## 3 Results and Discussion
### Effects of Using Free Access Topographic and Landuse Data  
Considering the simulations using \"DTM + LiDAR topography\" and detailed land-use (DTM_LiDAR + DL) as reference, the effects of applying free access topographic (DTM-derived) and land-use (extracted from BD-TOPO(r)) data on model outputs can be respectively evaluated by comparing the reference simulations with simulations using (i) DTM topography and detailed land-use (DTM + DL); (ii) DTM--dug road topography and detailed land-use (DTM_dug + DL); and (iii) DTM + LiDAR topography and coarse land-use (DTM_LiDAR + CL). The mean deviation (_MD_) and relative mean deviation (_RMD_) coefficients are used as performance indicators to quantify the differences between the references and the scenario simulations (Equations (2) and (3)):  
\[MD\ =\ \frac{1}{n}\ \sum_{i=1}^{n}\Bigl{|}x_{i}\ -\ x_{ref,i}\Bigr{|} \tag{2}\]  
\[RMD\ =\ \frac{\frac{1}{n}\ \sum_{i=1}^{n}\Bigl{|}x_{i}\ -\ x_{ref,i}\Bigr{|}}{ \overline{x}_{ref}}\ *\ 100\ \% \tag{3}\]  
where \(n\) is the total number of simulated discharges during the rainfall events, \(x_{i}\) and \(x_{ref,i}\) are the \(i_{th}\) output of the scenario and reference simulation, respectively, and \(\overline{x_{ref}}\) is the mean discharge of the reference simulation. The simulated sewer network discharges for the six studied rainfall events are presented in Figure 7, and their _RMD_ coefficients are displayed in Table 3:  
As shown in Figure 7 and Table 3, simulations using coarse land-use data (CL) are quite different from that using detailed land-use information (DL), with RMD values around 50%. This result reveals that the present 2D/1D modeling approach is very sensitive to land-use data on the studied urban catchment. Compared with the simulations using DL, scenarios using CL underestimate water  
Figure 7: Sensitivity to low-resolution topographic data and coarse land-use information (free access). Simulations using DTM + LiDAR topography and detailed Land-use (reference, solid blue lines) are compared with simulations using (i) DTM topography and detailed land-use (DTM + DL, dashed blue lines); (ii) DTM—dug road topography and detailed land-use (DTM_dug + DL, dash-dotted blue lines); and (iii) DTM + LiDAR topography and coarse land-use (DTM_LiDAR + CL, dotted blue lines). Rainfall is plotted on the upper part. For events (**a**) 8 October 2014; (**b**) 12 October 2014; (**c**) 3 November 2014; (**d**) 15 November 2014; (**e**) 25 November 2014; (**f**) 12 December 2014.  
discharges at the sewage outlet. This phenomenon is mainly due to the underestimation of surface run-offs contributing to outlet discharges. The inappropriate description of the urban land-uses for the impervious areas and the adjoining areas of manholes in CL (Figure 5b) may be the major reason, since: (i) the inaccurate information of impervious areas can lead to the surface runoffs following paths that do not reach the manholes, and thus do not contribute to outlet discharge; and (ii) the presence of public green spaces surrounding the manholes can lead to an overestimation of infiltration. On the other hand, the results surprisingly demonstrate that the gaps between the reference simulations and simulations using free access topographic data (DTM and DTM_dug) are not significant. The simulated water flows at the sewage outlet are hence not sensitive to the use of different resolutions of topographic data. This result is mainly related to the precisely defined and closely located manholes in the studied urban catchment. Since the distances between manholes are very short (generally less than 30 m), stormwater runoffs enter rapidly into the sewer networks. Thus, the precision of the road topography does not notably influence the transfer time, as this time is very short in any case. Moreover, as the building roofs are directly connected to the sewer networks in the TRENOE platform, the effects of using precise road topographic data has no effect on these land-uses.