Abstract:
This report stands for the project deliverable 1.2 and concerns the results from task 1.2 of the Proper
Project, namely Characterization and critical review of the tools to predict road runoff.
Following the literature review conducted in task 1.1 where the most important pollutants in road runoff
were identified, the aim of the present task is to evaluate the models from a theoretic point of view in
order to choose the most feasible to be used by operators or road designers to predict pollution in road
runoff.
The selected predicting models were:
PREQUALE (Barbosa et al., 2011)
Highways Agency Water Risk Assessment Tool (HAWRAT) (Crabtree et al., 2008)
Multiple linear regression by Kayhanian et al. (2007)
Stochastic Empirical Loading and Dilution Model (SELDM) (Granato, 2013)
Multiple linear regression by Higgins (2007)
Risk Assessment of road stormwater runoff (RSS) (Gardiner et al., 2016)
Each one was assessed taking into account the input data, the easiness of applicability and the
consistency of the output results. These factors were classified by a score from 1 to 3 in order to have
a global rating.
This methodology was used to select the four models to be implemented in task 1.4 of the PROPER
Project: PREQUALE; HAWRAT; Kayhanian et al. (2007) and SELDM.
