World's Best Scientists 2026 revealed!
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Engineering and Technology
USA
2026

D-Index & Metrics

Engineering and Technology

D-Index
88
Citations
52572
World Ranking
308
National Ranking
104

Environmental Sciences

D-Index
93
Citations
56661
World Ranking
510
National Ranking
230

Research.com Recognitions

  • 2026 - Research.com Engineering and Technology in United States Leader Award
  • 2009 - Fellow of American Geophysical Union (AGU)

Overview

Hoshin V. Gupta is affiliated with the University of Arizona in the United States. Their research primarily focuses on environmental science with significant contributions to subfields such as global and planetary change, water science and technology, environmental engineering, atmospheric science, and artificial intelligence.

The research topics covered by Gupta include hydrology and watershed management studies, flood risk assessment and management, hydrological forecasting using AI, hydrology and drought analysis, meteorological phenomena and simulations, precipitation measurement and analysis, and climate variability and models.

Gupta has a substantial publication record in various scientific venues, with frequent contributions to:

  • Water Resources Research
  • Journal of Hydrology
  • arXiv (Cornell University)
  • Environmental Modelling & Software
  • SSRN Electronic Journal

The recent papers reflecting Gupta's research interests include:

  • What Role Does Hydrological Science Play in the Age of Machine Learning? (2020), published in Water Resources Research
  • The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support (2020), published in Environmental Modelling & Software
  • Differentiable modelling to unify machine learning and physical models for geosciences (2023), published in Nature Reviews Earth & Environment
  • Deep learning rainfall-runoff predictions of extreme events (2022), published in Hydrology and Earth System Sciences
  • The delusive accuracy of global irrigation water withdrawal estimates (2022), published in Nature Communications

Frequent coauthors who have collaborated extensively with Gupta include Holger R. Maier, Feifei Zheng, Yuan-Heng Wang, Junyi Chen, and Grey Nearing.

Gupta has been recognized as a Fellow of the American Geophysical Union (AGU), an award received in 2009, indicating a professional standing within the geosciences community.

Best Publications

  • Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling

    Hoshin V. Gupta;Harald Kling;Koray K. Yilmaz;Guillermo F. Martinez

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

    Hoshin Vijai Gupta;Soroosh Sorooshian;Patrice Ogou Yapo

  • Artificial Neural Network Modeling of the Rainfall‐Runoff Process

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

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

    Hoshin Vijai Gupta;Soroosh Sorooshian;Patrice Ogou Yapo

  • 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

  • A decade of Predictions in Ungauged Basins (PUB)—a review

    M. Hrachowitz;H. H. G. Savenije;G. Blöschl;J. J. Mcdonnell

  • 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

  • Uncertainty in hydrologic modeling: Toward an integrated data assimilation framework

    Yuqiong Liu;Hoshin V. Gupta

  • 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

  • “Panta Rhei—Everything Flows”: Change in hydrology and society—The IAHS Scientific Decade 2013–2022

    A. Montanari;G. Young;H.H.G. Savenije;D.A. Hughes

  • 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

  • Do Nash values have value

    Bettina Schaefli;Hoshin V. Gupta

  • Towards reduced uncertainty in conceptual rainfall-runoff modelling: Dynamic identifiability analysis

    Thorsten Wagener;N McIntyre;M J Lees;H S Wheater

  • 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

  • A framework for development and application of hydrological models

    Thorsten Wagener;Douglas P. Boyle;Douglas P. Boyle;Matthew J. Lees;Howard S. Wheater

  • The future of hydrology: an evolving science for a changing world.

    Thorsten Wagener;Murugesu Sivapalan;Murugesu Sivapalan;Peter A. Troch;Brian L. McGlynn

  • Improved treatment of uncertainty in hydrologic modeling: Combining the strengths of global optimization and data assimilation

    Jasper A. Vrugt;Cees G. H. Diks;Hoshin V. Gupta;Willem Bouten

  • Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models

    Martyn P. Clark;Andrew G. Slater;David E. Rupp;Ross A. Woods

Frequent Co-Authors

Soroosh Sorooshian
Soroosh Sorooshian University of California, Irvine
Thorsten Wagener
Thorsten Wagener University of Potsdam
Kuolin Hsu
Kuolin Hsu University of California, Irvine
Jasper A. Vrugt
Jasper A. Vrugt University of California, Irvine
Stewart W. Franks
Stewart W. Franks University of Tasmania
David C. Goodrich
David C. Goodrich US Department of Agriculture
Martyn P. Clark
Martyn P. Clark University of Saskatchewan
Terri S. Hogue
Terri S. Hogue Colorado School of Mines
Juan B. Valdés
Juan B. Valdés University of Arizona
Willem Bouten
Willem Bouten University of Amsterdam

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