This paper provides a general statistical methodology for modeling environmental pathogen concentrations in natural waters. A hierarchical model of pathogen concentrations captures site and regional random effects as well as random laboratory recovery rates. Recovery rates were modeled by a generalized linear mixed model. Two classes of pathogen concentration models are differentiated according to their ultimate purpose: water quality prediction or health risk analysis. A fully Bayesian analysis using Markov chain Monte Carlo (MCMC) simulation is used for statistical inference. The applicability of this methodology is illustrated by the analysis of a national survey of Cryptosporidium parvum concentrations, in which 93% of the observations were zero counts.