Canada Spends Logo

Explore our Budget 2026 analysis

Grant: Research Tools and Instruments

University of Prince Edward Island

$150,000.00

Development of a Laboratory-Scale Coastal-Inland Flood Simulator for Prince Edward Island

FY 2022-23

Summary
In recent years, global warming has intensified extreme precipitation and caused unprecedented sea level rise around the world. As an island province in Atlantic Canada, PEI has been threatened by increasing coastal-inland flooding risks and the island has been shrinking at a faster rate than previously thought due the severe coastal erosion. This has become especially obvious after recent unprecedented post-tropical storms (e.g., Hurricane Fiona in 2022 and Hurricane Dorian in 2019). How to protect the island from coastal erosion and build climate-resilient coastal communities has become one of the most important questions to be addressed in PEI. Therefore, the objective of this project is to develop a state-of-the-art laboratory-scale coastal-inland flood simulator (CIFS) for PEI to facilitate holistic flood risk assessment by estimating the combined effects of rising sea levels, intensified storm surges, and increasing inland floods caused by intense rainfall. The CIFS system will support the planning of coastal adaptation measures, evaluation of the effectiveness of different coastal protection measures, as well as operational and emergency management of flooding events. The core of the CIFS system will comprise two independent models - a coastal model and an inland model - that can run separately or together to carry out flood risk analyses for different climate change scenarios. The coastal model will be equipped to simulate potential changes in nearshore waves and storm surge activities across PEI under different climate change scenarios, while the inland model will be capable of simulating urban and overland flooding caused by different sources, including heavy rainfall, and their interactions with rising sea levels. The proposed CIFS system will be the first of its kind in Canada to support the laboratory-scale simulation and demonstration of combined coastal and inland flood events. Given the increasing coastal-inland flooding risks that PEI has been facing over the past years, the proposed CIFS platform is urgently needed to allow the research team in the Canadian Centre for Climate Change and Adaptation at UPEI to find some sustainable solutions to protect the island from coastal erosion.
Program
Research Tools and Instruments
Location
Prince Edward Island, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
RTI-2023-00585
Name nom
Wang, Xiuquan (Xander)
Department département
Science, Faculty of - Science, Faculty of
Organization id
88
Institution établissement
University of Prince Edward Island
Province en
Prince Edward Island
Province fr
Île-du-Prince-Édouard
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2023
Award amount
150000
Program id
RTI
Program name en
Research Tools and Instruments
Program name fr
Outils et instruments de recherche
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1609
Committee name en
Engineering (RTI)
Committee name fr
Génie (OIR)
Area of application code
400
Area of application group en
Environment
Area of application group fr
Environnement
Area of application en
Environment
Area of application fr
Environnement
Research subject code
4500
Research subject group en
Hydrology
Research subject group fr
Hydrologie
Research subject en
Hydrology
Research subject fr
Hydrologie
Installment
inst:1
Partie
1
Nb partie
1
Application title
Development of a Laboratory-Scale Coastal-Inland Flood Simulator for Prince Edward Island
Application summary
In recent years, global warming has intensified extreme precipitation and caused unprecedented sea level rise around the world. As an island province in Atlantic Canada, PEI has been threatened by increasing coastal-inland flooding risks and the island has been shrinking at a faster rate than previously thought due the severe coastal erosion. This has become especially obvious after recent unprecedented post-tropical storms (e.g., Hurricane Fiona in 2022 and Hurricane Dorian in 2019). How to protect the island from coastal erosion and build climate-resilient coastal communities has become one of the most important questions to be addressed in PEI. Therefore, the objective of this project is to develop a state-of-the-art laboratory-scale coastal-inland flood simulator (CIFS) for PEI to facilitate holistic flood risk assessment by estimating the combined effects of rising sea levels, intensified storm surges, and increasing inland floods caused by intense rainfall. The CIFS system will support the planning of coastal adaptation measures, evaluation of the effectiveness of different coastal protection measures, as well as operational and emergency management of flooding events. The core of the CIFS system will comprise two independent models - a coastal model and an inland model - that can run separately or together to carry out flood risk analyses for different climate change scenarios. The coastal model will be equipped to simulate potential changes in nearshore waves and storm surge activities across PEI under different climate change scenarios, while the inland model will be capable of simulating urban and overland flooding caused by different sources, including heavy rainfall, and their interactions with rising sea levels. The proposed CIFS system will be the first of its kind in Canada to support the laboratory-scale simulation and demonstration of combined coastal and inland flood events. Given the increasing coastal-inland flooding risks that PEI has been facing over the past years, the proposed CIFS platform is urgently needed to allow the research team in the Canadian Centre for Climate Change and Adaptation at UPEI to find some sustainable solutions to protect the island from coastal erosion.
University of Prince Edward Island - $150,000 Grant (… | Canada Spends