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.

Groundwater nitrate contamination of the aquifer in the Central Valley, California is a major problem due to intense agricultural practice over the last decades. Excessive loading of fertilizer and manure in combination with hydrogeological parameters and geochemical conditions have enhanced the downward percolation of nitrate into the aquifer. A spatial variance-based geographical detector method was used at the watershed scale in Central Valley to identify the key determinants to elevated nitrate concentration, locate the risk areas and analyse the interaction between these determinants. Statistically significant difference was observed in percent of wells with above background concentration (5mg/L) between the areas with low and high fertilizer application. Higher number of wells was also contaminated in areas with higher manure, higher permeability and higher dissolved oxygen conditions. These factors interacted with the hydrogeological parameters in exacerbating the groundwater nitrate contamination in the study area. A distinctly higher nitrate concentration was observed in Tulare basin and San Joaquin basin compared to Sacramento Valley, which could be attributed higher fertilizer rate, coarse grained sediment and over pumping of groundwater altering the hydrogeological conditions.

Groundwater nitrate contamination in the Central Valley (CV) aquifer of California is widespread throughout the valley because of excess nitrogen fertilizer leaching down into the aquifer. The percolation of nitrate depends on several hydrogeological conditions of the valley. Groundwater contamination vulnerability mapping uses hydrogeologic conditions to predict vulnerable areas. This paper presents a new Geodetector-based Frequency Ratio (GFR) method and an optimized-DRASTIC method to generate nitrate vulnerability index values for the CV. The optimized-DRASTIC method combined the individual weights and rating values for Depth to water, Recharge rate, Aquifer media, Soil media, Topography, Impact of vadose zone, and Hydraulic conductivity. The GFR method incorporated the Frequency-Ratio (FR) method to derive rating values and the Geodetector method to derive relative Power of Determinant (PD) values as weights to generate nitrate susceptibility index map. The optimized-DRASTIC method generated very-high to high index values in the eastern part of the CV. The GFR method showed very-high index values in most part of the San Joaquin and Tulare basin. The quantitatively derived rating values and weights in the GFR method improved the vulnerability index and showed better consistency with the observed nitrate contamination pattern than optimized-DRASTIC index, suggesting that GFR is a better method for groundwater contamination vulnerability mapping in the CV aquifer.

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