Turbidity Model for Ashokan Reservoir, New York: Case Study

摘要

Terrigenous inorganic particles delivered during runoff events cause problems of high turbidity in many lakes and reservoirs. A turbidity model, composed of a two-dimensional hydrothermal/transport submodel and a turbidity submodel, is developed and tested for Ashokan Reservoir, New York, that experiences elevated turbidity levels following runoff events. A robotic monitoring network, rapid profiling instrumentation, and individual particle analyses are used to support the modeling, by specifying turbidity loads and in-reservoir patterns and features of the particles that guided representation of settling. The turbidity-causing particles are clay minerals, 1–10 μm in diameter. The hydrothermal/transport submodel that serves as the physical framework for the overall model, was separately validated for a 13-year period. The turbidity submodel considered three particle-size/settling velocity classes of turbidity, consistent with the independent individual particle characterizations. Robust performance is demonstrated for the overall turbidity model, as it simulates well the wide range of patterns observed in the reservoir and withdrawal, associated with a number of major runoff events from the same 13-year period. The model will be used to support forecasting in the evaluation of management alternatives intended to abate the problem.