World's Best Scientists 2026 revealed!
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Environmental Sciences
USA
2026

D-Index & Metrics

Environmental Sciences

D-Index
108
Citations
64998
World Ranking
222
National Ranking
99

Research.com Recognitions

  • 2026 - Research.com Environmental Sciences in United States Leader Award
  • 2025 - Research.com Environmental Sciences in United States Leader Award
  • 2010 - Fellow, The World Academy of Sciences
  • 2003 - Member of the National Academy of Engineering For the development of flood-forecasting models used worldwide in hydrologic services.
  • 1997 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 1994 - Fellow of American Geophysical Union (AGU)

Overview

Soroosh Sorooshian is affiliated with the University of California, Irvine in the United States. Their research primarily spans the fields of Earth and Planetary Sciences and Environmental Science, with a focus on Atmospheric Science and related subfields.

Their work covers several key topics, including:

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

The scientist has contributed to a variety of recent publications, such as:

  • "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

They have published frequently in journals including:

  • Remote Sensing
  • Journal of Hydrometeorology
  • Journal of Hydrology
  • Bulletin of the American Meteorological Society
  • Environmental Modelling & Software

Sorooshian often collaborates with several researchers, notably:

  • Kuolin Hsu
  • Phu Nguyen
  • Vesta Afzali Gorooh
  • Bita Analui
  • E. J. Shearer

The scientist has been recognized with various awards and honors, including:

  • Fellow, The World Academy of Sciences (2010)
  • Member of the National Academy of Engineering (2003) for the development of flood-forecasting models used worldwide in hydrologic services
  • Fellow of the American Association for the Advancement of Science (AAAS) (1997)
  • Fellow of American Geophysical Union (AGU) (1994)

Best Publications

  • Effective and efficient global optimization for conceptual rainfall‐runoff models

    Qingyun Duan;Soroosh Sorooshian;Vijai Gupta

  • A Modified Soil Adjusted Vegetation Index

    J. Qi;A. Chehbouni;A.R. Huete;Y.H. Kerr

  • Status of Automatic Calibration for Hydrologic Models: Comparison with Multilevel Expert Calibration

    Hoshin Vijai Gupta;Soroosh Sorooshian;Patrice Ogou Yapo

  • Shuffled complex evolution approach for effective and efficient global minimization

    Q. Y. Duan;V. K. Gupta;S. Sorooshian

  • Artificial Neural Network Modeling of the Rainfall‐Runoff Process

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

  • Optimal use of the SCE-UA global optimization method for calibrating watershed models

    Qingyun Duan;Soroosh Sorooshian;Vijai K. Gupta

  • Toward improved calibration of hydrologic models: Multiple and noncommensurable measures of information

    Hoshin Vijai Gupta;Soroosh Sorooshian;Patrice Ogou Yapo

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

    Qiaohong Sun;Chiyuan Miao;Qingyun Duan;Hamed Ashouri

  • A Shuffled Complex Evolution Metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters

    Jasper A. Vrugt;Hoshin V. Gupta;Willem Bouten;Soroosh Sorooshian

  • 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 information using artificial neural networks

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

  • Multi-objective global optimization for hydrologic models

    Patrice Ogou Yapo;Hoshin Vijai Gupta;Soroosh Sorooshian

  • Dual state-parameter estimation of hydrological models using ensemble Kalman filter

    Hamid Moradkhani;Soroosh Sorooshian;Hoshin Vijai Gupta;Paul R. Houser

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

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

  • Toward improved calibration of hydrologic models: Combining the strengths of manual and automatic methods

    Douglas P. Boyle;Hoshin V. Gupta;Soroosh Sorooshian

  • 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

  • Multi-model ensemble hydrologic prediction using Bayesian model averaging

    Qingyun Duan;Newsha K. Ajami;Xiaogang Gao;Soroosh Sorooshian

  • Effective and efficient algorithm for multiobjective optimization of hydrologic models

    Jasper A. Vrugt;Hoshin V. Gupta;Luis A. Bastidas;Willem Bouten

  • Automatic calibration of conceptual rainfall-runoff models: sensitivity to calibration data

    Patrice O. Yapo;Hoshin Vijai Gupta;Soroosh Sorooshian

  • Model Parameter Estimation Experiment (MOPEX): An overview of science strategy and major results from the second and third workshops

    Q. Duan;J. Schaake;V. Andréassian;S. Franks

Frequent Co-Authors

Kuolin Hsu
Kuolin Hsu University of California, Irvine
Hoshin V. Gupta
Hoshin V. Gupta University of Arizona
Amir AghaKouchak
Amir AghaKouchak University of California, Irvine
Ali Behrangi
Ali Behrangi University of Arizona
Terri S. Hogue
Terri S. Hogue Colorado School of Mines
Qingyun Duan
Qingyun Duan Hohai University
David C. Goodrich
David C. Goodrich US Department of Agriculture
Yang Hong
Yang Hong University of Oklahoma
Roger C. Bales
Roger C. Bales University of California, Merced
Hamid Moradkhani
Hamid Moradkhani University of Alabama

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