Investigating Spatial Extremes of Annual Daily Precipitation Using CMIP6 Multi-Model Ensembles for Sustainable Flood Risk Assessment

Alaba Boluwade (), Paul Sheridan and Upaka Rathnayake
Additional contact information
Alaba Boluwade: School of Climate Change & Adaptation, University of Prince Edward Island, Charlottetown, PE C1A 4P3, Canada
Paul Sheridan: School of Mathematical and Computational Sciences, University of Prince Edward Island, Charlottetown, PE C1A 4P3, Canada
Upaka Rathnayake: Faculty of Engineering and Design, Atlantic Technological University, F91 YW50 Sligo, Ireland

Sustainability, 2025, vol. 17, issue 18, 1-23

Abstract: This study investigates the spatial characteristics of daily maximum precipitation for Prince Edward Island using a max-stable process model. The ssp126, ssp245, and ssp585 climate change scenarios, indicating low/optimistic, intermediate/in-between, and worst/pessimistic emissions scenarios, respectively, were extracted from 11 global climate model ensembles. For the time periods, the reference (historical) period was from 1971 to 2000, according to the World Meteorological Organization recommendations. Other time periods considered were 2011–2040, 2041–2070, and 2071–2100 as immediate, intermediate, and far future periods, respectively. The spatial trends analysis shows a west-to-east gradient throughout the entire study area. Return levels of 25 years were predicted for all the projections using the spatial generalized extreme value model fitted to the historical period, showing that topography should be included as a covariate in the spatial extreme model. Across the 134 grid points used in the study, the predicted return level for the historical period was 94 mm. Compared with the immediate time period, there is an increase of 47%, 53%, and 50% for the low, intermediate, and worst emission scenarios, respectively. For the intermediate period, there is an increase of 43%, 59%, and 56% for the low, intermediate, and worst emission scenarios, respectively. For the far future period, there is an increase of 49%, 48%, and 84% for the low, intermediate, and worst emission scenarios, respectively. There is a systematic increase in return levels based on the different periods. This shows a high chance of increased risks of extreme events of large magnitudes for this area in the immediate future through to the far future. This study will be useful for engineers, city planners, financial officials, and policymakers tasked with infrastructure development, long-term safety protocols, and sustainability and financial risk management.

Keywords: CMIP6 multi-model ensemble; return period; return level; spatial extremes; Canada (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/17/18/8198/pdf (application/pdf)
https://www.mdpi.com/2071-1050/17/18/8198/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:18:p:8198-:d:1747446

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().