World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
65
Citations
21680
World Ranking
2159
National Ranking
877

Kuolin Hsu 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 Kuolin Hsu 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: 237 publications — 75th percentile

75% of scientists in this discipline score the same or lower.

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

Kuolin Hsu 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 Kuolin Hsu 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: 65 D-Index — 78th percentile

78% of scientists in this discipline score the same or lower.

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

Overview

Kuolin Hsu is affiliated with the University of California, Irvine in the United States. Their research primarily lies at the intersection of Environmental Science and Earth and Planetary Sciences, with contributions also spanning Atmospheric Science, Global and Planetary Change, Environmental Engineering, Water Science and Technology, and Public Health, Environmental and Occupational Health.

The scientist's work addresses a range of topics within these fields including:

  • Meteorological Phenomena and Simulations
  • Precipitation Measurement and Analysis
  • Hydrology and Watershed Management Studies
  • Climate variability and models
  • Soil Moisture and Remote Sensing
  • Flood Risk Assessment and Management
  • Hydrological Forecasting Using AI

Kuolin Hsu has contributed to multiple peer-reviewed papers, notable among them are:

  • PERSIANN-CCS-CDR, a 3-hourly 0.04° global precipitation climate data record for heavy precipitation studies, 2021, published in Scientific Data
  • PERSIANN Dynamic Infrared-Rain Rate (PDIR-Now): A Near-Real-Time, Quasi-Global Satellite Precipitation Dataset, 2020, published in Journal of Hydrometeorology
  • Improving near real-time precipitation estimation using a U-Net convolutional neural network and geographical information, 2020, published in Environmental Modelling & Software
  • Bias Correction of Satellite-Based Precipitation Estimations Using Quantile Mapping Approach in Different Climate Regions of Iran, 2020, published in Remote Sensing
  • Evaluation of Methods for Causal Discovery in Hydrometeorological Systems, 2020, published in Water Resources Research

The scientist frequently collaborates with other researchers including:

  • Soroosh Sorooshian
  • Phu Nguyen
  • Vesta Afzali Gorooh
  • Bita Analui
  • Ming-Chieh Lee

Kuolin Hsu's studies are often published in venues such as:

  • Journal of Hydrometeorology
  • Zenodo (CERN European Organization for Nuclear Research)
  • Remote Sensing
  • Bulletin of the American Meteorological Society
  • Journal of Hydrology

Best Publications

  • Artificial Neural Network Modeling of the Rainfall‐Runoff Process

    Kuo‐lin ‐l Hsu;Hoshin Vijai Gupta;Soroosh Sorooshian

  • A Review of Global Precipitation Data Sets: Data Sources, Estimation, and Intercomparisons

    Qiaohong Sun;Chiyuan Miao;Qingyun Duan;Hamed Ashouri

  • Evaluation of PERSIANN system satellite-based estimates of tropical rainfall

    Soroosh Sorooshian;Kuo Lin Hsu;Xiaogang Gao;Hoshin V. Gupta

  • PERSIANN-CDR: Daily Precipitation Climate Data Record from Multisatellite Observations for Hydrological and Climate Studies

    Hamed Ashouri;Kuo-Lin Hsu;Soroosh Sorooshian;Dan K. Braithwaite

  • Precipitation Estimation from Remotely Sensed Imagery Using an Artificial Neural Network Cloud Classification System

    Yang Hong;Kuo-Lin Hsu;Soroosh Sorooshian;Xiaogang Gao

  • Uncertainty assessment of hydrologic model states and parameters: Sequential data assimilation using the particle filter

    Hamid Moradkhani;Kuo-Lin Hsu;Hoshin V. Gupta;Soroosh Sorooshian

  • Integrated Multi-satellite Retrievals for the Global Precipitation Measurement (GPM) Mission (IMERG)

    George J. Huffman;David T. Bolvin;Dan Braithwaite;Kuo-Lin Hsu

  • Component analysis of errors in satellite-based precipitation estimates

    Yudong Tian;Yudong Tian;Christa D. Peters-Lidard;John B. Eylander;Robert J. Joyce

  • Hydrologic evaluation of satellite precipitation products over a mid-size basin

    Ali Behrangi;Ali Behrangi;Behnaz Khakbaz;Tsou Chun Jaw;Amir AghaKouchak

  • Evaluation of satellite-retrieved extreme precipitation rates across the central United States

    A. AghaKouchak;A. Behrangi;S. Sorooshian;K. Hsu

  • Self-organizing linear output map (SOLO): An artificial neural network suitable for hydrologic modeling and analysis

    Kuo Lin Hsu;Hoshin V. Gupta;Xiaogang Gao;Soroosh Sorooshian

  • Evaluation of the PERSIANN-CDR Daily Rainfall Estimates in Capturing the Behavior of Extreme Precipitation Events over China

    Chiyuan Miao;Hamed Ashouri;Kuo-Lin Hsu;Soroosh Sorooshian

  • The CHRS Data Portal, an easily accessible public repository for PERSIANN global satellite precipitation data.

    Phu Nguyen;Eric J. Shearer;Hoang Tran;Mohammed Ombadi

  • Intercomparison of rain gauge, radar, and satellite-based precipitation estimates with emphasis on hydrologic forecasting

    Koray K. Yilmaz;Terri S. Hogue;Kuo Lin Hsu;Soroosh Sorooshian

  • The frequency, intensity, and diurnal cycle of precipitation in surface and satellite observations over low- and mid-latitudes

    Aiguo Dai;Xin Lin;Xin Lin;Kuo-Lin Hsu

  • Uncertainty quantification of satellite precipitation estimation and Monte Carlo assessment of the error propagation into hydrologic response

    Yang Hong;Yang Hong;Kuo-lin Hsu;Hamid Moradkhani;Soroosh Sorooshian

  • HESS Opinions: Incubating deep-learning-powered hydrologic science advances as a community

    Chaopeng Shen;Eric Laloy;Amin Elshorbagy;Adrian Albert

  • Improving Precipitation Estimation Using Convolutional Neural Network

    Baoxiang Pan;Kuolin Hsu;Amir AghaKouchak;Soroosh Sorooshian

  • Intercomparison of high-resolution precipitation products over Northwest Europe

    C. Kidd;C. Kidd;P. Bauer;J. Turk;G. J. Huffman

  • Improved streamflow forecasting using self-organizing radial basis function artificial neural networks

    Hamid Moradkhani;Kuo Lin Hsu;Hoshin V. Gupta;Soroosh Sorooshian

  • Evaluation of PERSIANN-CCS rainfall measurement using the NAME event rain gauge network

    Yang Hong;David Gochis;Jiang-tao Cheng;Kuo-lin Hsu

Frequent Co-Authors

Soroosh Sorooshian
Soroosh Sorooshian University of California, Irvine
Amir AghaKouchak
Amir AghaKouchak University of California, Irvine
Hoshin V. Gupta
Hoshin V. Gupta University of Arizona
Yang Hong
Yang Hong University of Oklahoma
Ali Behrangi
Ali Behrangi University of Arizona
George J. Huffman
George J. Huffman Goddard Space Flight Center
Chris Kidd
Chris Kidd Goddard Space Flight Center
Pingping Xie
Pingping Xie National Oceanic and Atmospheric Administration
Hamid Moradkhani
Hamid Moradkhani University of Alabama
Qingyun Duan
Qingyun Duan Hohai University

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