Agricultural nonpoint pollution is inherently stochastic (e.g., due to weather). In theory, this randomness has implications for the choice and design of policy instruments. However, very few empirical studies have modeled natural variability. This paper investigates the importance of stochastic processes for the choice and design of alternative nonpoint instruments. The findings suggest that not explicitly considering the stochastic processes in the analysis can produce significantly biased results.