westside, Kings, Madera, Chowchilla, Merced, Turlock, Modesto, Delta-Mendota
• Survey Area 6: Cosumnes, Tracy, Eastern San Joaquin, East Contra Costa, Solano, Livermore, South American, North American, Yolo, Sutter, South Yuba, North Yuba
• Survey Area 7: Colusa, Butte, Wyandotte Creek, Vina, Los Molinos, Corning, Red Bluff, Antelope, Bowman, Bend, Millville, South Battle Creek, Anderson, Enterprise, Eel River, Sierra Valley
• Survey Area 8: Seaside, Monterey, 180/400 (partially surveyed Summer 2021), Eastside (partially surveyed Summer 2021), Langley, Pajaro, Santa Cruz Mid-County, Santa Margarita, San Benito, and Llagas (partial).
• Survey Area 9: Basin Characterization Pilot Study 1 - Madera and Kings.
• Survey Area 10: San Antonio Creek Valley, Arroyo Grande, Santa Maria, San Luis Obispo, Los Osos Area, Warden Creek, Chorro Valley (limited), Morro Valley (limited)
• Survey Area 11: Indian Wells Valley, Rose Valley, Owens Valley, Fish Slough, Indio, Mission Creek, West Salton Sea (limited), East Salton Sea (limited), Ocotillo-Clark Valley (limited), Imperial Valley (limited),Chocolate Valley (limited), Borrego Springs, and San Jacinto

Data Reports

Data reports detail the AEM data collection, processing, inversion, interpretation, and uncertainty analyses methods and procedures. Data reports also describe additional datasets used to support the AEM surveys, including digitized lithology and geophysical logs. Multiple data reports may be provided for a single Survey Area, depending on the Survey Area coverage.

Data Availability and Types

All data collected as a part of the Statewide AEM Surveys will be made publicly available, by survey area, approximately six to twelve months after individual surveys are complete (depending on survey area size). Datasets that will be publicly available include:

AEM Datasets

• Raw AEM Data
• Processed AEM Data
• Inverted AEM Data
• Inverted AEM Data Uncertainty Analysis
• Interpreted AEM Data (for coarse fraction)
• Interpreted AEM Data Uncertainty Analysis

Supporting Datasets

• Flown Survey Lines
• Digitized Lithology and Geophysical Logs

NEW! Revisions to digitized lithology and geophysical logs

AEM Data Viewers

DWR has developed AEM Data Viewers to provides a quick and easy way to visualize the AEM electrical resistivity data and the AEM data interpretations (as texture) in a three-dimensional space. The most recent data available are shown, which my be the provisional data for some areas that are not yet finalized. The Data Viewers can be accessed by direct link, below, or from the Data Viewer Landing Page.

• AEM 3D Viewer (Beta) (computer only)

• AEM Profile Viewer

• SGMA Data Viewer (Basin Characterization tab)

AEM Depth Slice and Shallow Subsurface Average Maps

As a part of DWR’s upcoming Basin Characterization Program, DWR will be publishing a series of maps and tools to support advanced data analyses. The first of these maps have now been published and provide analyses of the Statewide AEM Survey data to support the identification of potential recharge areas. The maps are located on the SGMA Data Viewer (under the Hydrogeologic Conceptual Model tab) and show the AEM electrical resistivity and AEM-derived texture data as the following:

• Shallow Subsurface Average: Maps showing the average electrical resistivity and AEM-derived texture in the shallow subsurface (the top approximately 50 feet below ground surface). These maps support identification of potential recharge areas, where the top 50 feet is dominated by high resistivity or coarse-grained materials.

• Depth Slices: Depth slice automations showing changes in electrical resistivity and AEM-derived texture with depth. These maps aid in delineating the geometry of large-scale features (for example, incised valley fills).

Shapefiles for the formatted AEM electrical resistivity data and AEM derived texture data as depth slices and the shallow subsurface average can be downloaded here:

• Electrical Resistivity Depth Slices and Shallow Subsurface Average Maps

• Texture Interpretation (Coarse Fraction) Depth Slices and Shallow Subsurface Average Maps

Technical Memos

Technical memos are developed by DWR's consultant team (Ramboll Consulting) to describe research related to AEM survey planning or data collection. Research described in the technical memos may also be formally published in a journal publication.

• AEM Test Flights to Evaluate the Bias Signal Caused by Vineyard Trellises Containing Metal

• SkyTEM Instrument Comparison for Airborne EM

2018-2020 AEM Pilot Studies

Three AEM pilot studies were conducted in California from 2018-2020 to support the development of the Statewide AEM Survey Project. The AEM Pilot Studies were conducted in the Sacramento Valley in Colusa and Butte county groundwater basins, the Salinas Valley in Paso Robles groundwater basin, and in the Indian Wells Valley groundwater basin.

Provisional Statement

Data Reports and datasets labeled as provisional may be incomplete and are subject to revision until they have been thoroughly reviewed and received final approval. Provisional data and reports may be inaccurate and subsequent review may result in revisions to the data and reports. Data users are cautioned to consider carefully the provisional nature of the information before using it for decisions that concern personal or public safety or the conduct of business that involves substantial monetary or operational consequences.

