Applying Process-Based Models for Subsurface Flow Treatment Wetlands: Recent Developments and Challenges
AbstractTo date, only few process-based models for subsurface flow treatment wetlands have been developed. For modelling a treatment wetland, these models have to comprise a number of sub-models to describe water flow, pollutant transport, pollutant transformation and degradation, effects of wetland plants, and transport and deposition of suspended particulate matter. The two most advanced models are the HYDRUS Wetland Module and BIO-PORE. These two models are briefly described. This paper shows typical simulation results for vertical flow wetlands and discusses experiences and challenges using process-based wetland models in relation to the sub-models describing the most important wetland processes. It can be demonstrated that existing simulation tools can be applied for simulating processes in treatment wetlands. Most important for achieving a good match between measured and simulated pollutant concentrations is a good calibration of the water flow and transport models. Only after these calibrations have been made and the effect of the influent fractionation on simulation results has been considered, should changing the parameters of the biokinetic models be taken into account. Modelling the effects of wetland plants is possible and has to be considered when important. Up to now, models describing clogging are the least established models among the sub-models required for a complete wetland model and thus further development and research is required. View Full-Text
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Langergraber, G. Applying Process-Based Models for Subsurface Flow Treatment Wetlands: Recent Developments and Challenges. Water 2017, 9, 5.
Langergraber G. Applying Process-Based Models for Subsurface Flow Treatment Wetlands: Recent Developments and Challenges. Water. 2017; 9(1):5.Chicago/Turabian Style
Langergraber, Guenter. 2017. "Applying Process-Based Models for Subsurface Flow Treatment Wetlands: Recent Developments and Challenges." Water 9, no. 1: 5.
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