Water Height and Flood Management System


Water height and flood management modelling involves the use of sensors (GPS, water level, radar for thermal images) to collect data on the water level, resources, quality and water-related hazards, for a set geographical area. The data collected is transmitted to a central system and then analysed to enable flood prevention and better water resource management.

Such flood management systems can process data on flooding and water quality in near real-time and can track patterns to identify areas likely to be flooded, looking at the probability that flooding will occur. This enables local authorities to determine mitigation solutions (e.g. dams and water management systems) or to identify alternative areas where the risk of flooding is lower.

Flooding is a frequent occurrence particularly in coastal regions, and near rivers and lakes. Flooding events can cause damage and destruction to property and infrastructure. Flooding is becoming increasingly frequent with climate change and rising sea levels. As urban expansion continues, flooding in these areas can become more frequent due to insufficient drainage. This requires action to lessen the risk of urban flooding for infrastructure.

A water height and flood management system will enable local authorities to predict future flooding and avoid building major infrastructure in high risk areas. Solutions such as water level control and flood prevention have been implemented around the world and have shown some success. For example, the Thames River barrier in the UK helps authorities to control the water level in the river by closing the barrier to stop additional water flowing in. This keeps the water level of the river consistent.

Sensor technologies can enable the collection of real-time data about water height, conditions and quality. This data is then analysed to create flood patterns for the region. Local authorities can use the flood patterns to identify the probability of flooding for each area and provide this information to engineers to improve decision-making when selecting suitable locations for future housing and infrastructure.

The data collected can be integrated into 3D models (see also the 3D Infrastructure Modelling use case) to control the design of future infrastructure and analyse the flooding risks on existing infrastructure. Implementation trials can be performed with prototypes in near realistic conditions to that of the location in question, to test the efficiency of the structures.



Improving efficiency and reducing costs:

  • Reduce the costs related to flooding and any potential loss of property, infrastructure and life by identifying flooding requirements upfront or avoiding building infrastructure in high risk areas.
  • Provide real-time monitoring of water levels to enable accurate decisions and timely responses.

Enhancing economic, social and environmental value:

  • Increase the resilience and safety of infrastructure by reducing flooding or the impact of flooding on infrastructure by enabling the implementation of mitigation solutions to prevent flood or enable the better placement of infrastructure at sites with lower risk.
  • Enable authorities to understand the current water environment, and alert them about water-related hazards.



Legislation and regulation: Governments should develop requirements for issues such as safety of workers during installations of monitoring stations since most of the stations are located remotely and the works are dangerous.

Effective institutions: Geotechnical and utility experts should be able to use the outputs from the flood modelling to drive better flood response and government decisions in relation to infrastructure projects.

Transition of workforce capabilities: Infrastructure planners and builders will be required to learn to use flood modelling and management systems to build their infrastructure.

Funding and financing: Governments should invest in flood studies and management systems. The public sector should finance flood management system projects as it provides benefits to both the environment and the city infrastructure. The private sector is also investing in the relevant sensor technologies and solutions that can be used to further develop water height and flood management systems.


Implementation risk

Risk: The implementation of the flood management system requires the installation of sensors in potentially remote, difficult to access locations. It may be difficult to find a suitable location to install the sensors due to the presence of existing infrastructure (e.g. utilities) and the need to avoid disturbing ongoing operations by installing the sensors. Furthermore, any available location may prove to be unsuitable or provide poorer data than the ideal location. The system requires a consistent communication network to transmit real-time data to the system.

Mitigation: The installation of sensors should be carefully planned to ensure there is no disruption to other operations and to find the most suitable location that will provide the highest possible quality of data. This should be done in collaboration with all relevant stakeholders to ensure minimum impact to operations.

Safety and (Cyber)security risk

Risk: The data is collected and transmitted by a computerised communication system, which means it is at risk of potential cybersecurity attack.

Mitigation: The operator must ensure the security of their communication and flood management systems to prevent data loss or theft during transmission or storage of data.

Environmental risk

Risk: The installation of sensors in remote areas can affect their surrounding environments and ecosystems.

Mitigation: Experts in areas such as aquatic biology, aquatic chemistry, and water/civil engineering should collaborate to ensure the water ecosystem is maintained and not affected or polluted because of the infrastructure developed and the technologies installed to monitor flood risks.



Example: Maeslant Storm Surge Barrier, the Netherlands

Implementation: The operation of the barrier is fully automatic via a connection to a computer system that links to weather and sea level data.

Cost: The cost to construct the barrier was EUR 450 million.

Timeframe: Construction took 6 years to complete. Operation started in 1997.

Example: WaterNSW Water Monitoring Network, Australia

Implementation: Over 5,000 monitoring stations measure the quality and quantity of New South Wales (NSW)’s rivers, streams, groundwater bores and dams. Over 1,300 of these stations deliver real-time data through NSW’s telemetry and remote data capture networks.

Timeframe: The data collected is available on the waterNSW website for up to 90 days.

Example: Oxford Flood Network

Implementation: A project built in partnership with Nominet UK and ThingInnovations, comprising of 30 wireless water level sensors to detect levels of water around the city to visualise flooding and river conditions.

Cost: The network gives a high spatial resolution than at a low cost, making it suitable for temporary deployment for catchment studies, community projects and site-specific monitoring.

Timeframe: Set up in 2014 following a series of storms that hit the UK causing flooding over the winter of 2013 and 2014.

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