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Global and local sensitivity analysis to improve the understanding of physically-based urban wash-off models from high-resolution laboratory experiments
Summary
A global and local sensitivity analysis was conducted on an urban stormwater runoff model to understand which parameters most influence how particles and pollutants are washed off city surfaces during rain events. Better stormwater models help quantify how microplastics from roads and urban surfaces reach waterways.
Physically-based urban wash-off models are a promising means of studying the transport of finer suspended solids and their associated pollutants during rain events, considering spatial and temporal heterogeneities. This study contributes to the understanding of these models through an in-depth sensitivity analysis to provide the necessary information to simplify the model and deal with parameter identifiability. First, based on twelve tailored high-resolution experiments, the accurate measurement of input variables was used to study the parameters of the Hairsine-Rose sediment transport model through a global sensitivity analysis. Using Standardized Regression Coefficients (SRC) and Extended Fourier Amplitude Sensitivity Test (EFAST) methods, the analysis showed that both the total washed-off mass and the TSS peaks concentration are highly sensitive to the critical mass, which considers the reduction in the detachment of particles when the sediment available decreases and is scattered over the surface. In addition, the rain- and flow-driven detachment parameters were presented as key for smaller and larger sediment particles, respectively. Then, those uncertainties that are associated in field studies with the determination of the model input variables were also considered by conducting a local sensitivity analysis. The initial load of sediment and the mean grain size were seen to be the most important variables, thus underlining the need for very accurate measurements here. Moreover, a precise definition of Harsine-Rose parameters is also necessary to achieve reliable results in order to work on treatment and management techniques to minimize the impact of urban surface contaminants on urban environments.
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