H
Hoshin V. Gupta
Researcher at University of Arizona
Publications - 315
Citations - 37832
Hoshin V. Gupta is an academic researcher from University of Arizona. The author has contributed to research in topics: Hydrological modelling & Precipitation. The author has an hindex of 75, co-authored 300 publications receiving 32703 citations. Previous affiliations of Hoshin V. Gupta include University of California, Davis & University of Illinois at Urbana–Champaign.
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Understanding uncertainty in distributed flash flood forecasting for semiarid regions
Soni Yatheendradas,Thorsten Wagener,Hoshin V. Gupta,Carl L. Unkrich,David C. Goodrich,M. Schaffner,A. M. Stewart +6 more
TL;DR: In this paper, the authors used a semiarid, physics-based, and spatially distributed watershed model driven by high-resolution radar rainfall input to evaluate a real-time forecast and warning system based on a rainfall runoff model.
Diurnal Variability of Tropical Rainfall Retrieved From the Combined GOES and TRMM Satellite Information
TL;DR: In this paper, the results demonstrate pronounced diurnal variability of tropical rainfall intensity at synoptic and regional scales over a large domain of the tropical Pacific Ocean, especially over the ITCZ and the eastern Asia.
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Spatial patterns in thunderstorm rainfall events and their coupling with watershed hydrological response
TL;DR: In this article, the spatial rainfall information of air mass thunderstorms and link it with a watershed hydrological model is presented. But the authors focus on a single intense rain cell (out of the five cells decomposed from the storm) in a semi-arid watershed.
Journal ArticleDOI
Trends in water balance components across the Brazilian Cerrado
Paulo Tarso Sanches de Oliveira,Mark A. Nearing,M. Susan Moran,David C. Goodrich,Edson Wendland,Hoshin V. Gupta +5 more
TL;DR: In this article, the authors assess the water balance of the Brazilian Cerrado based on remotely sensed estimates of precipitation (TRMM), evapotranspiration (MOD16), and terrestrial water storage (GRACE) for the period from 2003 to 2010.
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Toward improved identifiability of hydrologic model parameters: The information content of experimental data
TL;DR: In this paper, a parameter identification method based on the localization of information (PIMLI) is proposed to increase information retrieval from the data by inferring the location and type of measurements that are most informative for the model parameters.