Paul D. Bates

The 2024 John Dalton Medal is awarded to Paul D. Bates for outstanding contributions to the modeling of flood hydrology from the local to the global scale.

By masterfully combining mathematical modelling, remote sensing, and field and laboratory experiments, Paul Bates’ work has revealed fundamental insights into flood propagation and the relative importance of dynamic and boundary conditions during flood propagation. Bates’ work is underpinned by rigorous numerical solutions to the shallow water equation and the assessment of related hydraulic models of different complexity. His computationally efficient codes for simulating dynamic moving-boundary problems over finite element grids offer a unique framework in which errors and uncertainties are properly treated for optimal inferences.

At the same time, Bates’ approach has drawn attention to the crucial information carried by the boundary conditions and the role of external forcing components, thereby recognising the necessity of including remotely sensed information for flood forecasting (obtained from airborne laser scanning terrain data and satellite flood-inundation and gravimetry data). This has led to the fundamental realisation that enhancing terrain data resolution and quality often produces greater improvements in inundation models than the technicalities of the solvers. Airborne imagery over floods allowed Bates and co-workers to map the sequential flooding of urban areas for the first time as well as to yield new insights into the dynamical processes occurring during urban floods and the length scales of terrain and building features that control the inundation and drainage of urban and natural floodplains. Bates and co-workers showed that floodplain filling often occurred as wide area sheet flows, but that floodplain drainage happened along small flow pathways often below the resolution of typical models.

Bates’ team has developed the tools and data sets to conduct such modelling globally, resulting in the first global two-dimensional hydrodynamic model to map areas at risk from flooding at 90m resolution across the entire terrestrial land surface. These methods have also been widely adopted by the scientific community and used by private and public agencies. Thanks to these efforts, it is now possible to produce detailed mapping of flood risk anywhere on the planet. Bates has revolutionised modern flood hydrology. His record of publications and service to the hydrological community toward a global flood prediction set a commendable example for EGU and the hydrologic community at large.