Question 1

Which countries lead Flood Risk Assessment and Management research?

Accepted Answer

By volume, China and the United States publish the most (3.8k and 2.2k works in 2022-now).

Question 2

Which institutions lead Flood Risk Assessment and Management research?

Accepted Answer

By volume in 2022-now, Chinese Academy of Sciences publishes the most Flood Risk Assessment and Management research, followed by Hohai University and Centre National de la Recherche Scientifique.

Question 3

Who are the leading researchers in Flood Risk Assessment and Management?

Accepted Answer

The most-cited researchers publishing on Flood Risk Assessment and Management include Yoshua Bengio, Jun Wang and Xiaogang Wang.

Question 4

Where is Flood Risk Assessment and Management research done?

Accepted Answer

The largest centres of Flood Risk Assessment and Management research in 2022-now are Beijing (China), Nanjing (China), Wuhan (China) and New Delhi (India). Among places with at least 20 works in it, it is an unusually large share of all research in Arba Minch.

Question 5

Where is the best place to study Flood Risk Assessment and Management?

Accepted Answer

Among universities, judged by research, China University of Geosciences, Beijing Normal University and Hohai University score highest, combining citation excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

Question 6

Is Flood Risk Assessment and Management research growing?

Accepted Answer

Output in 2022-2025 was 28% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Flood Risk Assessment and Management.

Question 7

What are the most cited papers in Flood Risk Assessment and Management?

Accepted Answer

The most cited paper in Flood Risk Assessment and Management is "The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features" (Stuart K. McFeeters, 1996), with 7,778 citations. Next come "Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling" (7,007) and "A physically based, variable contributing area model of basin hydrology / Un modèle à base physique de zone d'appel variable de l'hydrologie du bassin versant" (6,834).