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A new approach of monitoring and physically-based modelling to investigate urban wash-off process on a road catchment near Paris

Overview of attention for article published in Water Research, October 2016
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Title
A new approach of monitoring and physically-based modelling to investigate urban wash-off process on a road catchment near Paris
Published in
Water Research, October 2016
DOI 10.1016/j.watres.2016.06.027
Pubmed ID
Authors

Yi Hong, Celine Bonhomme, Minh-Hoang Le, Ghassan Chebbo

Abstract

Nowadays, the increasing use of vehicles is causing contaminated stormwater runoff to drain from roads. The detailed understanding of urban wash-off processes is essential for addressing urban management issues. However, existing modelling approaches are rarely applied for these objectives due to the lack of realistic input data, unsuitability of physical descriptions, and inadequate documentation of model testing. In this context, we implement a method of coupling monitoring surveys with the physically-based FullSWOF (Full Shallow Water equations for Overland Flow) model (Delestre et al., 2014) and the process-based H-R (Hairsine-Rose) model (Hairsine and Rose, 1992a, 1992b) to evaluate urban wash-off process on a road catchment near Paris (Le Perreux sur Marne, Val de Marne, France, 2661 m(2)). This work is the first time that such an approach is applied for road wash-off modelling in the context of urban stormwater runoff. On-site experimental measurements have shown that only the finest particles of the road dry stocks could be transferred to the sewer inlet during rainfall events, and most Polycyclic Aromatic Hydrocarbons (PAHs) are found in the particulate phase. Simulations over different rainfall events represent promising results in reproducing the various dynamics of water flows and sediment transports at the road catchment scale. Elementary Effects method is applied for sensitivity analysis. It is confirmed that settling velocity (Vs) and initial dry stocks (S) are the most influential parameters in both overall and higher order effects. Furthermore, flow-driven detachment seems to be insignificant in our case study, while raindrop-driven detachment is shown to be the major force for detaching sediment from the studied urban surface. Finally, a multiple sediment classification regarding the Particle Size Distribution (PSD) can be suggested for improving the model performance for future studies.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 25%
Researcher 6 19%
Student > Master 5 16%
Student > Bachelor 3 9%
Student > Doctoral Student 2 6%
Other 5 16%
Unknown 3 9%
Readers by discipline Count As %
Environmental Science 9 28%
Engineering 9 28%
Earth and Planetary Sciences 3 9%
Agricultural and Biological Sciences 1 3%
Nursing and Health Professions 1 3%
Other 3 9%
Unknown 6 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 June 2016.
All research outputs
#10,874,305
of 12,269,818 outputs
Outputs from Water Research
#4,680
of 5,590 outputs
Outputs of similar age
#224,403
of 271,287 outputs
Outputs of similar age from Water Research
#55
of 104 outputs
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