Probabilistic groundwater salinity mapping results of the southwestern San Joaquin Valley derived from airborne electromagnetic and groundwater salinity data

This data release contains the results of three-dimensional, probabilistic, categorical groundwater salinity mapping of the alluvial and Tulare aquifers near areas of oil and gas development in the southwestern San Joaquin Valley of California. These results were derived from airborne electromagnetic (AEM) survey data collected between 2016 and 2018 in areas hydrogeologically downgradient of intensive oil-field infrastructure (Ball 2020; Ball, Zamudio, and Hoogenboom, 2024; Ball, Hoogenboom, and Zamudio, 2024). Probabilistic inversions of the AEM data were used to define spatially variable resistivity probability density functions (pdfs) using the geophysical inversion code Geophysical Bayesian Inference in Python (GeoBIPy, Foks and Minsley, 2020). TDS observations and well construction information were aggregated from public data sources and provided in WestsideAEMSalinityMapping_WellData.csv and used to define the interpretational relations between resistivity and groundwater salinity. WestsideAEMSalinityMapping_CategoricalProbability.csv contains marginal probabilities of the occurrence of three salinity categories given the geophysical data and interpretational relations: fresh (total dissolved solids (TDS) concentration less than 3,000 mg/L), brackish (TDS between 3,000 and 10,000 mg/L), and saline (TDS greater than 10,000 mg/L). The methods associated with this salinity mapping approach are described in detail by Ball and others (2020) and Ball and others (2026).

References cited:
Ball, L.B., 2020, Airborne Electromagnetic and Magnetic Survey Data, San Joaquin Valley near Lost Hills, California, October 2016: U.S. Geological Survey data release, https://doi.org/10.5066/F7G44PKR.
Ball, L.B., Davis, T.A., Minsley, B.J., Gillespie, J.M., and Landon. M.K., 2020, Probabilistic Categorical Groundwater Salinity Mapping from Airborne Electromagnetic Data Adjacent to California’s Lost Hills and Belridge Oil Fields: Water Resources Research, 56, no. 6, https://doi.org/10.1029/2019WR026273.
Ball, L.B., Hoogenboom, B.E., and Zamudio, K.D., 2024, Airborne Electromagnetic and Magnetic Survey Data, Southwestern San Joaquin Valley near Maricopa, California, 2018: U.S. Geological Survey data release, https://doi.org/10.5066/P9R1XBPG.
Ball, L.B., Zamudio, K.D., and Hoogenboom, B.E., 2024, Airborne Electromagnetic and Magnetic Survey Data, Southwestern San Joaquin Valley near Elk Hills, California, 2017: U.S. Geological Survey data release, https://doi.org/10.5066/P9LFGESW.
Ball, L.B., Foks, N.L., Davis, T.A., Warden, J.W., Gannon, R.S., Gillespie, J.M., and Landon, M.K., 2026, Regional and local controls on groundwater salinity in California’s southwestern San Joaquin Valley: insights from airborne electromagnetic surveys. Hydrogeology Journal. https://doi.org/10.1007/s10040-026-03057-8.
Foks,N.L. and Minsley,B.J., 2020, Geophysical Bayesian Inference in Python (GeoBIPy): U.S. Geological Survey software, https://doi.org/10.5066/P9K3YH9O.