@conference {bnh-4809, title = {Real-time flood inundation mapping for flood intelligence {\textendash} a case study from India}, booktitle = {AFAC18}, year = {2018}, month = {09/2018}, publisher = {Bushfire and Natural Hazards CRC}, organization = {Bushfire and Natural Hazards CRC}, address = {Perth}, abstract = {

Bihar is India{\textquoteright}s most flood-prone State, with 76 percent of the northern population living under the recurring threat of flooding. Annual monsoon floods claim lives and destroy homes and livelihoods, seriously impacting the economy and poverty alleviation efforts. The Bagmati River is one of Bihar{\textquoteright}s major rivers, draining the Kathmandu Valley in the foothills of the Himalayas before entering flat agricultural plains of Northern Bihar.

With no pre-existing flood modelling or mapping, this project started with a blank worksheet, with the objective to forecast flooding a week ahead of occurrence, and generate real-time inundation mapping resulting from embankment failure.\  The project established a flood forecasting framework which loads and processes data from national and international sources and provides an interface for real-time hydrologic and hydraulic modelling.

The project faced many challenges, particularly related to availability of data. Despite these challenges, a flood forecasting framework has been established which provides capacity for evolution of the system, has supported local capacity building and will greatly improve understanding of flood behaviour. The system represents a step-change improvement for flood forecasting systems integrating multiple hydrologic and hydraulic models, and allowing forecasters to understand in real-time the impact of topographic changes to the floodplain.

}, author = {Ben Caddis and Carrie Dearnley} }