Rainfall-runoff models have become essential tools for conceptualizing and predicting the response of hydrologic processes to changing environments, but they have rarely been applied to challenges facing health scientists. Yet with their efficient parameterization and modest data requirements, they hold great promise for epidemiological application. A modeling analysis incorporating simple hydrologic constraints on transmission of the human parasite Schistosoma japonicum in southwestern China was conducted by coupling a lumped parameter rainfall-runoff model (IHACRES) with a delay-differential equation schistosomiasis transmission model modified to account for channel flows and on-field egg inactivation. Model predictions of prevalence and infection timing agree with observations in the region, which indicate that hydrological differences between sites can lead to pronounced differences in transmission. Channel flows are shown to be important in determining infection intensity and timing in modeled village populations. In the periodic absence of flow, overall transmission intensity is reduced among all modeled risk groups. However, the influence of hydrologic variability was greater on the cercarial stage of the parasite than the miracidial stage, due to the parasite ova's ability to survive dormant on fields between rain events. The predictive power gained from including hydrological data in epidemiological models can improve risk assessments for environmentally mediated diseases, under both long-term climate change scenarios and near-term weather fluctuations.