BEGIN:VCALENDAR METHOD:PUBLISH PRODID:www-gzn-nat-fau-eu//Events//EN VERSION:2.0 BEGIN:VEVENT SUMMARY:Lecture: Climate-Informed Flood Frequency Analysis and Emergin g Perspectives on Flood Hazards UID:05c4-2fc4-7e5c-27793@www.gzn.nat.fau.de DESCRIPTION:The Research Group Modeling of Environmental Systems (Prof . Dr. Gabriele Chiogna) is delighted to welcome Abinesh Ganapathy (Ind ian Institute of Technology Roorkee) at our institute where he will pr esent a lecture entitled “\;Climate-Informed Flood Frequency Anal ysis and Emerging Perspectives on Flood Hazards”\;. We look forwa rd to a broad attendance. When? Tuesday\, June 9\, 2026 | 12:00–13:0 0 Room: KH 0.011 Hörsaal Kollegienhaus\, EG\, Universitätsstraße 15 \, 91054 Erlangen Abstract Flooding is one of the most devastating nat ural hazards\, causing significant loss of life and resources across t he globe. Flood Frequency Analysis (FFA) is commonly used to estimate flood quantiles at different return periods\, thereby providing essent ial information to flood managers and decision makers for flood risk a ssessment. However\, the traditional FFA assumes all the flood samples are process-neutral\, neglecting the inherent flood-generating mechan isms. Further\, with the anthropogenic climate change impact\, the flo od distributions are expected to change\, thereby affecting the flood quantile estimates. My PhD research addresses these challenges by deve loping improved approaches for flood quantile estimation. First\, I pr opose a novel methodology that integrates pooling of reforecast datase ts and addresses sample heterogeneity to show the importance of incorp orating diverse flood-generating processes in FFA. Next\, a season-mix ing climate-informed approach has been proposed\, which exploits clima te- flood linkages and incorporates the seasonality effect while estim ating flood quantiles. Furthermore\, the climate-informed model is ext ended to forecast season-ahead flood quantiles for the Indian catchmen ts and compares the results against the stationary reference model. Th e results demonstrate the improved capability of the climate-informed model in forecasting flood quantiles with uncertainty comparable to th at of the reference model. The talk will also highlight o DTSTART:20260609T100000Z DTEND:20260609T110000Z LOCATION:KH 0.011 Hörsaal Kollegienhaus DTSTAMP:20260603T181816Z END:VEVENT END:VCALENDAR