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VSP | CGC Hosts Database

Database of CGC Hosts
Project Description

University of Arizona

Contact Info

University of Arizona
Hydrology & Water Resources
1133 E James Rogers Way
The University of Arizona
Tucson, ARIZONA 85721-0518

Hoshin Vijai Gupta
Professor

Phone: (520) 275-5534
Fax: (520) 621-1422
Email: hoshin.gupta@hwr.arizona.edu
Website: http://www.hwr.arizona.edu/users/hoshin

Fields of Interest

Surface water hydrology, rainfall-runoff models, land-atmosphere transfer scheme models, flood forecasting,hydrology of semi-arid regions, prediction in ungaged basins, theory of evaluation,constraining lumped and distributed hydrologic models with observations, multi-criteria analysis,sensitivity analysis, blending expert knowledge into automated procedures, Bayesian estimation,recursive methods, uncertainty analysis, information content of data, data assimilation,application of remotely sensed data in hydrology, estimation of precipitation from remotely sensed data, relationship of scale to hydrologic process dominance, development and applications of artificial neural networks,theory and practice of model building, multi-objective stochastic recursive global optimization,interactive computer modeling, multi-resolution multi-disciplinary integrated modeling, decision analysis and decision support systems, merging hydrologic and economic models in support of decision making and policy analysis.

Description of Scientific Projects

Professor Gupta leads the Data Assimilation Group (DAG) which investigates the philosophy, theory and practice of building, calibration and application of mathematical models, and how to merge quantitative, fuzzy and/or qualitative data with models. He encourages students to understand and question conventional scientific wisdom, to examine underlying assumptions, to draw from ideas in other disciplines, and to think “outside the box.” The DAG has made contributions to the theory and practice of model calibration (including multi-criteria and Bayesian methods for assimilating information from data), model structure estimation, global optimization, parameter sensitivity analysis, and artificial neural networks. The group is also keenly interested in the application of emerging and futuristic technologies to hydrologic science, including for example distributed and embedded sensor networks, parallel processing computational tools, and multi-satellite sensors. Professional Websites: http://www.hwr.arizona.edu/users/hoshin http://web.hwr.arizona.edu/hoshin/

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