Hoshin Gupta
Hoshin Gupta
Regents Professor, Department of Hydrology & Atmospheric Sciences
TEP Fellow of the UA Galileo Circle
SRP Professor of Technology, Public Policy, and Markets
Fellow of the American Geophysical Union
2014 Winner of the EGU John Dalton Medal
2017 Winner of the AMS Robert E Horton Lecture Award
(520) 626-9712
PhD, Systems Engineering, Case Western Reserve University, 1984

Research: Hoshin Gupta is an internationally recognized leader in systems methods for reconciling models with data. He was elected Fellow of the American Geophysical Union in 2009 for ‘consistent contributions to modeling science’, awarded the 2014 Dalton Medal of the European Geophysical Union for ‘pioneering work on systems methods for the field of hydrology’, and the 2017 Robert E Horton Lecture award of the American Meteorological Society for ‘fundamental contributions towards quantifying uncertainty in hydrologic model predictions’. From 2009-2013, Hoshin served as an Editor of the premier hydrologic science journal ‘Water Resources Research’.

Hoshin is a hydrologist, systems theorist and philosopher, with strong technical skills in complex algorithm development. His particular expertise is in earth system modeling and in exploring issues relating to terrestrial processes with a particular focus on hydrology. Historically he has driven improvements to methods for model-based learning, including multi-criteria and diagnostic methods, and is now leading developments in assessment and correction of model structural adequacy based in rigorous Bayesian and Information Theoretic approaches. This work has earned him an H-Index = 62, having published 10 books and over 170 peer-reviewed papers, about 30% of which have been cited more than 100 times, and one cited more than 1500 times (data indicated for April 2017). 

Since serving as Associate Director (2000-2005) of the UA-HWR-based NSF science and technology center SAHRA, Hoshin has been working on improving the integration of hydrologic science into decision-making and policy. In 2006, he was named the Salt River Project (SRP) Professor of Technology, Public Policy & Markets for work on evaluating hydrological impacts of potential climate change, in 2013 the Tucson Electric Power (TEP) Fellow of the UA Galileo Circle, and in 2017 a Regents Professor of the University of Arizona. He has co-edited two books ‘Water Policy in New Mexico: Addressing the Challenge of an Uncertain Future’ (RFF Press 2012) was published in 2012 and co-edited book ‘Water Bankruptcy in The Land Of Plenty: Steps towards a Transatlantic and Transdisciplinary Assessment of Water Scarcity In Southern Arizona’ (CRC Press 2016), the latter being a product of the first EU funded project to strengthen ties between European- and US-based researchers in the social and natural sciences related to water. 

Teaching: Hoshin teaches graduate courses in the theory and applications of Systems Methods to hydrology, and an undergraduate class for non-science majors entitled ‘Earth: Our Watery Home’. He consistently receives excellent student evaluations, was recognized 5 years in a row for excellence in teaching by being voted the “Aquaman Award” by the students, and in 2015 received the UA Graduate College Graduate and Professional Education Teaching and Mentoring Award.

Selected Citations: 

Selected Publications (April 2017): 

A. Philosophy of Science:
Nearing GS and HV Gupta (In review), Information vs. Uncertainty as a Foundation for Science, submitted to Entropy journal.
Nearing GS and HV Gupta (in review), Ensembles vs. Information Theory: Supporting Science under Uncertainty, Special issue on "Uncertainty in Water Resources" of the Frontiers of Earth Science (FESCI).
Nearing G, Y Tian, H Gupta, K Harrison, M Clark & S Weijs (2016), A philosophical basis for hydrological uncertainty, Hydrologic Sciences Journal, 61(9), pp. 1666-1678
Gupta HV and GS Nearing (2014), Debates—The future of hydrological sciences … Using models and data to learn: A systems theoretic perspective …, Invited Commentary, Water Resources Research, 50

