Phosphorus (P) export from urban areas via stormwater runoff contributes to eutrophication of downstream aquatic ecosystems. Bioretention cells are a Low Impact Development (LID) technology promoted as a green solution to attenuate urban peak flow discharge, as well as the export of excess nutrients and other contaminants. Despite their rapidly growing implementation worldwide, a predictive understanding of the efficiency of bioretention cells in reducing urban P loadings remains limited. Here, we present a reaction-transport model to simulate the fate and transport of P in a bioretention cell facility in the greater Toronto metropolitan area. The model incorporates a representation of the biogeochemical reaction network that controls P cycling within the cell. We used the model as a diagnostic tool to determine the relative importance of processes immobilizing P in the bioretention cell. The model predictions were compared to multi-year observational data on 1) the outflow loads of total P (TP) and soluble reactive P (SRP) during the 2012-2017 period, 2) TP depth profiles collected at 4 time points during the 2012-2019 period, and 3) sequential chemical P extractions performed on core samples from the filter media layer obtained in 2019. Results indicate that exfiltration to underlying native soil was principally responsible for decreasing the surface water discharge from the bioretention cell (63 % runoff reduction). From 2012 to 2017, the cumulative outflow export loads of TP and SRP only accounted for 1 % and 2 % of the corresponding inflow loads, respectively, hence demonstrating the extremely high P reduction efficiency of this bioretention cell. Accumulation in the filter media layer was the predominant mechanism responsible for the reduction in P outflow loading (57 % retention of TP inflow load) followed by plant uptake (21 % TP retention). Of the P retained within the filter media layer, 48 % occurred in stable, 41 % in potentially mobilizable, and 11 % in easily mobilizable forms. There were no signs that the P retention capacity of the bioretention cell was approaching saturation after 7 years of operation. The reactive transport modeling approach developed here can in principle be transferred and adapted to fit other bioretention cell designs and hydrological regimes to estimate P surface loading reductions at a range of temporal scales, from a single precipitation event to long-term (i.e., multi-year) operation.

Lake Wilcox (LW), a shallow kettle lake located in southern Ontario, has experienced multiple phases of land use change associated with human settlement and residential development in its watershed since the early 1900s. Urban growth has coincided with water quality deterioration, including the occurrence of algal blooms and depletion of dissolved oxygen (DO) in the water column. We analyzed 22 years of water chemistry, land use, and climate data (1996-2018) using principal component analysis (PCA) and multiple linear regression (MLR) to identify the contributions of climate, urbanization, and nutrient loading to the changes in water chemistry. Variations in water column stratification, phosphorus (P) speciation, and chl-a (as a proxy for algal abundance) explain 76 % of the observed temporal trends of the four main PCA components derived from water chemistry data. MLR results further imply that the intensity of stratification, quantified by the Brunt-Väisälä frequency, is a major predictor of the changes in water quality. Other important factors explaining the variations in nitrogen (N) and P speciation, and the DO concentrations, are watershed imperviousness and lake chloride concentrations that, in turn, are closely correlated. We conclude that the observed in-lake water quality trends over the past two decades are linked to urbanization via increased salinization associated with expanding impervious land cover, rather than increasing external P loading. The rising salinity promotes water column stratification, which reduces the oxygenation of the hypolimnion and enhances internal P loading to the water column. Thus, stricter controls on the application and runoff of de-icing salt should be considered as part of managing eutrophication symptoms in lakes of cold climate regions.

Hydrologic models partition flows into surface and subsurface pathways, but their calibration is typically conducted only against streamflow. Here we argue that unless model outcomes are constrained using flow pathway data, multiple partitioning schemes can lead to the same streamflow. This point becomes critical for biogeochemical modeling as individual flow paths may yield unique chemical signatures. We show how information on flow pathways can be used to constrain hydrologic flow partitioning and how improved partitioning can lead to better water quality predictions. As a case study, an agricultural basin in Ontario is used to demonstrate that using tile discharge data could increase the performance of both the hydrology and the nitrogen transport models. Watershed‐scale tile discharge was estimated based on sparse tile data collected at some tiles using a novel regression‐based approach. Through a series of calibration experiments, we show that utilizing tile flow signatures as calibration criteria improves model performance in the prediction of nitrate loads in both the calibration and validation periods. Predictability of nitrate loads is improved even with no tile flow data and by model calibration only against an approximate understanding of annual tile flow percent. However, despite high values of goodness‐of‐fit metrics in this case, temporal dynamics of predictions are inconsistent with reality. For instance, the model predicts significant tile discharge in summer with no tile flow occurrence in the field. Hence, the proposed tile flow upscaling approach and the partitioning‐constrained model calibration are vital steps toward improving the predictability of biogeochemical models in tiled landscapes.

This is the peer reviewed version of the following article: Kompanizare M, Petrone RM, Shafii M, Robinson DT, Rooney RC. Effect of climate change and mining on hydrological connectivity of surficial layers in the Athabasca Oil Sands Region. Hydrological Processes. 2018;32:3698–3716. https://doi.org/10.1002/hyp.13292, which has been published in final form at https://doi.org/10.1002/hyp.13292. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.

© American Geophysical Union: Shafii, M., Basu, N., Craig, J. R., Schiff, S. L., & Van Cappellen, P. (2017). A diagnostic approach to constraining flow partitioning in hydrologic models using a multiobjective optimization framework. Water Resources Research, 53(4), 3279–3301. https://doi.org/10.1002/2016WR019736