Airborne electromagnetic (AEM) geophysical data were collected in California as a part of AEM pilot studies. The purpose of the AEM pilot studies was to inform the development of the Department of Water Resources’ (DWR’s) statewide AEM survey project. The AEM pilot studies were conducted in three areas: Butte and Glenn Counties, San Luis Obispo County, and Indian Wells Valley. The AEM surveys were conducted from 2018 through 2020 and were led by Stanford University with participants from the academic and private sectors, and local and state water agencies. All data used, collected, or created as a part of the AEM pilot studies are provided here. The AEM pilot studies were funded by grants from DWR, the Ministry of Denmark, and three local agencies (Butte County, Indian Wells Valley Water District, and San Luis Obispo County - Paso Robles). Pilot study participants included Stanford University, Aarhus University, Aqua Geo Frameworks, Ramboll, I-GIS, SkyTEM, University of California Davis, California State University Sacramento, California State University Chico, Parker Groundwater, the Danish Water Technology Alliance, the Danish Environmental Protection Agency, Glenn County Department of Water Resource Conservation, Butte County Department of Water Conservation, Indian Wells Valley Water District, and San Luis Obispo County.

Statewide AEM Surveys Project Overview The Department of Water Resources’ (DWR’s) Statewide Airborne Electromagnetic (AEM) Surveys Project is funded through California’s Proposition 68 and the General Fund. The goal of the project is to improve the understanding of groundwater aquifer structure to support the state and local goal of sustainable groundwater management and the implementation of the Sustainable Groundwater Management Act (SGMA). During an AEM survey, a helicopter tows electronic equipment that sends signals into the ground which bounce back. The data collected are used to create continuous images showing the distribution of electrical resistivity values of the subsurface materials that can be interpreted for lithologic properties. The resulting information will provide a standardized, statewide dataset that improves the understanding of large-scale aquifer structures and supports the development or refinement of hydrogeologic conceptual models and can help identify areas for recharging groundwater. DWR collected AEM data in all of California’s high- and medium-priority groundwater basins, where data collection is feasible. Data were collected in a coarsely spaced grid, with a line spacing of approximately 2-miles by 8-miles. AEM data collection started in 2021 and was completed in 2023. Additional information about the project can be found on the Statewide AEM Survey website. See the publication below for an overview of the project and a preliminary analysis of the AEM data. California’s Statewide Airborne Electromagnetic Surveys and Preliminary Hydrogeologic Interpretations Survey Areas AEM data are being collected in groups of groundwater basins, defined as a Survey Area. See Survey Area Map for groundwater subbasins within a Survey Area: Survey Area 1: 180/400 Foot Aquifer (partial), East Side (partial), Upper Valley, Forebay Aquifer, Paso Robles, Atascadero (limited), Adelaida (limited), Cuyama Valley. Survey Area 2: Scott River Valley, Shasta Valley, Butte Valley, Tulelake, Fall River Valley (limited), Big Valley (Modoc/Lassen County). Survey Area 3: Big Valley (Lake County), Ukiah Valley, Santa Rosa Plain, Petaluma Valley, Sonoma Valley. Survey Area 4: White Wolf, Kern County, Tulare Lake, Tule, Kaweah. Survey Area 5: Pleasant Valley, Westside, Kings, Madera, Chowchilla, Merced, Turlock, Modesto, Delta-Mendota Survey Area 6: Cosumnes, Tracy, Eastern San Joaquin, East Contra Costa, Solano, Livermore, South American, North American, Yolo, Sutter, South Yuba, North Yuba Survey Area 7: Colusa, Butte, Wyandotte Creek, Vina, Los Molinos, Corning, Red Bluff, Antelope, Bowman, Bend, Millville, South Battle Creek, Anderson, Enterprise, Eel River, Sierra Valley Survey Area 8: Seaside, Monterey, 180/400 (partially surveyed Summer 2021), Eastside (partially surveyed Summer 2021), Langley, Pajaro, Santa Cruz Mid-County, Santa Margarita, San Benito, and Llagas (partial). Survey Area 9: Basin Characterization Pilot Study 1 - Madera and Kings. Survey Area 10: San Antonio Creek Valley, Arroyo Grande, Santa Maria, San Luis Obispo, Los Osos Area, Warden Creek, Chorro Valley (limited), Morro Valley (limited) Survey Area 11: Indian Wells Valley, Rose Valley, Owens Valley, Fish Slough, Indio, Mission Creek, West Salton Sea (limited), East Salton Sea (limited), Ocotillo-Clark Valley (limited), Imperial Valley (limited),Chocolate Valley (limited), Borrego Springs, and San Jacinto Data Reports Data reports detail the AEM data collection, processing, inversion, interpretation, and uncertainty analyses methods and procedures. Data reports also describe additional datasets used to support the AEM surveys, including digitized lithology and geophysical logs. Multiple data reports may be provided for a single Survey Area, depending on the Survey Area coverage. Data Availability and Types All data collected as a part of the Statewide AEM Surveys will be made publicly available, by survey area, approximately six to twelve months after individual surveys are complete (depending on survey area size). Datasets that will be publicly available include: AEM Datasets Raw AEM Data Processed AEM Data Inverted AEM Data Inverted AEM Data Uncertainty Analysis Interpreted AEM Data (for coarse fraction) Interpreted AEM Data Uncertainty Analysis Supporting Datasets Flown Survey Lines Digitized Lithology Logs Digitized Geophysical Logs AEM Data Viewers DWR has developed AEM Data Viewers to provides a quick and easy way to visualize the AEM electrical resistivity data and the AEM data interpretations (as texture) in a three-dimensional space. The most recent data available are shown, which my be the provisional data for some areas that are not yet finalized. The Data Viewers can be accessed by direct link, below, or from the Data Viewer Landing Page. AEM 3D Viewer (Beta) (computer only) AEM Profile Viewer SGMA Data Viewer (Basin Characterization tab) AEM Depth Slice and Shallow Subsurface Average Maps As a part of DWR’s upcoming Basin Characterization Program, DWR will be publishing a series of maps and tools to support advanced data analyses. The first of these maps have now been published and provide analyses of the Statewide AEM Survey data to support the identification of potential recharge areas. The maps are located on the SGMA Data Viewer (under the Hydrogeologic Conceptual Model tab) and show the AEM electrical resistivity and AEM-derived texture data as the following: Shallow Subsurface Average: Maps showing the average electrical resistivity and AEM-derived texture in the shallow subsurface (the top approximately 50 feet below ground surface). These maps support identification of potential recharge areas, where the top 50 feet is dominated by high resistivity or coarse-grained materials. Depth Slices: Depth slice automations showing changes in electrical resistivity and AEM-derived texture with depth. These maps aid in delineating the geometry of large-scale features (for example, incised valley fills). Shapefiles for the formatted AEM electrical resistivity data and AEM derived texture data as depth slices and the shallow subsurface average can be downloaded here: Electrical Resistivity Depth Slices and Shallow Subsurface Average Maps Texture Interpretation (Coarse Fraction) Depth Slices and Shallow Subsurface Average Maps Technical Memos Technical memos are developed by DWR's consultant team (Ramboll Consulting) to describe research related to AEM survey planning or data collection. Research described in the technical memos may also be formally published in a journal publication. AEM Test Flights to Evaluate the Bias Signal Caused by Vineyard Trellises Containing Metal SkyTEM Instrument Comparison for Airborne EM 2018-2020 AEM Pilot Studies Three AEM pilot studies were conducted in California from 2018-2020 to support the development of the Statewide AEM Survey Project. The AEM Pilot Studies were conducted in the Sacramento Valley in Colusa and Butte county groundwater basins, the Salinas Valley in Paso Robles groundwater basin, and in the Indian Wells Valley groundwater basin. Provisional Statement Data Reports and datasets labeled as provisional may be incomplete and are subject to revision until they have been thoroughly reviewed and received final approval. Provisional data and reports may be inaccurate and subsequent review may result in revisions to the data and reports. Data users are cautioned to consider carefully the provisional nature of the information before using it for decisions that concern personal or public safety or the conduct of business that involves substantial monetary or operational consequences.

