Pre Conference Forum

8
Jun

Flood preparedness, emergency response and intelligent infrastructure control

Severe incidents of flooding are increasing worldwide. Sea-level rise due to climate change and human-induced land subsidence threaten the sustainability of numerous communities settling near river deltas.

Megacities, like New York, London and Shangai, are particularly vulnerable not only due to their rapid population growth but also because of their aging infrastructure. At the same time, extreme droughts are becoming more common and most climate models predict that by the end of this century the dry regions of the world will become drier whilst the wet areas will become wetter [1]. In the years to come, sustainability, liveability, and disaster response in urban environments will vitally rely on the efficient management of water infrastructure assets. The latter have been traditionally designed on the basis of obsolete methods and often function very poorly [2], having negative human, societal and environmental impact (flooding, combined sewer overflows, poor water quality) and causing substantial direct/indirect financial loss (damaged properties/ legal penalties). Yet, thanks to technological developments in wireless communication technologies, computing power, and Unmanned Aerial Vehicles (UAV), their possible inadequacies can be crucially mitigated through the development of new generation, intelligent, water defence/management networks, which can be supported by Early Warning Systems (EWS) and Real-Time Decision Support Systems (RT-DSS).

 

Research and development interest in EWS has picked up over the past decade (see a thorough review of existing studies in [3]). Worthy of special mention is the cloud-based platform recently developed by the EU funded UrbanFlood project [4]. Remotely monitoring the response of flood defence structures and analysing the sensor data through relevant geophysical and artificial intelligence software, the platform provides real-time assessment of the behaviour and strength of multiple test dikes located in 3 European countries with increased flood risk (namely, the Netherlands, the UK, and Germany). Making use of precipitation forecasts, it can be used to predict the short-term performance of the monitored flood defence systems, enabling timely management of flooding events.

 

UAVs often constitute an efficient, increasingly cost-effective, alternative to wireless sensors and have the appealing advantage of providing useful high quality digital images of the area at risk. Compared with space-borne observations, aerial remote sensing using UAVs is immune to extensive clouds and revisit limitations, manifesting itself as an ideal tool for flood monitoring. Erdelj et al [5] report in detail the latest advances in UAVs deployed in a variety of disaster management applications, not only for the sake of monitoring and early warnings but also in post-event applications related to reconnaissance, evacuation support and rescue. Despite their recognised limitations, primarily associated with power supply and maneuverability in harsh weather conditions, recent reports from Red Cross [6] and Unicef [7] advocate for UAVs as one of the most promising and powerful new technologies for use in post-disaster response and relief operations.

 

The vision for resilient cities strives for proactive rather than reactive measures against natural hazards. As far as stormwater is concerned, this has been recently rendered possible at least at a local, watershed scale [8 – 10]. Thanks to the use of Internet of Things (IoT) technology, real-time sensor data readings can be integrated with weather forecasts to allow dynamic, minute-by-minute, coordination, adaptive control and preactive optimization of the performance of stormwater storage assets (reservoirs, dry ponds, green roofs, etc.). In fact, such an intelligent stormwater network control has been effectively implemented in a plethora of sites across the US during the past few years [11].

 

Significant further development is necessary to scale up the gains from the aforementioned technological advancements and efficiently adopt them in the diffuse urban environment. Active campaigning and cross-sectoral consultation will create opportunities for systemic infrastructure interventions and promote coherent and integrative preparedness and response strategies.

 

Sources:

  1. Trenberth K.E. (2011). Changes in precipitation with climate change. Climate Research, 47, 123 – 138.
  2. Report to Congress on Implementation and Enforcement of the CSO Control Policy. EPA. 2015.
  3. Erdelj M., Król M., Natalizio E. (2017). Wireless Sensor Networks and Multi-UAV systems for natural disaster management. Computer Networks, 124, 72 – 86.
  4. http://www.urbanflood.eu
  5. Erdelj M., Natalizio E., Chowdhury K.R., Akylidiz I.F. (2017). Help from the Sky: Leveraging UAVs for Disaster Management. IEEE Pervasive Computing, 16(1), 24 – 32.
  6. Drones for Disaster Response and Relief Operations, American Red Cross, 2015. issuelab.org/resources/21683/21683.pdf.
  7. Malawi Floods Situation Report 18. UNICEF, 2015.https://www.unicef.org/malawi/media_19507.html
  1. Muschalla D., Vallet B., Anctil F., Lessard P., Pelletier G., Vanrolleghem P.A. (2014). Ecohydraulic-driven real-time control of stormwater basins. Journal of Hydrology, 511, 82 – 91.
  2. Hutton C.J., Kapela Z., Vamvakeridou-Lyroudia L. Savic D.A. (2014). Dealing with Uncertainty in Water Distribution System Models: A Framework for Real-Time Modeling and Data Assimilation. Journal of Water Resources Planning and Management, ASCE, 140, 169 – 183.
  3. Kerkez B., Gruden C., Lewis M., Montestruque L., Quigley M., Wong B., Bedig A., Kertesz R., Braun T., and Cadwalader O. (2016). Smarter stormwater systems. Environmental Science & Technology, 50, 7267–7273.
  4. Quigley M. and Brown C. (2014). Transforming Our Cities: High-Performance Green Infrastructure (WERF Report INFR1R11). Water Environment Research Foundation, Alexandria, VA, 2014.