B. Information Theory & Models:
Nearing GS and HV Gupta (2015), The Quantity and Quality of Information in Hydrologic Models, Water Resources Research, 51, 524–538, doi:10.1002/2014WR015895
Gong W, D Yang, HV Gupta and G Nearing (2014), Estimating Information Entropy for Hydrological Data: One Dimensional Case, Technical Note, Water Resources Research, 50
Gupta HV and GS Nearing (2014), Debates—The future of hydrological sciences … Using models and data to learn: A systems theoretic perspective …, Invited Commentary, Water Resources Research, 50
Nearing GS, HV Gupta and W Crow (2013), Information Loss in Approximately Bayesian Data Assimilation …, Journal of Hydrology, 507, pp. 163-173
Gong W, HV Gupta, D Yang, K Sricharan, AO Hero (2013), Estimating Epistemic & Aleatory Uncertainty During Hydrologic Modeling: An Information Theory Approach, Water Resources Research, 49, 1–21
Nearing GS, HV Gupta, WT Crow and Wei G (2013), An Approach to Quantifying the Efficiency of a Bayesian Filter, Water Resources Research, 49, 1–10
Gupta HV, MP Clark, JA Vrugt, G Abramowitz and M Ye (2012), Towards a Comprehensive Assessment of Model Structural Adequacy, Opinion Paper, Water Resources Research, 48(8), 1-16, W08301

C. Sensitivity Analysis:
Razavi S and HV Gupta (2016), A New Framework for Comprehensive, Robust, and Efficient Global Sensitivity Analysis: Part II - Applications, Water Resources Research, 52, 440–455
Razavi S and HV Gupta (2016), A New Framework for Comprehensive, Robust, and Efficient Global Sensitivity Analysis: Part I - Theory, Water Resources Research, 52, 423–439
Razavi S and HV Gupta (2015), What Do We Mean by Sensitivity Analysis? The Need for a Comprehensive Characterization of ‘Global’ Sensitivity in … Systems Models, Water Resources Research
Rosolem R, HV Gupta, WJ Shuttleworth, X Zeng and LGG de Goncalves (2012), A Fully Multiple-Criteria Implementation of the Sobol Method for Parameter Sensitivity Analysis, J Geophys. Res. (117), D07103
Bastidas LA, HV Gupta, S Sorooshian, WJ Shuttleworth and ZL Yang (1999), Sensitivity Analysis of a Land Surface Scheme Using Multi-Criteria Methods, JGR-Atmospheres, 104 (D16), pp. 19481-19490

D. Uncertainty Analysis & Data Assimilation:
Bulygina N, and H Gupta (2011), Correcting the Mathematical Structure of a Hydrological Model Via Bayesian Data Assimilation, Water Resources Research, 47, W05514, doi:10.1029/2010WR009614
Bulygina N and HV Gupta (2010), How Bayesian Data Assimilation Can be Used to Estimate the Mathematical Structure of a Model, Stochastic Environ. Research and Risk Assessment, 24:925–937
Bulygina N, and HV Gupta (2009), Estimating The Uncertain Mathematical Structure Of A Water Balance Model Via Bayesian Data Assimilation, Water Resources Research, 45
Liu YQ, and HV Gupta (2007), Uncertainty in hydrologic modeling: Toward An Integrated Data Assimilation Framework, Water Resources Research, 43, W07401
Vrugt JA, CGH Diks, HV Gupta, W Boughten and JM Verstraten (2005), Imp. Treatment of Unc. in Hyd. Mod.: Combining the Strengths of Global Opt. and Data Assim., Water Res. Research, 41(1), W01017
Thiemann M, MW Trosset, HV Gupta and S Sorooshian (2001), Bayesian Recursive Parameter Estimation for Hydrologic Models, Water Resources Research, Vol. 37, No. 10, pp. 2521-2535

E. Diagnostic Model Identification:
Gupta HV, C Perrin, R Kumar, G Blöschl, M Clark, A Montanari and V Andressian (2014), Large-Sample Hydrology: A Need to Balance Depth With Breadth, Hydrology and Earth Systems Science, 18, 1–15
Martinez GF and HV Gupta (2011), Hydrologic Consistency as a Basis for Assessing Complexity of Water Balance Models for the Continental United States, Water Resources Research
Martinez GF and HV Gupta (2010), Toward Imp. Identifiability of Hyd. Models: A Diagnostic Evaluation of the “abcd” Monthly Water Balance Model … United States, Water Resources Research, 46, W08507
Gupta HV, H Kling, KK Yilmaz and GF Martinez-Baquero (2009), Decomposition of the Mean Squared Error & NSE Performance Criteria: Implications for Imp. Hydr. Mod., J of Hydrology, 377, pp. 80-91
Yilmaz KK, HV Gupta and T Wagener (2008), A Process-Based Diagnostic Approach To Model Evaluation: Application To The NWS Distributed Hydrologic Model, Water Resources Research, 44, W09417
Gupta HV, T Wagener and YQ Liu (2008), Reconciling Theory with Observations: Towards a Diagnostic Approach to Model Evaluation, Hydrological Processes, 22 (18), pp. 3802-3813

