.png){kind=icon}
.png){kind=icon}
Return
Real-time control-based urban flood risk assessment framework for arid regions
.png){kind=icon}
PRE
AI
S
B
H
DOI：10.1080/15732479.2026.2691755.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Global climate change increases the risk of flash floods in urban areas of arid regions. Low-capacity storm drainage systems (SDS) designed for short return periods and clogged sewers during long dry periods intensify the severity. The present framework categorises the service area into different zones to assess SDS’s resilience to varying return-period floods using hazard, vulnerability, and exposure indices. The hazard index evaluates the hydro-geomorphological components based on water depth in manholes as a function of service area surcharge and overflow. The vulnerability index considers land use type, and the exposure index incorporates population density. The hierarchical approach estimates the risk index for each zone and the overall flood risk of a region. Real-time control (RTC) employs evidential reasoning within control structures to minimise flood risk by leveraging the capacity of manholes. The framework’s application to an 11.32 km2 urban area in the Qassim Region of Saudi Arabia demonstrates the RTC’s pragmatism for 5-, 10-, 20-, 50-, 100-, 200-, and 500-year floods. The existing SDS exhibited varying levels of resilience to flooding risk, ranging from very low to very high, affirming the approach’s robustness. The framework will assist municipalities with mitigating flood risk using RTC in urban areas of arid regions.
Keywords:
Flood risk
fuzzy logic
real-time control
internet of things
sustainability
arid regions
storm drainage systems
Journal
IF:
2.6
Papers:
451
Citations:
5.3K
Organization
Cited Papers