CityCAT

Report Exercise 7 - CITYCAT

 

Team 1 - HydroEurope

Deadline: February 10th 2016

Benoît BESSEAS, Océane CALMELS, Laura DAUL, Kamila FUSIEK, Guillaume HAZEMANN, Zhengmin LEI, Quentin MOLIERES, Arianna VARRANI, Taline ZGHEIB

Supervisors: Philippe GOUBERSVILLE, Olivier DELESTRE

 

I.                   Introduction

CityCAT is a software tool for hydrodynamic modelling, analysis and visualization of surface water flooding. It enables the assessment of flood risk at the city scale, and effects of different flood risks management measures. It also allows the user to take into account some installations or potential solutions called the “blue-green features”: infiltration, roof storage, swales.

The goal of this exercise is to calculate the maximum depth of water adjacent to the shopping center New Eldon Square in the city of Newcastle upon Tyne (UK) and to find adaptations to reduce this water depth. Indeed, Newcastle upon Tyne suffered from huge floods in the past years, and this borrow was one of the ones that were the most impacted.


II.               Study area and methodology

The study zone is set in the center of Newcastle upon Tyne (UK), in the North East of England as we can see on figure 1, and has a total area of 0.457 km². Moreover, permeable pavements (~0.095 km²) and impermeable pavements (~0.146 km²) cover the area.

This exercise consists in modelling the flood with the current values of permeable and impermeable surfaces and then repeat this simulation by changing the green roof storage and permeable areas to evaluate the impact. After testing different scenarios, we will propose a solution to mitigate the risk of urban flooding.

 

Figure 1: Newcastle upon Tyne localization [Google Maps]

CityCat uses a surface flow model: shallow water equations solved by finite volumes with shock-capturing scheme. The software has two major advantages:

       The buildings are considered as objects so roof drainage, occupants and damages can be modelled ;

       The flow processes are more realistic and faster to model than other software where the buildings are part of the flow grid.

The data used for this exercise are:

-          A 3m resolution lidar DEM of the ground surface in Newcastle Upon Tyne ;

-          An input of rainfalls of a 1-hour duration from a 20-year return period storm ;

-          Text files of the buildings present in the study zone (~0.216 km²) and greens areas.

We upload these files on Citycat and obtain the map on figure 2, which defines our study area. The DEM generates the computational grid, which is divided into permeable (green areas) and impermeable areas (roads).

 

Figure 2: the numerical grid defining the study area.

 

By zooming in and zooming out, we can visualize the grid and all the cells one by one with their characteristics. Then the goal is to simulate the flood event by changing the permeability of the soil and the capacity of storage of the green roofs.

 

The main steps to simulate the water depth are the following (figure 3):


Figure 3: Main Steps of the CityCAT process

For all the simulations, we can visualize the results with graphs that represent the water depth (but also the velocity of the water) according to the time.

 

III.            Results and discussion

In this part, we run different scenarios with different parameters and compare the results obtained for the cell 41474. This cell is situated on the East side of the New Eldon Square at 44m of altitude. This cell represents an area of 16m² and a perimeter of 16m.

First, we run the original scenario with impermeable roads and no roof storage. We obtain a water depth of 1.5m at the cell 41474 with a velocity that does not exceed 0.03m/s, whether it is the velocity according to X, or according to Y. (figure 4)


Figure 4: Results for the original scenario.

 

Then, for the second, third and fourth simulations, we consider impermeable roads and the installation of green roofs on top of the buildings with a respective roof storage capacity of: 0.01 m, 0.025 m and 0.1 m (table 1). This installation lead to a decrease of water depth to a minimum of 0.93 m. Therefore, it seems that the more we increase the storage capacity of the roof storage, the more the water depth will decrease, which makes sense in the case that the water comes from the rain. Indeed the rain will be captured by the green roofs and will less likely fall on the ground.

If we consider the entire surface permeable (to allow water to escape by infiltration) and no roof storage, we obtain a 1.16 m water depth, which is less than the original scenario with no permeable cells at all.

The last idea is to combine both of the solution to see the impacts on the water depth. If we consider the entire surface permeable with a roof storage of 0.01 m, 0.025 m and 0.1 m (table 1), we observe that the minimal water depth is 0.22 m and occurs with permeable cells and a roof storage of 0.1 m. (figure 5)


Figure 2: Results with combined solutions (0.1m of roof storage and permeable cells)

With this combination, we also notice that the velocity decreased in X and only increased a little bit (not exceeding 0.04 m/s) for the Y.

This result is logical and constitute a good solution to mitigate the flood risk. Nevertheless, this solution is expensive: we can count about £100 to £150 per meter squared of green roof in the UK (Renewableenergyhub.co.uk, 2017).

It is important to note that if we increase again the roof storage, the water depth increases once again compared to the previous results. (We obtain a water depth of 0.94m with a roof storage of 0.25m). Therefore, it is safe to say that the best combination seems to stay permeable cells and a roof storage of 0.1m.

This table bellows recapitulates the results of the water depth we were able to obtain depending on the input parameters.

Table 1: Water depth according to the different case scenario

 

Throughout all those simulations with this model, it is important to note that we are not considering the saturation of the sewer network and this have an important impact on the water depth. Here, rainfall water becomes runoff or infiltrates into the permeable roads. Nevertheless, taking the sewer network into account would decrease runoff until a critical rainfall quantity. It could be interesting to define this critical rainfall quantity. Depending on that value, a study of the network dimensioning could be considered.

Another aspect to take into account is that we considered that all the cells were impermeable or permeable, but this does not represent the reality well. Indeed, we said in the beginning that the city had about ~0.095 km² permeable pavements and about ~0.146 km² impermeable pavements. However, even if in CityCAT allows us to change the permeability of some cells, it is difficult to approximate the area it represents. In addition, we do not know exactly where in reality are those types of pavements. In addition, it might not be very realistic to change all the pavements in the streets of Newcastle and once again, it might cost a lot of money to do so.

Finally concerning the rainfalls, we only have 13 values of rainfalls on a short amount of time (3600 seconds), maybe it would be wiser to simulate the even with a longer simulation time and/or more rain.

 

IV.            Conclusion

CityCAT is a good software to model the urban floods at a city-scale, thanks to the advantage of taking into account the buildings that are not part of the computational grid. The fact that the software allows us to insert parameters that can be used to decrease the volume of water is a good alternative to simulate and compare the best results in order to reduce the vulnerability of Newcastle upon Tyne to urban flooding. Implementing roof storage (eg: green roof) is definitely a solution that can be considered but has to be chosen carefully because of its price. The combination with permeable pavements in the city (allowing infiltration) seems to be the most efficient solution to reduce the water depth.

Overall, the tutorial was easy to follow and reproduce. We wished we were able to produce a map with all the water depths indicated but did not succeed.

 

V.                References

1.         Newcastle University, CITYCAT - Step by Step tutorial. Polytech Nice-Sophia Antipolis , HYDROEUROPE 2017.

2.         Renewableenergyhub.co.uk. (2017). How much do green roofs cost? : Green Roof Information. [online] Available at: https://www.renewableenergyhub.co.uk/green-roof-information/how-much-do-green-roofs-cost.html [Accessed 6 Feb. 2017].

 

 

 

 

 

 

 

Ċ
laura DAUL,
9 Feb 2017, 04:23
Comments