F. Optimization Algorithms:
Vrugt JA, HV Gupta, LA Bastidas, W Bouten and S Sorooshian (2003), Effective and efficient algorithm for multi-objective opt. of hydrologic models, Water Resources Research, Vol. 39, No. 8, pp. 5.1-5.19
Vrugt JA, HV Gupta, W Bouten and S Sorooshian (2003), A Shuffled Complex Evolution Metropolis Alg. for Opt. and Unc. Assess. of Hyd. Model Par, Water Resources Research, Vol. 39, No. 8, pp. 1.1-1.16
Duan Q, S Sorooshian and VK Gupta (1992), Effective and Efficient Global Optimization for Conceptual Rainfall-Runoff Models, Water Resources Research, Vol. 28, No. 4, pp. 1015-1031

G. Data-Based Modeling:
Sapriza G, J Jodar-Bermudez, J Carrera-Ramirez, HV Gupta (2013). Stoch. Sim. of Non-Stat. Rainfall Fields, Accounting for Seasonality and Atmos. Circ. … , Mathematical Geosciences, 45 (5), pp 621-645.
Hsu K, HV Gupta, X Gao, S Sorooshian and B. Imam (2002), Self-Organizing Linear Output Map (SOLO): An Artificial Neural Network Suitable for Hyd. Mod. and Anal., Water Res. Res., 38 (12), pp. 38.1-38.17
Hsu L, HV Gupta, X Gao and S Sorooshian (1999), Est. of Physical Var. from Multi-Channel Remotely Sensed Imagery using a Neural Network: Appl. to Rainfall Est., Water Res. Res., 35 (5), pp. 1605-1618
Hsu K, X Gao, S Sorooshian and HV Gupta (1997), Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks, Journal of Applied Meteorology, 36(9), pp. 1176-1190
Hsu K, HV Gupta and S Sorooshian (1995), Artificial Neural Network Modeling of the Rainfall-Runoff Process, Water Resources Research, 31 (10), pp. 2517-2530

H. Multi-Criteria Model Identification:
Rosolem R, HV Gupta, WJ Shuttleworth, LGG de Goncalves, and X Zeng (2012), Towards a Comprehensive Approach to Parameter Estimation in Land Surface Parameterization Schemes, Hydrological Processes, published online in Wiley Online Library (wileyonlinelibrary.com)
Laplastrier M, AJ Pitman, HV Gupta and Y Xia (2002), Exploring the Relationship Between Complexity and Performance in a Land Surface Model Using the Multi-Criteria Method, J Geophysical Res., 107 (D20)
Xia Y, AJ Pitman, HV Gupta, M Laplastrier, A Henderson-Sellers and LA Bastidas (2002), Calib. a Land Surface Model of Varying Complexity Using Multi-Criteria Meth. …, J Hydrometeorology, 3, pp. 181-194
Boyle DP, HV Gupta and S Sorooshian (2000), Towards Imp. Calib. of Hydrologic Models: Combining the Strengths of Manual and Automatic Methods, Water Resources Research, 36 (12), pp. 3663-3674
Gupta HV, L Bastidas, S Sorooshian, WJ Shuttleworth and ZL Yang (1999), Parameter Estimation of a Land Surface Scheme Using Multi-Criteria Methods, JGR-Atmospheres, 104 (D16), pp. 19491-19503
Gupta HV, S Sorooshian and PO Yapo (1998), Towards Imp. Calib. of Hydrologic Models: Multiple and Non-Commensurable Measures of Information, Water Resources Research, Vol. 34, No. 4, pp. 751-763

