Articles | Volume 21, issue 7
https://doi.org/10.5194/hess-21-3543-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-3543-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Hydrological modeling of the Peruvian–Ecuadorian Amazon Basin using GPM-IMERG satellite-based precipitation dataset
Ricardo Zubieta
CORRESPONDING AUTHOR
Subdirección de Ciencias de la Atmósfera e Hidrósfera
(SCAH), Instituto Geofísico del Perú (IGP), Lima, Peru
Programa de Doctorado en Recursos Hídricos, Universidad Nacional
Agraria La Molina, Peru
Augusto Getirana
Hydrological Sciences Laboratory, NASA Goddard Space Flight Center,
Greenbelt, MD, USA
Earth System Science Interdisciplinary Center, College Park, MD, USA
Jhan Carlo Espinoza
Subdirección de Ciencias de la Atmósfera e Hidrósfera
(SCAH), Instituto Geofísico del Perú (IGP), Lima, Peru
Programa de Doctorado en Recursos Hídricos, Universidad Nacional
Agraria La Molina, Peru
Waldo Lavado-Casimiro
Servicio Nacional de Meteorología e Hidrología (SENAMHI),
Lima, Peru
Programa de Doctorado en Recursos Hídricos, Universidad Nacional
Agraria La Molina, Peru
Luis Aragon
Programa de Doctorado en Recursos Hídricos, Universidad Nacional
Agraria La Molina, Peru
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66 citations as recorded by crossref.
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- Reliability of GPM IMERG Satellite Precipitation Data for Modelling Flash Flood Events in Selected Watersheds in the UAE M. Hamouda et al. 10.3390/rs15163991
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4 citations as recorded by crossref.
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- Assessment of IMERG-V06, TRMM-3B42V7, SM2RAIN-ASCAT, and PERSIANN-CDR Precipitation Products over the Hindu Kush Mountains of Pakistan, South Asia A. Hamza et al. 10.3390/rs12233871
- Impact of local versus global datasets on hydrological responses in Mahanadi River basin in India S. Naha et al. 10.1080/02626667.2023.2193700
- Identification and inter‐comparison of appropriate long‐term precipitation datasets using decision tree model and statistical matrix over China M. Faiz et al. 10.1002/joc.7113
Discussed (final revised paper)
Discussed (preprint)
Latest update: 24 Dec 2024
Short summary
This paper indicates that precipitation data derived from GPM-IMERG correspond more closely to TMPA V7 than TMPA RT datasets, but both GPM-IMERG and TMPA V7 precipitation data tend to overestimate, in comparison to observed rainfall (by 11.1 % and 15.7 %, respectively). Statistical analysis indicates that GPM-IMERG is as useful as TMPA V7 or TMPA RT datasets for estimating observed streamflows in Andean–Amazonian regions (Ucayali Basin, southern regions of the Amazon Basin of Peru and Ecuador).
This paper indicates that precipitation data derived from GPM-IMERG correspond more closely to...