Flood Adaptation

Flood adaptation research focuses on developing and implementing strategies to mitigate the impacts of increasingly frequent and severe floods. Current efforts emphasize equitable distribution of benefits from adaptation measures, addressing disparities in access to resources and protection across different communities, often employing causal inference methods to evaluate policy effectiveness. Furthermore, research explores the use of unsupervised domain adaptation techniques, such as adversarial networks, to improve flood forecasting accuracy in data-scarce regions, aiming to achieve performance comparable to supervised models with significantly less training data. These advancements are crucial for enhancing flood resilience and promoting climate justice globally.

Papers

October 17, 2024

DamFormer: Generalizing Morphologies in Dam Break Simulations Using Transformer Model
Zhaoyang Mul, Aoming Liang, Mingming Ge, Dashuai Chen, Dixia Fan, Minyi Xu
Knowledge Barrier Scientifically Interesting Morphology Flood Adaptation

December 6, 2023

Exposing Disparities in Flood Adaptation for Equitable Future Interventions
Lidia Cano Pecharroman, ChangHoon Hahn
Health Disparity Fairness Intervention Climate Change Adaptation Flood Adaptation

June 16, 2022

A Simple Baseline for Adversarial Domain Adaptation-based Unsupervised Flood Forecasting
Delong Chen, Ruizhi Zhou, Yanling Pan, Fan Liu
Domain Adversarial Flood Prediction Domain Encoders Coastal Flood Prediction Flood Adaptation

Flood Adaptation

Papers

DamFormer: Generalizing Morphologies in Dam Break Simulations Using Transformer Model

Exposing Disparities in Flood Adaptation for Equitable Future Interventions

A Simple Baseline for Adversarial Domain Adaptation-based Unsupervised Flood Forecasting