Design-Life Levels for Environmental Extremes: A Dependence-Aware Block-Maxima Workflow for Severity and Persistence

Abstract

Environmental risk assessment often asks how large the maximum discharge, flood, or insured loss may become over a design life rather than in a single year. In environmental records, planning-horizon risk is complicated by limited record length, extremal clustering, and sub-asymptotic behavior, yet severity estimation, clustering assessment, and design-life levels are often handled separately. We develop a dependence-aware block-maxima workflow that links these tasks within a single inferential scheme. The severity branch estimates the extreme value index from sliding block-maximum quantile scaling using data-adaptive plateau selection and covariance-aware feasible generalized least squares. The persistence branch pools native block-maxima extremal-index paths over a stable block-size window to characterize extremal clustering. Design-life levels are then derived on the chosen observation clock, with the extremal index retained as a complementary descriptor of persistence. In synthetic short-record benchmarks, the main gain is improved interval calibration under overlap dependence, especially within block-maxima comparisons. Applications to Texas and Florida streamflow and National Flood Insurance Program building-payout claims show persistent hydrologic extremes but much faster escalation of insured losses across adjacent parts of the flood-risk chain. The workflow provides calibrated severity, persistence, and design-life levels for environmental design and flood-risk assessment under dependent records.