World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

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

Jeffrey C. Neal publication distribution in Environmental Sciences in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Environmental Sciences in 2026. The highlighted bar marks where Jeffrey C. Neal sits on this spectrum.

41–50 publications: 21 scientists 51–60 publications: 62 scientists 61–70 publications: 133 scientists 71–80 publications: 257 scientists 81–90 publications: 361 scientists 91–100 publications: 440 scientists 101–110 publications: 492 scientists 111–120 publications: 541 scientists 121–130 publications: 617 scientists 131–140 publications: 544 scientists 141–150 publications: 541 scientists 151–160 publications: 539 scientists 161–170 publications: 444 scientists 171–180 publications: 444 scientists 181–190 publications: 400 scientists 191–200 publications: 377 scientists 201–210 publications: 318 scientists 211–220 publications: 283 scientists 221–230 publications: 263 scientists 231–240 publications: 220 scientists 241–250 publications: 217 scientists 251–260 publications: 180 scientists 261–270 publications: 181 scientists 271–280 publications: 155 scientists 281–290 publications: 130 scientists 291–300 publications: 127 scientists 301–310 publications: 130 scientists 311–320 publications: 85 scientists 321–330 publications: 106 scientists 331–340 publications: 80 scientists 341–350 publications: 83 scientists 351–360 publications: 75 scientists 361–370 publications: 69 scientists 371–380 publications: 52 scientists 381–390 publications: 54 scientists 391–400 publications: 56 scientists 401–410 publications: 44 scientists 411–420 publications: 40 scientists 421–430 publications: 36 scientists 431–440 publications: 25 scientists 441–450 publications: 25 scientists 451–460 publications: 32 scientists 461–470 publications: 29 scientists 471–480 publications: 21 scientists 481–490 publications: 26 scientists 491–500 publications: 25 scientists 501–510 publications: 17 scientists 511–520 publications: 18 scientists 521–530 publications: 15 scientists 531–540 publications: 22 scientists 541–550 publications: 12 scientists 551–560 publications: 15 scientists 561–570 publications: 11 scientists 571–580 publications: 19 scientists 581–590 publications: 9 scientists 591–600 publications: 9 scientists 601–610 publications: 7 scientists 611–620 publications: 11 scientists 621–630 publications: 5 scientists 631–640 publications: 5 scientists 641–650 publications: 6 scientists 651–660 publications: 3 scientists 661–670 publications: 3 scientists 671–680 publications: 4 scientists 681–686 publications: 3 scientists 687+ publications: 100 scientists
41 publications 687+

This scientist: 256 publications — 79th percentile

79% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 687 publications or more.

Jeffrey C. Neal D-index placement in Environmental Sciences in 2026

The chart shows the D-index (discipline H-index) distribution of Environmental Sciences scientists ranked by Research.com in 2026. The highlighted bar marks where Jeffrey C. Neal sits on this spectrum.

30 D-Index: 12 scientists 31 D-Index: 26 scientists 32 D-Index: 51 scientists 33 D-Index: 88 scientists 34 D-Index: 123 scientists 35 D-Index: 163 scientists 36 D-Index: 206 scientists 37 D-Index: 267 scientists 38 D-Index: 265 scientists 39 D-Index: 275 scientists 40 D-Index: 321 scientists 41 D-Index: 343 scientists 42 D-Index: 305 scientists 43 D-Index: 336 scientists 44 D-Index: 330 scientists 45 D-Index: 348 scientists 46 D-Index: 291 scientists 47 D-Index: 275 scientists 48 D-Index: 272 scientists 49 D-Index: 273 scientists 50 D-Index: 263 scientists 51 D-Index: 232 scientists 52 D-Index: 266 scientists 53 D-Index: 217 scientists 54 D-Index: 199 scientists 55 D-Index: 177 scientists 56 D-Index: 202 scientists 57 D-Index: 204 scientists 58 D-Index: 166 scientists 59 D-Index: 177 scientists 60 D-Index: 166 scientists 61 D-Index: 152 scientists 62 D-Index: 143 scientists 63 D-Index: 150 scientists 64 D-Index: 124 scientists 65 D-Index: 119 scientists 66 D-Index: 120 scientists 67 D-Index: 118 scientists 68 D-Index: 82 scientists 69 D-Index: 98 scientists 70 D-Index: 94 scientists 71 D-Index: 105 scientists 72 D-Index: 74 scientists 73 D-Index: 84 scientists 74 D-Index: 70 scientists 75 D-Index: 67 scientists 76 D-Index: 78 scientists 77 D-Index: 60 scientists 78 D-Index: 59 scientists 79 D-Index: 52 scientists 80 D-Index: 47 scientists 81 D-Index: 38 scientists 82 D-Index: 48 scientists 83 D-Index: 42 scientists 84 D-Index: 42 scientists 85 D-Index: 43 scientists 86 D-Index: 29 scientists 87 D-Index: 37 scientists 88 D-Index: 29 scientists 89 D-Index: 30 scientists 90 D-Index: 34 scientists 91 D-Index: 20 scientists 92 D-Index: 22 scientists 93 D-Index: 17 scientists 94 D-Index: 19 scientists 95 D-Index: 24 scientists 96 D-Index: 21 scientists 97 D-Index: 20 scientists 98 D-Index: 24 scientists 99 D-Index: 17 scientists 100 D-Index: 17 scientists 101 D-Index: 21 scientists 102 D-Index: 25 scientists 103 D-Index: 18 scientists 104 D-Index: 26 scientists 105 D-Index: 19 scientists 106 D-Index: 15 scientists 107 D-Index: 10 scientists 108 D-Index: 13 scientists 109 D-Index: 15 scientists 110 D-Index: 12 scientists 111 D-Index: 8 scientists 112 D-Index: 7 scientists 113 D-Index: 9 scientists 114 D-Index: 6 scientists 115 D-Index: 12 scientists 116 D-Index: 7 scientists 117 D-Index: 8 scientists 118 D-Index: 3 scientists 119 D-Index: 5 scientists 120 D-Index: 7 scientists 121 D-Index: 2 scientists 122 D-Index: 4 scientists 123 D-Index: 8 scientists 124 D-Index: 7 scientists 125+ D-Index: 99 scientists
30 D-Index 125+

This scientist: 62 D-Index — 74th percentile

74% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 125 D-Index or more.

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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