Rydén, Jesper
- Department of Energy and Technology, Swedish University of Agricultural Sciences
 
Estimation of so-called return levels for environmental extremes is of importance for risk assessment. A particular challenge is to find estimates corresponding to long return periods, as uncertainties in the form of confidence intervals became too wide for practical use when applying conventional methodology where large portions of data are not used. A recently proposed technique, the Average Conditional Exceedance Rate (ACER), makes effective use of all available data. For risk analysis related to nuclear infrastructure, usually located along a coastline, extreme sea levels are of concern. We demonstrate, for measurements of the sea level along the Swedish coast at locations close to nuclear power plants, that the methodology results in considerably shorter confidence intervals compared to conventional approaches.
extreme values; GEV distribution; ACER method; return levels; sea level
                                GeoHazards
2024, volume: 5, number: 1, pages: 166-175
                            
                                Oceanography, Hydrology, Water Resources
Probability Theory and Statistics
                            
https://res.slu.se/id/publ/128472