Airborne electromagnetic (AEM) and magnetic survey data were collected during October 2016 along 1,443 line kilometers in the southwestern San Joaquin Valley near Lost Hills, California. These data were collected in support of groundwater salinity mapping and hydrogeologic framework development as part of the U.S. Geological Survey California Oil, Gas, and Groundwater program and the California State Water Resources Control Board’s Program of Regional Monitoring of Water Quality in Areas of Oil and Gas Production. Minimally processed binary AEM data received from the contractor were imported into the Aarhus Workbench software (v. 5.6.3.0, Aarhus Geosoftware, Aarhus, Denmark) and processed. Filters were applied to inclinometer and spatial positioning data to smooth raw data and remove sensor drop outs. Altimeter data were filtered, smoothed, and manually edited to correct false altitudes associated with trees and other obstacles, resulting in processed altitude representative of th ...

Airborne electromagnetic (AEM) and magnetic survey data were collected during October 2016 over a total distance of 262 line kilometers in the southeastern San Joaquin Valley near Cawelo, California. These data were collected in support of groundwater salinity mapping and hydrogeologic framework development as part of the U.S. Geological Survey California Oil, Gas, and Groundwater program and the California State Water Resources Control Board’s Oil and Gas Regional Monitoring Program. Minimally processed binary AEM data received from SkyTEM ApS were imported into the Aarhus Workbench software (Aarhus Geosoftware, Aarhus, Denmark) and processed. Filters were applied to inclinometer and spatial positioning data to smooth raw data and remove sensor dropouts. Altimeter data were filtered, smoothed, and manually edited to correct false altitudes associated with trees and other obstacles, resulting in processed altitude representative of the distance between the AEM sensor airframe and ...

