W-11-7 Design of Critical Cases for the Application of Calibrated Thermal Models: A Key Part of the Modeling Process

Wednesday, August 22, 2012: 9:30 AM
Meeting Room 11 (RiverCentre)
Mark Gerath , Water Resources, AECOM Environment, Chelmsford, MA
Several factors have lead to an increase in the application of sophisticated thermal models of aquatic systems.   In particular, modeling and monitoring technology have improved so that development and application of sophisticated, time-varying, and three-dimensional models has become more routine.   Following model calibration and validation to field data, the definition of hypothetical “future” or design case, including quasi-“worst” cases for permitting, requires careful consideration.    For example, while regulatory guidance on dilution flows and other factors are available for permitting of toxic constituents in wastewater, there is far less consensus on the approach to the regulatory assessment of thermal loadings.     This is particularly important in systems in which several, partially-related parameters (e.g., cloud cover, relative humidity, wind speed and direction, current structure) affect the heat budget of the receiving water.  The issue is complicated by the fact that, unlike the standards for toxic parameters, standards for temperature generally do not have an “allowable” frequency and duration of exceedence.  The lack of clear regulatory guidance and the complicated nature of thermal aquatic systems require innovative approaches to defining and defending the selected worst-case scenarios. The primary innovation of the proposed solutions is the movement away from evaluating the statistical range of individual boundary conditions and towards the evaluating the statistical range of influence from thermal loading.  This change in approach leverages the dropping cost of computation time to compensate for the difficulty of pairing, and systematically varying, related boundary conditions. Two cases studies will provide illustration of the issues and potential solutions as well as the anticipated challenges in using probabilistic assessments to meet regulatory requirements.