Oil and gas development generates large amounts of wastewater (i.e., produced water), which in California has been partially disposed of in unlined percolation/evaporation ponds since the mid-20th century. Although produced water is known to contain multiple environmental contaminants (e.g., radium and trace metals), prior to 2015, detailed chemical characterizations of pondwaters were the exception rather than the norm. Using a state-run database, we synthesized samples (n = 1688) collected from produced water ponds within the southern San Joaquin Valley of California, one of the most productive agricultural regions in the world, to examine regional trends in pondwater arsenic and selenium concentrations. We filled crucial knowledge gaps resulting from historical pondwater monitoring by constructing random forest regression models using commonly measured analytes (boron, chloride, and total dissolved solids) and geospatial data (e.g., soil physiochemical data) to predict arsenic and selenium concentrations in historical samples. Our analysis suggests that both arsenic and selenium levels are elevated in pondwaters and thus this disposal practice may have contributed substantial amounts of arsenic and selenium to aquifers having beneficial uses. We further use our models to identify areas where additional monitoring infrastructure would better constrain the extent of legacy contamination and potential threats to groundwater quality.
Keywords: San Joaquin valley; arsenic; oil & gas; produced water; random forest modeling; selenium.