DWR has a long history of studying and characterizing California’s groundwater aquifers as a part of California’s Groundwater (Bulletin 118). California's Groundwater Basin Characterization Program provides the latest data and information about California’s groundwater basins to help local communities better understand their aquifer systems and support local and statewide groundwater management. Under the Basin Characterization Program, new and existing data (AEM, lithology logs, geophysical logs, etc.) are integrated to create continuous maps and three-dimensional models. To support this effort, new data analysis tools have been developed to create texture models, hydrostratigraphic models, and aquifer flow parameters. Data collection efforts have been expanded to include advanced geologic, hydrogeologic, and geophysical data collection and data digitization and quality control efforts will continue. To continue to support data access and data equity, the Basin Characterization Program has developed new online, GIS-based, visualization tools to serve as a central hub for accessing and exploring groundwater related data in California. Additional information can be found on the Basin Characterization Program webpage. #DWR's Evaluation of Groundwater Resources ## Maps and Models DWR is undertaking local, regional, and statewide investigations to evaluate California's groundwater resources and develop state-stewarded maps and models. New and existing data have been combined and integrated using the analysis tools described below to develop maps and models that describe grain size, the hydrostratigraphic properties, and hydrogeologic conceptual properties of California’s aquifers. These maps and models help groundwater managers understand how groundwater is stored and moves within the aquifer. The models will be state-stewarded, meaning that they will be regularly updated, as new data becomes available, to ensure that up-to-date information is used for groundwater management activities. The first iterations of the following maps and models will be published as they are developed: + Texture Models + Hydrostratigraphic Models + Aquifer Recharge Potential Maps + Extent of Important Aquifer Units + Depth to Basement + Depth to Freshwater Click on the link below for each local, regional, or statewide investigation to find the following datasets. ##Local Investigations + Madera & North Kings: AEM data collection, lithology log digitization, texture model development, aquifer recharge potential mapping analysis. + Pajaro: AEM and tTEM data collection + Western San Joaquin Valley: AEM data collection, lithology and geophysical log data digitization, texture model development. + Prospect Island: AEM data collection, FloaTEM data collection test. ##Regional Investigations + Sacramento Valley: AEM data collection, texture model development, aquifer recharge potential mapping analysis. + Four County Area of San Joaquin Valley (Madera, Fresno, Kings, and Tulare) + San Joaquin Valley ##Statewide Investigations + Statewide AEM Surveys: AEM data collection, geophysical and lithology log data digitization. # Data Collection & Compilation As a part of the Basin Characterization Program, advanced geologic, hydrogeologic, and geophysical data will be collected to improve our understanding of groundwater basins. Data collected under Basin Characterization are collected at a local, regional, or statewide scale depending on the scope of the study. Advanced data collection methods include: + Airborne electromagnetics (AEM) + All-terrain vehicle towed electromagnetics (tTEM) + Watercraft towed electromagnetics (FloaTEM) + Geophysical borehole logging ## Digitized Existing Lithology and Geophysical Logs Lithology and geophysical logging data have been digitized to support the Statewide AEM Survey Project and will continue to be digitized to support Basin Characterization efforts. All digitized lithology logs with Well Completion Report IDs will be imported back into the OSWCR database. Digitized lithology and geophysical logging can be found under the following resource: + Digitized Lithology and Geophysical Logs. #Analysis Tools and Process Documents To develop the state-stewarded maps and models outlined above, new tools and process documents have been created to integrate and analyze a wide range of data, including geologic, geophysical, and hydrogeologic information. By combining and assessing various datasets, these tools help create a more complete picture of California's groundwater basins. All tools, along with guidance documents, are made publicly available for local groundwater managers to use to support development of maps and models at a local scale. All tools and guidance will be updated as revisions to tools and process documents are made. ##Data Analysis Tools + Data2Texture: Data2Texture is an advanced spatial data interpolation tool for estimating the distribution of sediment textures from airborne electromagnetic data and lithology logs to create a 3D texture model + Data2HSM - Smart Interpretation: Data2HSM via Smart Interpretation (SI) is a semi-automatic Python tool for delineating continuous hydrogeologic surfaces from airborne electromagnetic data products. + Data2HSM - Gaussian Mixture Model: The Data2HSM via Gaussian Mixture Model tool ingests the AEM data and groups the data into a user-specified number of clusters that are interpreted as stratigraphic units in the hydrostratigraphic model (HSM) + Data2HSM - Geological Pseudolabel Deep Neural Network: The GeoPDNN (Geological Pseudolabel Deep Neural Network) is a semi-supervised machine learning tool that integrates lithologic well logs and AEM data into plausible stratigraphic surfaces. + Texture2Par V2: Texture2Par V2 is a groundwater model pre-processor and parameterization utility developed to work with the IWFM and MODFLOW families of hydrologic simulation code. ##Process Documents + Aquifer Recharge Potential Mapping: The Aquifer Recharge Potential (ARP) Mapping Process Document provides a framework for identifying locations that have relatively higher potential for managed aquifer recharge. #Data Visualization Data access equity is a priority for the Basin Characterization Program. To ensure data access equity, the Basin Characterization Program has developed applications and tools to allow data to be visualized without needing access to expensive data visualization software. This list below provides links and descriptions for the Basin Characterization's suite of data viewers. SGMA Data Viewer: Basin Characterization tab: Provides maps, depth slices, and profiles of Basin Characterization maps, models, and datasets, including the following: + Aquifer Recharge Potential Maps + Subsurface Texture Model Depth Slices + Statewide AEM Survey Texture Depth Slices + Lithology Log Location Maps + Geophysical Logs Location Maps + Statewide AEM Survey Profile Images 3D AEM Data Viewer: Displays the Statewide AEM Survey electrical resistivity and coarse fraction data, along with lithology logs, in a three-dimensional space. California's Groundwater Subsurface Viewer: Provides a map view and profile view of the Statewide AEM Survey electrical resistivity and coarse fraction data, along with lithology logs. The map view dynamically shows the exact location of AEM data displayed. #Basin Characterization Exchange The Basin Characterization Exchange (BCX) is a meeting series and network space for the Basin Characterization community to exchange ideas, share lessons

This repository includes airborne electromagnetic (AEM) data acquired at Tulare in the southern portion of the Central Valley of California, USA. Also, the repository includes the derived electrical resistivity model from the observed AEM data.

