Survival and Release of Animal Waste-Borne E. Coli in Field Conditions.

Field- and farm-scale estimates of E. coli loads to surface water sources are needed to evaluate management decisions affecting microbiological quality of irrigation and recreation waters. This work reports initial steps of the development of bacteria survival subroutine for the USDA-ARS-supported APEX model. Recently models of bacteria survival have been proposed and results of experiments to test these models have been published by various research groups. The objective of this work is to augment our experimental results with data from other sources to assess the applicability of the models and variability of parameters of those models. Experiments on survival of E. coli from bovine animal waste of different types are being carried in Beltsville Agricultural Research Center. We also utilize available data from experiments in Australia, New Zealand and Virginia.

The modified Arrhenius model presents a viable tool to normalize inactivation data obtained at different temperature regimes converting the original times into thermal times. E.coli populations in manure and non-altered cowpats remained quite constant during the first period of thermal time. In contrast, data of cowpats from NZ and VA that were rebuilt after collection and before their application in the field showed either an initial growth when they were applied during warm seasons or initial decay during colder seasons. Die-off using the thermal time, when it occurred, had the same rate independently of the origin of the data with a value of 0.037 thermal units^-1. Intercepts were different for different seasons, but were very similar independently of the original dataset. Resources availability could be a reason to the switch between initial maintenance, growth and die-off. Stable bacteria population use resources but not grow, and can exhaust the resources in that way. The growth period appears to be source of uncertainty in field- and watershed scale modeling. These different dynamics were successfully modeled using a modified version of the Monod equation assuming different dependences of the E.coli population growth on substrate concentration. This work will continue with the aim of providing the reliable module for field, farm, and watershed scale modeling of microbiological surface water quality.