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Título : Validation of satellite precipitation (TRMM 3B43) in Ecuadorian coastal plains, Andean highlands and Amazonian rainforest
Autor: Ballari, Daniela Elisabet
Campozano Parra, Lenin Vladimir
Castro, E
Correspondencia: Ballari, D.; Civil Engineering Department, Faculty of Engineering, University of CuencaEcuador; email: daniela.ballari@ucuenca.edu.ec
Nombre de Revista: 23rd International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences Congress ISPRS 2016
Palabras clave : Detection Indexes
Ecuador
Statistical Error Metrics
Trmm
Ungagged Watershed Basins
Validation
Fecha de publicación : 12-jul-2016
Fecha de fin de embargo: 1-ene-2022
Volumen: 41
Fuente: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
metadata.dc.identifier.doi: 10.5194/isprsarchives-XLI-B8-305-2016
Editor: INTERNATIONAL SOCIETY FOR PHOTOGRAMMETRY AND REMOTE SENSING
Ciudad: 
Prague
Tipo: Article
Abstract: 
Precipitation monitoring is of utmost importance for water resource management. However, in regions of complex terrain such as Ecuador, the high spatio-temporal precipitation variability and the scarcity of rain gauges, make difficult to obtain accurate estimations of precipitation. Remotely sensed estimated precipitation, such as the Multi-satellite Precipitation Analysis TRMM, can cope with this problem after a validation process, which must be representative in space and time. In this work we validate monthly estimates from TRMM 3B43 satellite precipitation (0.25° x 0.25° resolution), by using ground data from 14 rain gauges in Ecuador. The stations are located in the 3 most differentiated regions of the country: the Pacific coastal plains, the Andean highlands, and the Amazon rainforest. Time series, between 1998-2010, of imagery and rain gauges were compared using statistical error metrics such as bias, root mean square error, and Pearson correlation; and with detection indexes such as probability of detection, equitable threat score, false alarm rate and frequency bias index. The results showed that precipitation seasonality is well represented and TRMM 3B43 acceptably estimates the monthly precipitation in the three regions of the country. According to both, statistical error metrics and detection indexes, the coastal and Amazon regions are better estimated quantitatively than the Andean highlands. Additionally, it was found that there are better estimations for light precipitation rates. The present validation of TRMM 3B43 provides important results to support further studies on calibration and bias correction of precipitation in ungagged watershed basins.
URI : https://www.scopus.com/inward/record.uri?eid=2-s2.0-84979499879&doi=10.5194%2fisprsarchives-XLI-B8-305-2016&partnerID=40&md5=b0bc7f0339bb282ba6a06eee261ac37e
http://dspace.ucuenca.edu.ec/handle/123456789/29215
ISSN : 16821750
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