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Groundwater nitrate contamination in the Central Valley (CV) aquifer of California is a ubiquitous groundwater problem found in various parts of the valley. Heavy irrigation and application of fertilizer over the last several decades have caused groundwater nitrate contamination in several domestic, public and monitoring wells in the CV above EPA’s Maximum Contamination level of 10 mg/L. Source variables, aquifer susceptibility and geochemical variables could affect the contamination rate and groundwater quality in the aquifer. A comparative study was conducted using Geodetector (GED), Principal Component Analysis (PCA) and Geographically Weighted Regression (GWR) to observe which method is most effective at revealing environmental variables that control groundwater nitrate concentration. The GED method detected precipitation, fertilizer, elevation, manure and clay as statistically significant variables. Watersheds with percent of wells above 5 mg/L of nitrate were higher in San Joaquin and Tulare Basin compared to Sacramento Valley. PCA grouped cropland, fertilizer, manure and precipitation as a first principal component, suggesting similar construct of these variables and existence of data redundancy. The GWR model performed better than the OLS model, with lower corrected Akaike Information Criterion (AIC) values, and captured the spatial heterogeneity of fertilizer, precipitation and elevation for the percent of wells above 5 mg/L in the CV. Overall, the GED method was more effective than the PCA and GWR methods in determining the influence of explanatory variables on groundwater nitrate contamination

isprs international journal of geo-information

Analysis of Groundwater Nitrate Contamination in the Central Valley: Comparison of the Geodetector Method, Principal Component Analysis and Geographically Weighted Regression