Inundation Modeling in Data Scarce Regions

Zvika Ben-Haim
Vova Anisimov
Yusef Shafi
Sella Nevo
Artificial Intelligence for Humanitarian Assistance and Disaster Response Workshop (2019)

Abstract

Flood forecasts are crucial for effective individual and governmental protective action. The vast majority of flood-related casualties occur in developing countries, where providing spatially accurate forecasts is a challenge due to scarcity of data and lack of funding. This paper describes an operational system providing flood extent forecast maps covering several flood-prone regions in India, with the goal of being sufficiently scalable and cost-efficient to facilitate the establishment of effective flood forecasting systems globally.