## Materials and Methods
### LiDAR and Topographic Data  
In Europe, the DTM databases are accessible for public research centres (Directive 2007/2/EC of the European Parliament and of the Council). As for France, the National Institute of Geographic and  
\begin{table}
\begin{tabular}{c c c c c} \hline
**Rainfall Date** & **Rainfall Depth (mm)** & **Mean Intensity (mm/h)** & **Max Intensity (mm/h)** & **Duration (h)** \\ \hline
8 October 2014 & 4.86 & 1.52 & 8.57 & 6.17 \\
12 October 2014 & 3.60 & 1.68 & 7.50 & 2.14 \\
3 November 2014 & 4.60 & 1.33 & 36.0 & 10.3 \\
15 November 2014 & 9.27 & 2.81 & 6.21 & 4.41 \\
25 November 2014 & 2.86 & 1.32 & 5.14 & 3.33 \\
12 December 2014 & 4.15 & 1.28 & 40.0 & 22.6 \\ \hline \end{tabular}
\end{table}
Table 1: Characteristics of the six studied rainfall events.  
Figure 2: Study urban catchment in eastern Paris (12 ha, Le Perreux sur Marne, France). A rain gauge is installed on the roof of a building close to the catchment, and the flow monitoring devices are set up at the sewage outlet.  
Forestry Information (IGN) provides the large-scale reference database (RGE(r), [[http://professionnels.ign.fr/rge](http://professionnels.ign.fr/rge)]([http://professionnels.ign.fr/rge](http://professionnels.ign.fr/rge))) that contains DTM data of 25 m resolution for the whole country. Figure 3a shows a part of this data on our study site. This dataset is easy to achieve and demands no extra cost, hence have evident value for operational purposes.  
In addition to this available DTM data, a mobile mapping system (MMS) called Stereopolis [20] has been applied over the study area in order to produce a 3D point cloud of the road topography with centimetric resolution. Whereas the measured 3D cloud not only contains the topography, but also objects such as trees, urban furniture, and moving objects such as vehicles and pedestrians. A semi-automatic modeling approach was then developed in order to filter out the non-terrain point [21]. At the end, a 20 cm resolution topographic data of road and sidewalks was accomplished (Figure 3b).  
Following [PERSON] et al. and [PERSON] et al. [4; 8], the proper spatial resolution for 2D modeling of the urban surface can be set by considering the minimum distance between buildings and one third of the street width. For our case study, this distance can be estimated to 5 m. In order to assess the influence of high-resolution LiDAR data on urban 2D/1D modeling, three typical configurations are tested: (i) directly resampling the DTM data (25 m) to 5 m resolution, called \"DTM\"; (ii) resampling the DTM data (25 m) to 5 m resolution, and then lowering the identified road grid cells by 50 cm, called \"DTM--dug road\"; (iii) resampling the road LiDAR data (20 cm) and the DTM data (25 m) to 5 m resolution, then fusing the two types of data together, which will heretofore be called \"DTM + LiDAR\". The three different topographic scenarios are illustrated in Figure 4.  
Figure 4: Three different topographic input data. For (**a**) DTM, (**b**) DTM—dug road, and (**c**) DTM + LiDAR.  
Figure 3: Different sources of the topographic data. (**a**) Coarse digital terrain model (DTM) data of 25 m resolution; (**b**) 20 cm resolution light detection and ranging (LiDAR) topographic data for roads and sidewalks.