Prof. Dr. Zoran Kapelan

Prof Kapelan’s work is already delivering a major impact in engineering practice. Working closely with the water industry he has pioneered the award winning technology for automated detection of pipe bursts/leaks and other events in drinking water systems. The technology is using Artificial Intelligence to process pressure and flow sensor data in near real-time. A version of this technology is now used companywide in United Utilities reducing the risk of supply interruptions to its 7 million customers and resulting in major operational cost savings.

On the wastewater side, Prof Kapelan has developed a new technology for automated condition assessment of sewer pipes from CCTV data by using image processing and machine learning techniques. This technology is currently being commercialised. Another example is the methodology for the prediction of sewer blockage rates that is assisting Welsh Water in creating operational and maintenance plans.

Prof Kapelan is a member of External Scientific Advisory Council of KWR, IWA Digital Water Steering Committee, IWA/IAHR/IAHS Management Committee on Hydroinformatics, the EWRI Emerging and Innovative Technologies Task Committee and the ASCE WDSA Standing Committee.

He is currently serving as an Editor for the Journal of Water Resources Planning and Management (ASCE) and Associate Editor for the Water Resources Research. He has given over 80 invited talks including over 12 keynotes at major water engineering events such as IWA and CCWI conferences series. He has received a number of awards for his work. Further information can be found on his personal website.

Prof Kapelan’s research is inter-disciplinary in nature and covers the following topics across the urban water cycle:

• Smart water systems and hydroinformatics: advanced methods for planning, operation/control and maintenance of drinking water and sewer systems by using sensor and other data and advanced methods such as AI/machine learning and real-time forecasting and control;
• Drinking water distribution systems management: leakage detection and management, pressure management, pump scheduling, optimal system (re)design including network/DMA sectorization, discolouration risk, demand forecasting, demand saving technologies, smart demand metering, intermittent water supply;
• Storm/waste/combined sewer systems management: blockage/collapse predications and management, optimal (re)design and maintenance of these systems, sediment transport, nature based solutions / sustainable drainage systems;
• Integrated water management and solutions: centralised and decentralised solutions based on water and wastewater recovery/recycling/reuse and the principles of urban metabolism, water-energy-food nexus, circular economy and sustainability;
• Adaptation of urban water infrastructure to uncertain future: robust, resilient and flexible design based adaptation to climate change, population growth and urbanisation; characterisation of uncertainties;
• Asset management of urban water infrastructure: advanced asset condition inspection techniques, asset performance assessment, asset deterioration modelling, prioritisation of asset interventions
• Flood risk assessment and management;
• Other (e.g. water resources management)

The above involves applying and developing new methods:

• Artificial intelligence / machine learning (neural networks, deep learning, Random Forest, Bayesian Networks), image processing, fuzzy logic
• Real-time data validation, state estimation using data assimilation, real-time control including model predictive control
• Methods for fault detection and isolation/location such as detection of pipe bursts/leaks, blockages/collapses and equipment failures;
• Optimisation (stochastic/deterministic, wide range of metaheuristics including Genetic Algorithms, hybrid optimisation)
• Multi-criteria decision analysis including methods such as Analytical Hierarchy Process and Compromise Programming
• Decision making under deep uncertainty (robust/resilient/flexible design, Real options, scenario discovery)
• Risk assessment and management including methods such as Fault and Event Tree Analysis and Failure Mode and Effect Analysis
• Advanced simulation models of urban water infrastructure (physically based, data-driven and hybrids)
• Serious gaming
• Other (e.g. advance statistics methods)

Prof Kapelan participated in funding prioritisation panels and has evaluated research proposals for over 20 funding bodies around the world. He has examined externally over 50 PhD students in ten countries. He served as a chair or member of scientific and organisation committees at more than 50 international and national conferences, workshops and other events. He has supervised over 25 postdocs and 40 PhD students so far.

Further information about Prof Kapelan’s research can be found on his personal website.