DWR has a long history of studying and characterizing California’s groundwater aquifers as a part of California’s Groundwater (Bulletin 118). California's Groundwater Basin Characterization Program provides the latest data and information about California’s groundwater basins to help local communities better understand their aquifer systems and support local and statewide groundwater management.

Under the Basin Characterization Program, new and existing data (AEM, lithology logs, geophysical logs, etc.) are integrated to create continuous maps and three-dimensional models. To support this effort, new data analysis tools have been developed to create texture models, hydrostratigraphic models, and aquifer flow parameters. Data collection efforts have been expanded to include advanced geologic, hydrogeologic, and geophysical data collection and data digitization and quality control efforts will continue. To continue to support data access and data equity, the Basin Characterization Program has developed new online, GIS-based, visualization tools to serve as a central hub for accessing and exploring groundwater related data in California.

Additional information can be found on the Basin Characterization Program webpage.

DWR's Evaluation of Groundwater Resources

Maps and Models

DWR is undertaking local, regional, and statewide investigations to evaluate California's groundwater resources and develop state-stewarded maps and models. New and existing data have been combined and integrated using the analysis tools described below to develop maps and models that describe grain size, the hydrostratigraphic properties, and hydrogeologic conceptual properties of California’s aquifers. These maps and models help groundwater managers understand how groundwater is stored and moves within the aquifer. The models will be state-stewarded, meaning that they will be regularly updated, as new data becomes available, to ensure that up-to-date information is used for groundwater management activities. The first iterations of the following maps and models will be published as they are developed:

• Texture Models
• Hydrostratigraphic Models
• Aquifer Recharge Potential Maps
• Extent of Important Aquifer Units
• Depth to Basement
• Depth to Freshwater

Click on the link below for each local, regional, or statewide investigation to find the following datasets.

Local Investigations

• Madera & North Kings: AEM data collection, lithology log digitization, texture model development, aquifer recharge potential mapping analysis.
• Pajaro: AEM and tTEM data collection
• Western San Joaquin Valley: AEM data collection, lithology and geophysical log data digitization, texture model development.
• Prospect Island: AEM data collection, FloaTEM data collection test.

Regional Investigations

• Sacramento Valley: AEM data collection, texture model development, aquifer recharge potential mapping analysis.
• Four County Area of San Joaquin Valley (Madera, Fresno, Kings, and Tulare counties) : AEM data collection, texture model development, hydrogeologic conceptual model development, clay delineation, subsidence potential and mitigation, and aquifer recharge potential mapping analysis.
• San Joaquin Valley

Statewide Investigations

• Statewide AEM Surveys: AEM data collection, geophysical and lithology log data digitization.

Data Collection & Compilation

As a part of the Basin Characterization Program, advanced geologic, hydrogeologic, and geophysical data will be collected to improve our understanding of groundwater basins. Data collected under Basin Characterization are collected at a local, regional, or statewide scale depending on the scope of the study. Advanced data collection methods include:

• Airborne electromagnetics (AEM)
• All-terrain vehicle towed electromagnetics (tTEM)
• Watercraft towed electromagnetics (FloaTEM)
• Geophysical borehole logging

Digitized Existing Lithology and Geophysical Logs

Lithology and geophysical logging data have been digitized to support the Statewide AEM Survey Project and will continue to be digitized to support Basin Characterization efforts. All digitized lithology logs with Well Completion Report IDs will be imported back into the OSWCR database. Digitized lithology and geophysical logging can be found under the following resource:

• Digitized Lithology and Geophysical Logs.

Analysis Tools and Process Documents

To develop the state-stewarded maps and models outlined above, new tools and process documents have been created to integrate and analyze a wide range of data, including geologic, geophysical, and hydrogeologic information. By combining and assessing various datasets, these tools help create a more complete picture of California's groundwater basins. All tools, along with guidance documents, are made publicly available for local groundwater managers to use to support development of maps and models at a local scale. All tools and guidance will be updated as revisions to tools and process documents are made.

Data Analysis Tools

• Data2Texture: Data2Texture is an advanced spatial data interpolation tool for estimating the distribution of sediment textures from airborne electromagnetic data and lithology logs to create a 3D texture model

• Data2HSM - Smart Interpretation: Data2HSM via Smart Interpretation (SI) is a semi-automatic Python tool for delineating continuous hydrogeologic surfaces from airborne electromagnetic data products.

