Forecasting Stormwater Pond Dry-Weather Water Temperature Profiles Using the Group Method of Data Handling

One of the unintended consequences of stormwater management ponds is the thermal enrichment of the shallow pond water during the summer months. The warm outflow ponds can degrade the cold and cool water aquatic habitat in urban streams. The current tools available to predict pond temperature are process based and rely on numerical methods to solve the heat exchange. This paper presents a novel method to compute the temperature profiles of stormwater management ponds during dry weather warming periods. First, a new shallow thermocline equation was fitted to temperature data (daily minimum and maximum) from stormwater ponds monitored in the Greater Toronto Area. The Group Method of Data Handling method was then used to develop models for the 6 equation parameters using commonly available climatic data and pond characteristics. The model can replicate the thermal profiles under summer, fall and winter conditions for the case study ponds ranging in depths between 2 and 3 meters. Links between diurnal, seasonal and short-term temperature trends and the model parameters were observed. This new equation provides easy-to-explain mathematical equations that describe the heating and cooling process in the pond. Important metrics are obtained from the curves, such as average pond temperature, total thermal energy, net energy gain and the depth of penetration of nighttime cooling. This model has the potential to aid stormwater pond designers in predicting thermal loading to sensitive aquatic habitat using commonly-available climatic records, while avoiding the requirements of continuous simulation of complex numerical models.