Estimating environmental conditions affecting protozoal pathogen removal in surface water wetland systems using a multi-scale, model-based approach

Autor: Melissa A. Miller, Patricia A. Conrad, Clare Dominik, Woutrina A. Smith, Jennifer N. Hogan, Miles E. Daniels, Karen Shapiro, Marc Los Huertos, Fred G.R. Watson, Stori C. Oates, Dane Hardin
Rok vydání: 2014
Předmět:
Zdroj: Science of The Total Environment. 493:1036-1046
ISSN: 0048-9697
Popis: Cryptosporidium parvum, Giardia lamblia, and Toxoplasma gondii are waterborne protozoal pathogens distributed worldwide and empirical evidence suggests that wetlands reduce the concentrations of these pathogens under certain environmental conditions. The goal of this study was to evaluate how protozoal removal in surface water is affected by the water temperature, turbidity, salinity, and vegetation cover of wetlands in the Monterey Bay region of California. To examine how protozoal removal was affected by these environmental factors, we conducted observational experiments at three primary spatial scales: settling columns, recirculating wetland mesocosm tanks, and an experimental research wetland (Molera Wetland). Simultaneously, we developed a protozoal transport model for surface water to simulate the settling columns, the mesocosm tanks, and the Molera Wetland. With a high degree of uncertainty expected in the model predictions and field observations, we developed the model within a Bayesian statistical framework. We found protozoal removal increased when water flowed through vegetation, and with higher levels of turbidity, salinity, and temperature. Protozoal removal in surface water was maximized (~0.1 hour(-1)) when flowing through emergent vegetation at 2% cover, and with a vegetation contact time of ~30 minutes compared to the effects of temperature, salinity, and turbidity. Our studies revealed that an increase in vegetated wetland area, with water moving through vegetation, would likely improve regional water quality through the reduction of fecal protozoal pathogen loads.
Databáze: OpenAIRE