This review compares and evaluates eleven Low Impact Development (LID) models on the basis of: (i) general model features including the model application, the temporal resolution, the spatial data visualization, the method of placing LID within catchments; (ii) hydrological modelling aspects including: the type of inbuilt LIDs, water balance model, runoff generation and infiltration; and (iii) hydraulic modelling methods with a focus on the flow routing method. Results show that despite the recent updates of existing LID models, several important features are still missing and need improvement. These features include the ability to model: multi-layer subsurface media, tree canopy and processes associated with vegetation, different spatial scales, snowmelt and runoff calculations. This review provides in-depth insight into existing LID models from a hydrological and hydraulic point of view, which will facilitate in selecting the best-suited model. Recommendations on further studies and LID model development are also presented.

The primary goal of low impact development (LID) is to capture urban stormwater runoff; however, multiple indirect benefits (environmental and socioeconomic benefits) also exist (e.g., improvements to human health and decreased air pollution). Identifying sites with the highest demand or need for LID ensures the maximization of all benefits. This is a spatial decision-making problem that has not been widely addressed in the literature and was the focus of this research. Previous research has focused on finding feasible sites for installing LID, whilst only considering insufficient criteria which represent the benefits of LID (either neglecting the hydrological and hydraulic benefits or indirect benefits). This research considered the hydrological and hydraulic, environmental, and socioeconomic benefits of LID to identify sites with the highest demand for LID. Specifically, a geospatial framework was proposed that uses publicly available data, hydrological-hydraulic principles, and a simple additive weighting (SAW) method within a hierarchical decision-making model. Three indices were developed to determine the LID demand: (1) hydrological-hydraulic index (HHI), (2) socioeconomic index (SEI), and (3) environmental index (ENI). The HHI was developed based on a heuristic model using hydrological-hydraulic principles and validated against the results of a physical model, the Hydrologic Engineering Center-Hydrologic Modeling System model (HEC-HMS). The other two indices were generated using the SAW hierarchical model and then incorporated into the HHI index to generate the LID demand index (LIDDI). The framework was applied to the City of Toronto, yielding results that are validated against historical flooding records.

Climate change and urbanization are increasing the intensity and frequency of floods in urban areas. Low Impact Development (LID) is a technique which attenuates runoff and manages urban flooding. However, the impact of climate change and urbanization on the demand or need for LID in cities for both current and future conditions is not known. The primary goal of this research was to evaluate the demand for LID under different climate change and urban growth scenarios based on a physical-based geospatial framework called the hydrological-hydraulic index (HHI). To do this, 12 scenarios considering four climate change and three urbanization conditions were developed. The HHI for three cities in Canada (Toronto, Montreal, and Vancouver) were estimated, evaluated, and compared for these scenarios. The results show that both urbanization and climate change increase the demand for LID. The contribution of climate change and urbanization on LID demand, measured using HHI, varies for each city: in Toronto and Montreal, high rainfall intensity and low permeability mean that climate change is dominant, whereas, in Vancouver, both climate change and urbanization have a similar impact on LID demand. Toronto and Montreal also have a higher overall demand for LID and the rate of increase in demand is higher over the study period. The results of this study provide us with a comprehensive understanding of the effect of climate and urbanization on the demand for LID, which can be used for flood management, urban planning, and sustainable development of cities.

Urban stormwater runoff is a major pathway for microplastic (MP) pollution to aquatic environments. In this study, MPs from five stormwater catchments (SWCs) in the City of Kitchener, Ontario, Canada, were analyzed in water and sediment samples collected at their receiving stormwater ponds (SWPs). We integrated MP characterization targeting particles between 20 and 500 µm using a Laser Direct Infrared (LDIR) system with hydrological modeling, measured sediment accumulation rates, and particle to mass conversion calculations to quantify MP concentrations and loads. The LDIR data included polymer type, size class, and particle shape. Inflow concentrations to the SWPs ranged from 4.9 × 10⁶ to 4 × 10⁷ particles m^-3 and from 5.8 × 10^-2 to 0.9 g m^-3, yielding annual loads of 9.7 × 10¹¹ to 3.5 × 10¹² particles yr^-1 and 1.1 × 10⁴ to 8 × 10⁴ g yr^-1. Per unit impervious surface area MP yields fell in the range 3.6 × 10¹⁰ to 2.1 × 10¹¹ particles ha^-1 yr^-1 and 4.2 × 10² to 4.9 × 10³ g ha^-1 yr^-1, while normalized to the total SWC area produced 1.6 × 10¹⁰-1.4 × 10¹¹ particles ha^-1 yr^-1 and 1.9 × 10²-3.2 × 10³ g ha^-1 yr^-1. Fragments were the dominant morphology (94-98% by count; 83-91% by mass). MPs smaller than 100 µm comprised 92.6-97.3% of particle counts but only 32.1-60.8% of mass, whereas MPs larger than 500 µm accounted for 0.2-0.8% of particle counts but 5.9-33.9% of mass. Yields showed no systematic differences across broad land-use categories and no correlation with total population. Instead, positive associations were observed with residential population density and with SWC imperviousness, including strong correlations with rubber and several polymer-specific yields. Annual average daily traffic was not related to total MP loads from SWCs but aligned with the relative abundances of specific polymers, particularly polystyrene and polycarbonate. Yields of rubber particles correlated with overall MP yields, reinforcing the role of road traffic as a source. Road and mixed-impervious cover considered independently were not significant predictors, but their ratio explained the relative yields of fragments, fibers, and selected polymers.