• Data2HSM - Gaussian Mixture Model: The Data2HSM via Gaussian Mixture Model tool ingests the AEM data and groups the data into a user-specified number of clusters that are interpreted as stratigraphic units in the hydrostratigraphic model (HSM)

• Data2HSM - Geological Pseudolabel Deep Neural Network: The GeoPDNN (Geological Pseudolabel Deep Neural Network) is a semi-supervised machine learning tool that integrates lithologic well logs and AEM data into plausible stratigraphic surfaces.

• Texture2Par V2: Texture2Par V2 is a groundwater model pre-processor and parameterization utility developed to work with the IWFM and MODFLOW families of hydrologic simulation code.

Process Documents

• Aquifer Recharge Potential Mapping: The Aquifer Recharge Potential (ARP) Mapping Process Document provides a framework for identifying locations that have relatively higher potential for managed aquifer recharge.

Data Visualization

Data access equity is a priority for the Basin Characterization Program. To ensure data access equity, the Basin Characterization Program has developed applications and tools to allow data to be visualized without needing access to expensive data visualization software. This list below provides links and descriptions for the Basin Characterization's suite of data viewers.

SGMA Data Viewer: Basin Characterization tab: Provides maps, depth slices, and profiles of Basin Characterization maps, models, and datasets, including the following:

• Aquifer Recharge Potential Maps
• Subsurface Texture Model Depth Slices
• Statewide AEM Survey Texture Depth Slices
• Lithology Log Location Maps
• Geophysical Logs Location Maps
• Statewide AEM Survey Profile Images

3D AEM Data Viewer: Displays the Statewide AEM Survey electrical resistivity and coarse fraction data,

Kaweah Subbasin in the Central Valley of California is one of the over-drafted water basins. Over-pumping of groundwater resources due to the latest droughts and the high level of water demand to support agricultural activities threatens the water security of the region. Developing management practices to use groundwater resources in a sustainable way is urgent and important. However, without seeing under the ground where groundwater is stored and flows, it is not possible to pursue sustainable groundwater management. Traditionally, well-based approaches have been used for this imaging purpose. While these approaches provide accurate point information about hydrogeology of the subsurface, low spatial density and coverage of the wells result in a large data gap between the wells. Therefore, a new approach is needed to fill in this data gap for mapping out hydrogeology of the subsurface with high spatial density and coverage. This was the motivation of the acquisition of the AEM data covering Kaweah Subbasin. For this AEM experiment, SkyTEM 312 system was used; a total of 800 line-km AEM data was obtained. Acquired AEM data were processed by Aqua Geo Framework. Noisy data due to man-made noise sources (e.g., powerlines) were first omitted, then standard processing schemes (e.g., stacking, harmonic noise reduction, trapezoidal filtering) were applied using Aarhus Workbench Software. Provided AEM data in this repository are the processed AEM data, which is ready to be inverted to recover a resistivity distribution of the subsurface.

Airborne electromagnetic (AEM) and magnetic survey data were collected during October 2016 over a total distance of 262 line kilometers in the southeastern San Joaquin Valley near Cawelo, California. These data were collected in support of groundwater salinity mapping and hydrogeologic framework development as part of the U.S. Geological Survey California Oil, Gas, and Groundwater program and the California State Water Resources Control Board’s Oil and Gas Regional Monitoring Program. Deterministic spatially constrained inversions of the processed AEM data were conducted using the AarhusINV code (Auken and others, 2015) implemented in Aarhus Workbench software (Aarhus Geosoftware, Aarhus, Denmark). Inversion parameters were selected by running a series of test models with varying starting model resistivity values, layer discretization, horizontal/lateral constraints, and other inversion parameters. A 30-layer fixed-depth smooth inversion model was developed with layer top depths ranging between 4 and 400 meters and layer thickness increasing with depth. Inversions were run with vertical and lateral constraints of values of 2.0 and 1.6, respectively, and a 30 ohm-meter homogeneous half-space starting model. Sensor altitude was treated as a free parameter after the 5th iteration. Depth of investigation was calculated with a minimum and maximum depth of 5 and 500 meters. The data provided include inverted resistivity models along all flight lines. Digital data are described in the data dictionary, additional details regarding data inversion are described in the metadata processing steps.

This is the data and code release for the manuscript "From Resistivity to Hydraulic Properties: Calibrating a Groundwater Flow Model by Integrating Airborne Electromagnetic and Borehole Data into a Probabilistic Multi-Texture Framework" by Leland Scantlebury & Thomas Harter.

Manuscript Abstract: Airborne electromagnetic (AEM) surveys offer rapid, cost‑effective subsurface imaging, yet converting their electrical resistivity (ER) models into physically meaningful hydraulic property fields for groundwater models remains a challenge. We develop and demonstrate a data‑driven workflow for an unconsolidated sedimentary aquifer system in Scott Valley, northern California, USA, that incorporates AEM ER data with borehole logs to build and calibrate a heterogeneous groundwater-surface water model. ER and texture observations are first combined through consensus clustering into five meta‑texture classes; log‑normal ER-texture distributions derived with the Knight et al. (2018) method then transform the ER data to cell‑scale texture probabilities. These probabilities and borehole data are combined using Texture2Par to create a three‑dimensional texture model, which is translated to grid-scale hydraulic conductivity and storage via power‑law averaging. During calibration, we parameterized the ER-texture distributions, essentially allowing parameter estimation to adjust the estimated textures along the AEM flight lines. The texture‑based groundwater-surface water model attains the same high goodness‑of‑fit as the previous zonal calibration (Fort Jones streamflow NSE = 0.84; GW heads r2 = 0.98), with more geologically plausible heterogeneity and improved simulation of groundwater-driven seasonally low streamflow. The proposed ER‑to‑texture workflow provides an adaptable workflow for embedding AEM information into basin‑scale groundwater models.

