Abstract #T208

# T208
Checks and balances: Evaluating reliability of dairy nutrient management data to better protect groundwater resources.
Christine Miller*1, Deanne Meyer1, 1University of California, Davis, Davis, CA.

To protect groundwater from further nitrate contamination, California regulations prohibit dairy producers from applying more than 140% of the nitrogen (N) that their crops remove. The regulations require copious annual reporting of crop field management, farm infrastructure, and animal population. The data collected in these annual reports could be integral to evaluating and improving both farm practices and the regulations themselves. Data reliability and accuracy must be assessed to use the information responsibly. Annual Reports from 18 dairies were obtained to assess reliability. Mass balance calculations were preformed to check the self-consistency of data within a facility. The results of mass balance calculations show that the data do not account for a remarkably large percentage of the nutrients being produced on the farms. Literature suggests that over 60% of N and 90% of P should be recovered; however, a median of only 25% of both N and P in cattle manure was recovered based on annual report data. This could be due to many different causes including inaccurate nitrogen sampling and analysis techniques, systematic reporting errors, or fraudulent reporting. Given that the accuracy of the majority of the recommended sampling and analysis protocols has not been assessed, it is likely that these methods are a significant source of error. Projects that should improve data collection protocols in both the short and long-term are in progress. Online decision trees are being developed to help farmers self-assess their current data collection practices, and provide personalized suggestions for improvement. Additionally, I will use a statistical modeling approach paired with in-field measurements to examine the uncertainty in these recommended protocols (and thereby the overall uncertainty in regulations). By separating the various sources of measurement error, the model will identify the best ways to improve data collection and regulation efficacy. Results of this and future studies will influence future nutrient management regulations in California and other states with active livestock industries.

Key Words: dairy waste management, nitrate leaching