Modelling dry-weather temperature profiles in urban stormwater management ponds

Abstract

One of the unintended consequences of urban stormwater quality management wet ponds is the thermal enrichment of the shallow pond water during the summer months. The outflow from thermally enriched ponds can degrade the cold and cool water aquatic habitat in urban streams. An accurate model of the pond temperature profile is needed to assess the pond effluent thermal load. However, most models developed for this purpose are process-based and not simple to use, requiring a lengthy monitoring dataset to calibrate. This paper introduces a new design/assessment tool to predict the hourly water temperatures in these ponds at different depths during the summer season dry-weather warming periods and the diurnal cycles. We compiled monitoring data from five ponds in the Greater Toronto Area from 2013 − 2016 to evaluate the ponds' thermal impact on the receiving cold water streams. Using these datasets, we developed a new equation that allows for separating the active upper portion and stable lower portion of the pond. This ensures the focus is on the active upper part, where the majority of the heat transfer within the pond occurs and exhibits diurnal temperature fluctuations. We also used machine-learning tools to develop accurate equations for the bottom temperature and surface temperature, as well as, key equation parameters that characterize the thermal profiles. The developed thermal profile equation allows for the simple determination of other key thermal metrics such as average temperature, energy stored, thermocline location, which may be used as inputs to model wet weather flow conditions and pond outflow temperature. The results show that the proposed machine-learning model is acceptably accurate and capable, according to the low mean absolute percentage error (MAPE) and coefficient of determination (R2) values of 5% and 0.965, respectively, for temperature prediction for all depths. This work provides a building block for the overall objective to develop a new, easy to use, wet weather explicit equation for predicting the outlet temperature from stormwater management wet ponds since it establishes the initial thermal condition before the storm hits.