Two decades of ensemble flood forecasting: a state-of-the-art on past developments, present applications and future opportunities

In the present study a total of 201 research articles from around the globe over the review period from 2001 to 2021 are identified and investigated. The study has identified some of the grand challenges associated with ensemble flood forecasting (EFF). In addition, future opportunities are identified including the development of quality-controlled datasets for longer duration, new techniques to weigh the ensembles, inclusion of more physically based datasets in data assimilation techniques, simulation of more observable states by hydrological models to facilitate data assimilation, application of artificial intelligence and machine learning, and optimization of computational efficiency to issue timely flood warnings. Moreover, it is worth mentioning that in addition to the technical aspects, the effectiveness of the operational flood forecasting system depends on the non-technical aspects.

Automated summary

This study investigates 201 research articles from around the globe between 2001 and 2021, identifying the challenges and opportunities associated with ensemble flood forecasting (EFF). The findings highlight the importance of both technical and non-technical aspects in the effectiveness of operational flood forecasting systems.