REAL-TIME CONTROL (RTC)-BASED URBAN FLOOD RISK ASSESSMENT FRAMEWORK FOR ARID AND SEMI-ARID REGIONS

Global climate change has recently increased Flood Risk (FR) disasters in arid and semi-arid regions, particularly in Gulf countries, such as the Kingdom of Saudi Arabia (KSA). Arid regions generally face low rain on average during a year, but flash floods occur during rainfall of longer return periods due to urbanization and climate change. Flood Risk Assessment (FRA) outcomes enable municipalities (planners and decision-makers) in arid urban areas to develop flood management strategies and mitigate the issues of drainage systems, which may otherwise affect the quality of life. FRA is an effective tool for not only identifying high-risk areas but also for providing a comprehensive understanding of the FR landscape, thereby empowering decision-makers to develop effective Flood Risk Management (FRM) strategies. Furthermore, Real-Time Control (RTC) of Urban Drainage Systems (UDS) offers solutions to improve the efficiency of existing UDS. One of the motivations behind using RTC is to exploit the maximum storage conduit capacity in stormwater networks using actuators (control structure, i.e., gates or valves). This dissertation developed an FRA and management framework based on a fuzzy rule-based system for arid and semi-arid regions to identify and manage high flood-risk areas. Firstly, FRA is performed to identify the risk using a fuzzy rule-based system for different return periods, including 5, 10, 20, 50, 100, 200, and 500-year. Secondly, a proof-of-concept RTC strategy is developed to improve the efficiency of an existing stormwater drainage system that integrates urban hydrology knowledge with the Internet of Things (IoT) technology. Finally, the developed RTC for FRM is implemented on a simulation-based study to reduce or eliminate risks based on a fuzzy rule-based system for different return periods. Applying the FRA framework in Buraydah City (Qassim, KSA) revealed that the existing drainage system exhibits very low to very high flooding risks, based on the severity of rainfall. Findings show that 5 to 25-year return periods generate a 'very low' flooding risk, a 50 and 100-year return period generates a 'medium' flooding risk, a 200-year return period generates a 'high' risk, and a 500-year return period generates a ‘very high' flooding risk. Using the FRM approach based on RTC, simulations show a significant reduction in FR, in which risk levels for 5 to 100-year return periods are reduced to a 'very low' flooding risk, a 200-year return period generates a 'low' flooding risk, and a 500-year return period generates a 'medium' flooding risk. This potential for risk reduction should provide reassurance and confidence in the proposed framework. The research will provide valuable support to stormwater utility managers in arid and semi-arid regions, as well as potentially other areas worldwide, in improving their performance assessment and management of flooding risk. By effectively implementing the proposed framework and leveraging accurate resources, stormwater managers in these regions can realize socio-economic benefits, including enhanced infrastructure, minimized property damage, and improved public safety. Ultimately, this approach will contribute to an increased quality of life by enabling stormwater managers to identify and efficiently address underperforming areas within a city.