This data release documents time-series analyses of aqueous-chemistry data from public-supply wells (PSWs) and associated potential explanatory factors to characterize responses of groundwater quality to drought and recovery periods in California’s San Joaquin Valley (SJV) during 2000-2022. Annual median nitrate values were computed for PSWs throughout the SJV during the period of study. Median annual nitrate values were calculated at all PSWs with available data in the SJV, resulting in a total of 698 PSWs with complete annual records after single-year linear gap imputation. A total of 237 of these records were classified as “low variance” because they contained proportions of identical values exceeding 80 percent or had standard deviations less than the study reporting level of 0.452 milligram of nitrate as nitrogen per liter. Annual nitrate anomalies were computed for the 461 remaining nitrate records not classified as “low variance” by detrending using the Hodrick-Prescott filter and z-score standardizing resultant values by subtracting the mean and dividing by the standard deviation. Resultant time series of nitrate anomalies were clustered into two groups sharing similar time-series characteristics quantified by the nonparametric correlation coefficient, Spearman’s rho. Potential explanatory factors based on time-series characteristics or extrinsic factors used in prior studies to characterize groundwater nitrate concentrations in the SJV were compiled to help explain differences among cluster groups. Additionally, concentration changes for nitrate, total dissolved solids (TDS), arsenic, and fluoride in the regulatory monitoring dataset were computed for two selected hydrologic stress periods representative of an historic drought (Dsp; 2012-2016) and subsequent recovery period (Rsp; 2016-2019). Change values were computed by differencing the annual median concentration of the last year with available data in a given stress period with that of the first, including the year before the onset of the stress period to compare with antecedent conditions when possible.