Bayesian Nitrate Source Apportionment to Individual Groundwater Wells in the Central Valley by use of Nitrogen, Oxygen, and Boron Isotopic Tracers

Monday, 15 December 2014
Katherine Lockhart1, Thomas Harter1, Mark Grote1, Megan B Young2, Gary Eppich3, Amanda Deinhart4, Josh Wimpenny1 and Qing-Zhu Yin1, (1)University of California Davis, Davis, CA, United States, (2)USGS California Water Science Center Menlo Park, Menlo Park, CA, United States, (3)Lawrence Livermore National Laboratory, Livermore, CA, United States, (4)California State University East Bay, Hayward, CA, United States
Groundwater quality is a concern in alluvial aquifers underlying agricultural areas worldwide, an example of which is the San Joaquin Valley, California. Nitrate from land applied fertilizers or from animal waste can leach to groundwater and contaminate drinking water resources. Dairy manure and synthetic fertilizers are the major sources of nitrate in groundwater in the San Joaquin Valley, however, septic waste can be a major source in some areas. As in other such regions around the world, the rural population in the San Joaquin Valley relies almost exclusively on shallow domestic wells (≤150 m deep), of which many have been affected by nitrate. Consumption of water containing nitrate above the drinking water limit has been linked to major health effects including low blood oxygen in infants and certain cancers. Knowledge of the proportion of each of the three main nitrate sources (manure, synthetic fertilizer, and septic waste) contributing to individual well nitrate can aid future regulatory decisions. Nitrogen, oxygen, and boron isotopes can be used as tracers to differentiate between the three main nitrate sources. Mixing models quantify the proportional contributions of sources to a mixture by using the concentration of conservative tracers within each source as a source signature. Deterministic mixing models are common, but do not allow for variability in the tracer source concentration or overlap of tracer concentrations between sources. Bayesian statistics used in conjunction with mixing models can incorporate variability in the source signature. We developed a Bayesian mixing model on a pilot network of 32 private domestic wells in the San Joaquin Valley for which nitrate as well as nitrogen, oxygen, and boron isotopes were measured. Probability distributions for nitrogen, oxygen, and boron isotope source signatures for manure, fertilizer, and septic waste were compiled from the literature and from a previous groundwater monitoring project on several dairies in the San Joaquin Valley. Median percent contribution of nitrate to wells from fertilizer, manure, and septic waste generally match the expected source based on land use patterns, with some exceptions.