Infographic

High resolution models and data are needed, as well as the rapid and timely simulation of flood forecasts to better prevent pluvial floods.

Contrary to what one might expect, the specific monitoring and modelling needs for pluvial flood analysis in urban catchments have not translated into a denser monitoring network of rainfall and/or hydrological response. ︎
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The main reason is the relatively high cost of installation and maintenance of dense sensor networks. Although recent developments in radar technology have made it possible to obtain spatially - continuous, high resolution rainfall estimates, such measurements still need to be complemented by direct rainfall measurements on the ground.

APPROACH

3 PILOT CITIES

To develop the flood early warning service, we worked within the prone-to-flood cities of Brussels, Rotterdam and Birmingham.

‘The combination of steep slopes and a combined sewer system leads to high concentration of flows, making low-lying valley areas prone to pluvial floods’

‘The city's ambitious water resilience strategy has reduced the risk of pluvial flooding to only small-scale local floods’

‘While a flood alleviation scheme directly addresses the risk arising from fluvial floods in the Minworth catchment, the area remains prone to pluvial flooding’

In each city, we set up Urban Living Labs together with citizens, local institutions and other stakeholders to co- create the various solutions developed during the project.

URBAN
LIVING
LAB

> universities
> civil society
> ...

> water actors
> environmental agencies
> meteorological institute
> ...

In pilot cities, citizens played a CENTRAL AND ACTIVE ROLE  by gathering necessary alternative rainfall data to fulfil the need for spatially distributed measurements.

SOLUTIONS

With the FloodCitiSense app, citizens can make reports of rainfall intensity and impacts on the go!

Citizens placed low-cost rainfall sensors at home to help fill the gaps in cities’ network of official rain gauges.

With the FloodCitiSense app, citizens can make reports of rainfall intensity and impacts on the go!

Citizens placed low-cost rainfall sensors at home to help fill the gaps in cities’ network of official rain gauges.

Crowdsourced and smart sensing data gathered by citizens feed a database of detailed information crucial to improve the prediction of urban floods.

URBAN Pluvial flood  
early warning service

The FloodCitiSense mobile and web app

Usability score 
mobile app

74.2%

Usability score 
web platform

76%

Main CONCLUSION

The main challenge regarding the app is the building and retaining of a large users base.  The implementation of push notifications enabling  us to communicate with all users was a critical development in that direction.

Low-cost rainfall sensors

Overall, a total number of 50 low-cost, solar powered, acoustic rain gauges were assembled by – and distributed to citizens.
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A first trial with sensors brought out several shortcomings (damaged batteries, software malfunction, corrosion) that were improved with the release of the 2nd generation.

  It included an important new feature being the communication of data in near-real time using the global open LoRaWAN The Things Network (TTN)

Main findings

When compared to official, highly accurate sensors, the low cost sensors followed various trends:

A relatively high correlation between timeseries.
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A considerable underestimation of absolute rainfall rates, leading to...

... overlooking some peak rainfall events.

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A relatively high correlation between timeseries.
‍

A considerable underestimation of absolute rainfall rates, leading to...

... overlooking some peak rainfall events.

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The gathering of data using the low-cost sensors was complicated in multiple ways:

new sensors still faced BATTERY ISSUES during winter.
In an URBAN CONTEXT, the installation of low-cost sensors is challenging.

> it is crucial to limit obstruction by neighbouring objects as well as to  favorize a S-SW orientation.

> The placement of one personal, LoRa gateway per sensor helps overcoming connectivity issues and loss of data packages in urban contexts.

=> CONCLUSION: technology not mature yet

Modelling

We explored very different modelling  approaches in the 3 pilot cities.

*click the tabs for more details about the modelling approach in each pilot city

This variety is a direct result of the specific context in each pilot city (spatial configuration, data availability, etc.) But all approaches have in common that they enable to

set thresholds for identifying occurrence of pluvial flooding

Flood Early Warning System

Based on the identified thresholds for the occurrence of pluvial flooding, a prediction of pluvial flood risk can be made. 
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In the web platform, a dashboard that visualizes rainfall and flood predictions would enable water managers to evaluate the potential pluvial flood risks and take decisions on sending out a warning or not.

Check out web platform >

Outlook: Towards an operational phase

When operational, the FloodCitiSense tools  can facilitate urban management by

helping city authorities to :

Take appropriate decisions before and after flood events

Interact directly with citizens (e.g. flood warnings)