Airborne electromagnetic (AEM) and magnetic survey data were collected during November 2017 over a total distance of 1,980 line kilometers in the southwestern San Joaquin Valley of California adjacent to the Elk Hills, North and South Coles Levee, and Buena Vista oil fields. These data were collected in support of groundwater salinity mapping and hydrogeologic framework development as part of the U.S. Geological Survey California Oil, Gas, and Groundwater program and the California State Water Resources Control Board’s Oil and Gas Regional Monitoring Program. Data were acquired by SkyTEM ApS with the SkyTEM 312 time-domain helicopter-borne electromagnetic system together with a Geometrics G822A cesium vapor magnetometer. The survey was flown at a nominal flight height of 35 m above terrain along block-style lines with a nominal spacing of 300 m. The AEM typical maximum depth of investigation is between 150 and 300 m. This data release includes minimally processed (raw) AEM and ra ...

Airborne electromagnetic (AEM) and magnetic survey data were collected during November 2018 over a total distance of 1,480 line kilometers in the Maricopa Flats and surrounding areas of southwestern San Joaquin Valley of California adjacent to the Buena Vista, Midway Sunset, Yowlumne, Los Lobos, Pioneer, Landslide, San Emidio Nose, Rio Viejo, and White Wolf oil fields. These data were collected in support of groundwater salinity mapping and hydrogeologic framework development as part of the U.S. Geological Survey California Oil, Gas, and Groundwater program and the California State Water Resources Control Board’s Oil and Gas Regional Monitoring Program. Data were acquired by SkyTEM ApS with the SkyTEM 312 time-domain helicopter-borne electromagnetic system together with a Geometrics G822A cesium vapor magnetometer. The survey was flown at a nominal flight height of 35 m above terrain along block-style lines with a nominal spacing of 300 m. The AEM typical maximum depth of investigation is between 150 and 350 m. This data release includes minimally processed (raw) AEM and raw/processed magnetic data, fully processed AEM data used for resistivity model development, and laterally constrained inverted resistivity models. The complete data package received from the contractor is included in separate zip-file directory and described in the contractor's report.

Airborne electromagnetic (AEM) and magnetic survey data were collected during October 2016 along 1,443 line kilometers in the southwestern San Joaquin Valley near Lost Hills, California. These data were collected in support of groundwater salinity mapping and hydrogeologic framework development as part of the U.S. Geological Survey California Oil, Gas, and Groundwater program and the California State Water Resources Control Board’s Program of Regional Monitoring of Water Quality in Areas of Oil and Gas Production. Deterministic laterally constrained inversions of the processed airborne electromagnetic data (https://www.sciencebase.gov/catalog/item/5d60373ae4b01d82ce9854ec) were developed using the AarhusINV code (Auken et al. 2014, https://doi.org/10.1071/EG13097) implemented in Aarhus Workbench software (v. 5.6.3.0, Aarhus Geosoftware, Aarhus, Denmark). Inversion parameters were selected by running a series of test models with varying starting model resistivity values, layer discretization, horizontal/lateral constraints, and other inversion parameters. A smooth 30-layer fixed-depth inversion model was developed with layer top depths ranging between 3 and 400 meters and layer thickness increasing with depth (see model data for exact thicknesses). Relatively weak vertical and lateral constraints on resistivity were used with values of 2.5 and 2.0, respectively. A 30 ohm-meter homogenous half-space starting model was used. Sensor altitude was treated as a free parameter after the 5th iteration. The final model parameters described above were selected because they best represented the physical understanding of the system and minimized data misfit.
The data provided include laterally-constrained inverted resistivity models and plotted depth sections along all flight lines. Digital data are described in the data dictionary, additional details regarding data inversion are described in the metadata processing steps

Airborne electromagnetic (AEM) and magnetic survey data were collected from December 2022 through March 2023 over a distance of 11,079 line kilometers in western Nevada and eastern California; central Nevada; and northern Nevada and southeastern Oregon. These data were collected in support of the U.S. Geological Survey (USGS) Earth Mapping Resources Initiative (Earth MRI), which aims to improve knowledge of the geologic framework of the United States through new geological and geophysical mapping and to identify areas that may have the potential to contain critical mineral resources. Data were acquired by XCalibur Multiphysics with the HELITEM² time-domain helicopter-borne electromagnetic system together with the CS-3 Scintrex Cesium Vapour magnetometer. The survey was acquired at a nominal flight height of 35 meters (m) above terrain and an average height of 80 - 85 meters. AEM data were processed and inverted to produce models of electrical resistivity along flight paths, with t ...

