World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
62
Citations
14752
World Ranking
2589
National Ranking
200

Overview

Jeffrey C. Neal is affiliated with the University of Bristol in the United Kingdom. Their research is primarily situated within the field of Environmental Science, with significant contributions spanning several subfields. These include Global and Planetary Change, Water Science and Technology, Atmospheric Science, Environmental Engineering, and Ecology.

The body of work by Neal focuses extensively on topics related to flood risk assessment and management, hydrology and watershed management studies, and tropical and extratropical cyclones research. Additional concentration areas include hydrology and drought analysis, hydrology and sediment transport processes, climate variability and models, and meteorological phenomena and simulations.

Neal's recent publications include:

  • "A 30 m global map of elevation with forests and buildings removed" (2022, Environmental Research Letters)
  • "Combined Modeling of US Fluvial, Pluvial, and Coastal Flood Hazard Under Current and Future Climates" (2020, Water Resources Research)
  • "Inequitable patterns of US flood risk in the Anthropocene" (2022, Nature Climate Change)
  • "A deep convolutional neural network model for rapid prediction of fluvial flood inundation" (2020, Journal of Hydrology)
  • "Flood hazard potential reveals global floodplain settlement patterns" (2023, Nature Communications)

Frequently collaborating with other researchers, Neal has coauthored numerous publications with Paul Bates, Laurence Hawker, Christopher Sampson, Raphaël M. Tshimanga, and James Savage.

Neal's work has appeared repeatedly in several prominent publication venues, including:

  • Water Resources Research
  • Zenodo (CERN European Organization for Nuclear Research)
  • Geophysical Monograph
  • Natural Hazards and Earth System Sciences
  • Environmental Research Letters

Best Publications

  • A high-accuracy map of global terrain elevations

    Dai Yamazaki;Daiki Ikeshima;Ryunosuke Tawatari;Tomohiro Yamaguchi

  • A high‐resolution global flood hazard model

    Christopher C. Sampson;Andrew M. Smith;Paul D. Bates;Jeffrey C. Neal

  • A 30 m global map of elevation with forests and buildings removed

    Unknown

  • A subgrid channel model for simulating river hydraulics and floodplain inundation over large and data sparse areas

    Jeffrey C. Neal;Guy Schumann;Guy Schumann;Paul D. Bates

  • Inequitable patterns of US flood risk in the Anthropocene

    Unknown

  • Comparative flood damage model assessment: towards a European approach

    B. Jongman;H. Kreibich;H. Apel;J. I. Barredo

  • Combined Modeling of US Fluvial, Pluvial, and Coastal Flood Hazard Under Current and Future Climates

    Paul D. Bates;Niall Quinn;Christopher Sampson;Andrew Smith

  • Flood Detection in Urban Areas Using TerraSAR-X

    D.C. Mason;R. Speck;B. Devereux;G.J.-P. Schumann

  • Integrating the LISFLOOD-FP 2D hydrodynamic model with the CAESAR model: implications for modelling landscape evolution

    Tom J. Coulthard;Jeffrey C Neal;Paul D. Bates;Jorge Ramirez

  • Advances in pan-European flood hazard mapping

    Lorenzo Alfieri;Peter Salamon;Alessandra Bianchi;Jeffrey Neal

  • A deep convolutional neural network model for rapid prediction of fluvial flood inundation

    Syed Kabir;Syed Kabir;Sandhya Patidar;Xilin Xia;Qiuhua Liang

  • How much physical complexity is needed to model flood inundation

    Jeffrey Neal;Ignacio Villanueva;Nigel Wright;Thomas Willis

  • Benchmarking urban flood models of varying complexity and scale using high resolution terrestrial LiDAR data

    Timothy J. Fewtrell;Alastair Duncan;Christopher C. Sampson;Jeffrey C. Neal

  • An intercomparison of remote sensing river discharge estimation algorithms from measurements of river height, width, and slope

    M. Durand;C. J. Gleason;P. A. Garambois;D. Bjerklie

  • Near Real-Time Flood Detection in Urban and Rural Areas Using High-Resolution Synthetic Aperture Radar Images

    D. C. Mason;I. J. Davenport;J. C. Neal;G. J-P Schumann

  • A first large-scale flood inundation forecasting model

    G. J.-P. Schumann;Jeff Neal;N. Voisin;K. M. Andreadis

  • The credibility challenge for global fluvial flood risk analysis

    Mark Trigg;Cathryn Birch;Jeffrey Neal;Paul Bates

  • Distributed whole city water level measurements from the Carlisle 2005 urban flood event and comparison with hydraulic model simulations

    Jeffrey C. Neal;Paul D. Bates;Timothy J. Fewtrell;Neil M. Hunter

  • New estimates of flood exposure in developing countries using high-resolution population data.

    Andrew Smith;Paul D. Bates;Oliver Wing;Christopher Sampson

  • Perspectives on Digital Elevation Model (DEM) Simulation for Flood Modeling in the Absence of a High-Accuracy Open Access Global DEM

    Laurence Hawker;Paul Bates;Jeffrey Neal;Jonathan Rougier

  • Evaluating a new LISFLOOD‐FP formulation with data from the summer 2007 floods in Tewkesbury, UK

    Jeff Neal;Gj-P Schumann;TJ Fewtrell;M Budimir

  • A data assimilation approach to discharge estimation from space

    Jeffrey Neal;Guy Schumann;Paul Bates;Wouter Buytaert

Frequent Co-Authors

Paul D Bates
Paul D Bates University of Bristol
Guy Schumann
Guy Schumann University of Bristol
David C. Mason
David C. Mason University of Reading
Jim Freer
Jim Freer University of Bristol
Michael Durand
Michael Durand The Ohio State University
Hannah Cloke
Hannah Cloke University of Reading
Keith Beven
Keith Beven Lancaster University
Dai Yamazaki
Dai Yamazaki University of Tokyo
Marco Chini
Marco Chini National Institute of Geophysics and Volcanology
Thorsten Wagener
Thorsten Wagener University of Potsdam

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