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MODIFICATIONS OF WASP FOR SIMULATING PERIPHYTON DYNAMICS
Citation:
Wool, T. A., R B. Ambrose Jr., J. L. Martin, S. Davie, AND W. Anderson. MODIFICATIONS OF WASP FOR SIMULATING PERIPHYTON DYNAMICS. Presented at Total Maximum Daily Load 2003, Chicago, IL, November 16-18, 2003.
Impact/Purpose:
Improve the scientific understanding of the processes controlling nutrient distributions in surface waters. Produce a suite of enhanced models for characterizing nutrient distributions in surface waters by incorporating improved process understanding in existing models (e.g., WASP), by developing new models (e.g., WHAM, reactive transport), and improving linkages between model components.
Description:
Conventional water quality models that are in current use today for the development of TMDLs and waste load allocations usually use dissolved oxygen, nutrient concentrations and algal growth as indicators to water health. In shallow streams and rivers, water health can be controlled by presence of fixed plants, such as macrophytes to periphyton. As water resource managers and regulators develop nutrient management strategies for these waterbodies it becomes difficult to determine what types of nutrient controls need to be put in place to control the presence, abundance and influence of periphyton on water quality. This paper looks at the process of adding periphyton algorithms to the Water Quality Analysis Simulation Program (WASP). The Water Quality Analysis Simulation Program- (WASP6), an enhancement of the original WASP (DiToro et al., 1983; Connolly and Winfield, 1984; Ambrose, R.B. et al., 1988). This model helps users interpret and predict water quality responses to natural phenomena and man made pollution for various pollution management decisions. WASP is a dynamic compartment-modeling program for aquatic systems, including both the water column and the underlying benthos. The time varying processes of advection, dispersion, point and diffuse mass loading, and boundary exchange are represented in the basic program. The paper will discuss the selection and development process for the periphyton routines and how they are incorporated into the model. A discussion will be presented on the type of data that will be required to use the algorithms in a modeling study. Finally, a series of case studies will be presented to illustrate the impact of considering periphyton in a modeling study and how it translates into point and nonpoint source load allocations in nutrient TMDLs