In collaboration with Luleå University of Technology (LTU) and Professor Jiri Marsalek (LTU and Burlington Research Institute, Canada), we wrote a scientifically reviewed article in the journal Sustainability which was published 2022-03-02.

The article is a follow-up to the article we wrote last year with the same co-authors and which can also be downloaded from www.stormtac.com. The previous article described the methodology in the model with a focus on quantifying uncertainty for different inputs and results.

This second article in the topic describes the advantage of using the type of simpler model, of which StormTac Web is an example, and how to quantify the uncertainty specifically for each substance and land use based on updated data in StormTac Database. The methodology that StormTac Web uses to quantify the uncertainty in the input data and results contained in the model is because of the article scientifically reviewed. The methodology is presented in the guide with supplementation in these two articles. The uncertainty has been shown not to be greater than in more dynamic models that would require significantly more data.

This second article examines these types of stormwater models, their methodology, calculated uncertainty, and their usefulness when input data is limited, as in most stormwater investigations and projects with areas planned to be exploited. According to Marsalek, calibration of stormwater models is a major challenge, especially at the planning level, as the physical system under construction does not yet exist, with which calibration data must be transferred from similar existing areas. Such transposition of data can be implemented using the StormTac Web model and the StormTac Database, which contain stormwater quality data for different types of urban land use.

The demonstrated data-driven approach, implemented within the framework of StormTac Web and associated database, has proven to be a practical tool to facilitate the analysis of stormwater quality and pollution control in urban catchment areas. This is especially true for planned cases that cannot be measured and are therefore necessary to model. This also applies to existing areas as it is very costly to measure flows and pollutants, which would require flow proportional sampling over a longer period. The approach used by StormTac Web utilizes typical values of runoff coefficients and concentrations from sub-areas with different land uses and is based on data from flow proportional sampling from a large number of similar case studies. This data is continuously updated and reported in StormTac Database.

The article can be downloaded from our website www.stormtac.com and from the journal: https://www.mdpi.com/2071-1050/14/5/2888/pdf