I. Spatial Regularization:
Pokhrel P, K Yilmaz and HV Gupta (2012), Multiple-Criteria Calibration of a Distributed Watershed Model using Spatial Regularization and Response Signatures, Journal of Hydrology 418-419, pp 49-60
Pokhrel P, and HV Gupta (2010), On The Use Of Spatial Regularization Strategies to Improve Calibration Of Distributed Watershed Models, Water Resources Research, 46, W01505
Pokhrel P, HV Gupta and T Wagener (2008), A Spatial Regularization Approach to Parameter Estimation for a Distributed Watershed Model, Water Resources Research, 44, W12419

J. Support for Decision-Making & Policy Analysis:
Yang Z, F Dominguez, X Zeng, H Hu, H Gupta and B Yang (2017), Impact of Irrigation Over The California Central Valley On Regional Climate, Journal of Hydrometeorology
Gupta HV, G Sapriza, J Jodar-Bermudez, J Carrera-Ramirez (2016), Circulation Pattern-Based Assessment of Projected Climate Change for a Catchment in Spain, Journal of Hydrology 
Moreno HA, DD White, HV Gupta, DA Sampson and ER Vivoni (2016), Modeling the Distributed Effects of Forest Thinning on the Long-Term Water Balance and Stream Flow Extremes for a Semi-Arid Basin in the Southwestern U.S., Hydrology and Earth Systems Science, 20, 1–27
Yang Z, F Dominguez, HV Gupta, X Zeng, L Norman, (2016), Urban Effects on Regional Climate: A Case Study in the Phoenix and Tucson ‘Sun’ Corridor, Earth Interactions
Sapriza-Azuri G, J Jodar-Bermudez, V Navarro, L Jan Slooten, J Carrera-Ramirez, and HV Gupta (2015), Impacts of Rainfall Spatial Variability on Hydrogeological Response, Water Res. Res, 51, 1300–1314
Sapriza G, J Jodar-Bermudez, J Carrera-Ramirez and HV Gupta (2015), Toward a Comprehensive Assessment of the Combined Impacts of Climate Change and Groundwater Pumping on Catchment Dynamics, Journal of Hydrology, 529, 1701–1712
Rodrigues DBB, HV Gupta, EM Mendiondo and PTS Oliveira (2015), Assessing Uncertainties in Surface Water Security: An Empirical Multi-Model Resampling Approach, Water Res. Research, 51, 9013–9028
Rodrigues DBB, HV Gupta and EM Mendiondo (2014), A Blue/Green Water-Based Accounting Framework for Assessment Of Water Security, Water Resources Research, 50, 7187–7205
Rajagopal S, F Dominguez, HV Gupta, PA Troch, CL Castro (2014), Physical Mechanisms Related to Climate-Induced Drying of Two Semi-Arid Watersheds In The Southwest US, J of Hydrometeorology, 15
Mahmoud M, HV Gupta and S. Rajagopal (2011), Scenario Dev. for Water Resources Planning and Watershed Management: Method. and Semi-Arid Region Case Study, J of Env. Modeling and Software
Mahmoud M, YQ Liu, et al. (2009), A Formal Framework for Scenario Development to Support Environmental Decision Making, Environmental Modelling & Software, 24, pp. 798-808
Liu, YQ, HV Gupta, E Springer and T Wagener (2008), Linking science with environmental decision making: Experiences from an integrated modeling approach …, Env. Mod. and Software, 23, 846-858

Research Themes: 
Decision making
Modeling and simulation
Climate and Adaptation
Climate change
Climate variability
Human dimensions
Remote sensing
Scenario planning
Water resources
Governance, Law, and Policy
Water resource management
Informatics, Modeling, and Remote Sensing
Algorithm development
Data analysis
Data cleaning and information extraction
Data mining
Data-fusion technology
Dynamical systems theory
Information theory
Mathematical and system dynamics modeling
Natural Environment and Biodiversity
Ecosystem services
Decision support
Science Engagement
Connecting science and decision making
Urban Environment
Arid lands
Climate change impacts
Water-energy nexus
Watershed hydrology
Watershed management

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