Theses Doctoral

Rethinking Climate Risk for Flood Insurance: Learning the Spatiotemporal Dynamics of Hydroclimatic Extremes

Nayak, Adam

The growing instability of U.S. insurance markets, evident in the NFIP’s over $20 billion debt and the withdrawal of private insurers from high-risk states, reflects a deeper failure in natural disaster risk quantification. Current catastrophe modeling frameworks, though advanced in spatial resolution and multi-hazard representation, often miss a key reality: hydroclimatic extremes are not independent or isolated, but emerge as spatiotemporally clustered phenomena shaped by ocean-atmosphere variability and climate change.

This dissertation develops new methods to assess, project, and manage flood risks that account for these dynamic space-time interactions. First, we analyze historical flood damage and NFIP debt, identifying the role of clustered extremes in driving financial losses. Next, we simulate nonstationary, climate-conditioned flood scenarios to forecast portfolio-level exposure under future extremes. Finally, we explore redesign strategies for the NFIP and reinsurance under clustered flooding and pressures of decentralization. By rethinking flood risk as a coupled human–climate system, this work aims to inform more resilient insurance portfolios in an era of compounding disaster risk.

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More About This Work

Academic Units
Earth and Environmental Engineering
Thesis Advisors
Lall, Upmanu
Degree
Ph.D., Columbia University
Published Here
June 24, 2026

Notes

Hydroclimate, Flooding, Machine learning, Climate Risk, Insurance