Phyllosilicates occurring as replacements of olivine, clinopyroxene and interstitial materials and as veins or fracture-fillings in hydrothermally altered basalts from DSDP Hole 504B, Leg 83 have been studied using transmission and analytical electron microscopy. The parageneses of phyllosilicates generally change systematically with depth and with the degree of alteration, which in turn is related to permeability of basalts. Saponite and some mixed-layer chlorite/smectite are the dominant phyllosilicates at the top of the transition zone. Chlorite, corrensite, and mixed-layer chlorite/corrensite occur mainly in the lower transition zone and upper levels of the sheeted dike zone. Chlorite, talc, and mixed-layer talc/chlorite are the major phyllosilicates in the sheeted dike zone, although replacement of talc or olivine by saponite is observed. The phyllosilicates consist of parallel or subparallel discrete packets of coherent layers with packet thicknesses generally ranging from < 100 A to a few hundred A. The packets of saponite layers are much smaller or less well defined than those of chlorite, corrensite and talc, indicating poorer crystallinity of saponite. By contrast, chlorite and talc from the lower transition zone and the sheeted dike zone occur in packets up to thousands of A thick. The Si/(Si + A1) ratio of these trioctahedral phyllosilicates increases and Fe/(Fe + Mg) decreases in the order chlorite, corrensite, saponite, and talc. These relations reflect optimal solid solution consistent with minimum misfit of articulated octahedral and tetrahedral sheets. Variations in composition of hydrothermal fluids and precursor minerals, especially in Si/(Si+A1) and Fe/(Fe+Mg) ratios, are thus important factors in controlling the parageneses of phyllosilicates. The phyllosilicates are generally well crystallized discrete phases, rather than mixed-layered phases, where they have been affected by relatively high fluid/rock ratios as in high-permeability basalts, in veins, or areas adjacent to veins. Intense alteration in basalts with high permeability (indicating high fluid/rock ratios) is characterized by pervasive albitization and zeolitization. Minimal alteration in the basalts without significant albitization and zeolitization is characterized by the occurrence of saponite ± mixed-layer chlorite/smectite in the low-temperature alteration zone, and mixed-layer chlorite/corrensite or mixed-layer talc/chlorite in the high-temperature alteration zone. Textural non-equilibrium for phyllosilicates is represented by mixed layering and poorly defined packets of partially incoherent layers. The approach to textural equilibrium was controlled largely by the availability of fluid or permeability.

The Quartz Valley Geologic Framework uses geologic data gathered from previous publications (Mack, 1958) and airborne electromagnetic (AEM) surveys (California Department of Water Resources, 2024) in conjunction with the well log database presented in this data release to create an understanding of the extents and thicknesses of geologic units including channel alluvium, alluvium and basement. Geologic maps and cross sections were taken from a Geological Survey water supply paper (Mack, 1958) to determine surface geologic contacts and general depth to basement material in the valley. Well Completion Reports and AEM data from the California Department of Water Resources (California Department of Water Resources, 2023, 2024) provided lithologic information that was used to determine depth to basement. The well log database includes lithology, well location, depths, construction information, and water levels. These data were interpolated to create the top of basement across the model grid using the three-dimensional modeling program Rockworks, and its inverse distance algorithm for creating grid surfaces. Channel alluvium was added on top of the alluvium layer where current rivers, creeks and ditches are in the valley to be able to add more hydrologic details to the groundwater flow model. This data release includes a shapefile of a grid that defines the extent and thicknesses of the three hydrogeologic layers.

This dataset contains summarized historical groundwater salinity observations from wells near the Lost Hills and Belridge oil fields in the southwestern San Joaquin Valley, Kern County, California. Total dissolved solids (TDS) concentration, electrical fluid conductivity (EC), and well construction information were aggregated from public data sources and local water management agencies. Trends in total-dissolved solids (TDS) concentrations and fluid conductivity were assessed on a well-by-well basis to develop a dataset of salinity observations to support the interpretation of resistivity data derived from an airborne electromagnetic (AEM) survey flown in October 2016. Results of the trend analysis were used to identify wells that were stable with respect to three salinity categories between 2004 and 2014: fresh (TDS less than 3000 mg/L), brackish (TDS between 3,000 and 10,000 mg/L), and saline (TDS greater than 10,000 mg/L). Salinity observations considered to be contemporary with respect to the AEM survey (2015-2018) are also included in this dataset.

Borehole lithology data from drillers' log descriptions were compiled for the Salton Sea area and vicinity. This data will be utilized to support hydrogeologic and hydrologic investigations. Data for some parts of the Salton Sea Watershed were already compiled for other USGS reports. These included Borrego Valley (Faunt and others, 2015), and the East Mesa (Shepherd and Rosenberg, 2024). For the parts of the watershed that were not already covered by a USGS report, wells were sourced from the California Department of Water Resources Online Well Completion Reports (California Department of Water Resources, 2024), a consultant report on in-sea geotechnical wells (URS, 2004), the California Natural Resources Agency DWR Airborne Electromagnetic (AEM) survey area 11 (California Natural Resources Agency, 2024), and California Department of Conservation Geological Energy Management Division (California Department of Conservation, 2024).

Servicio de mantenimiento de ascensores, montacargas y salva escaleras en la Dirección Provincial TGSS y centros dependientes, según ITC AEM 1 Ascensores. Cinco centros, 18 aparatos, 1 salva escalera