Flooding
Water Companies have common performance commitments to reduce customer property internal flooding. A critical aspect of improving performance is to understand that flooding can be caused by any individual or combination of issues within networks and flood waters can emanate from single or multiple ‘escape points’ as a result of these issues.
Asset management made easy
Whether rainfall related, overland flow from a burst water main or caused by roots blocking a sewer, flooding has significant customer impact.
Flooding can be prevented through advanced alerting algorithms and catchment knowledge enabling timely intervention; and incidents can be managed by having a greater level of information at the click of a button, all of which supports our clients to meet performance commitments and improve their customer experience.
Users of our predictive analysis platforms, such as WaterNet ProTM, can interrogate live data from telemetry systems alongside live modelling results and predictions. Using in conjunction with our specialist historical performance information and catchment knowledge and experience, interventions can be made in advance of events to manage flooding performance across this range of causes. Advanced 2D routing simulation can also deliver indicative impacts of flood waters on properties and to customers.
Our expertise
- Sewer flow surveys
- CCTV surveys
- Rainfall measurement
- Asset surveys - Combined Sewer Overflows (CSO), manhole and pumping station
- Drainage and mis-connection assessmentÂ
- Water Framework Directive - flow and quality survey
Leading minds
Featured insights-
Sweating wastewater data and systems? How to make better decisions faster
Read articleSteve Hogg looks at how machine learning and artificial intelligence are best implemented into water services and discusses how our own innovative data analysis tool, FlowBot, can achieve quicker, accurate data analysis.
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FlowBot: Going beyond existing best practice to deliver measurable benefit
Read articleSpreadsheets used to manage repetitive data analysis tasks takes time – too much time. This inefficiency results in less time available for engineers to work with their clients to support informed, sustainable decision making on their projects.
