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dc.contributor.authorBendix, Jorg-
dc.contributor.authorGuallpa Guallpa, Mario Xavier-
dc.contributor.authorOrellana Alvear, Johanna Marlene-
dc.date.accessioned2020-05-16T00:13:05Z-
dc.date.available2020-05-16T00:13:05Z-
dc.date.issued2019-
dc.identifier.issn2073-4441-
dc.identifier.urihttp://dspace.ucuenca.edu.ec/handle/123456789/34323-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85066302976&origin=inward-
dc.descriptionWeather radar networks are an excellent tool for quantitative precipitation estimation (QPE), due to their high resolution in space and time, particularly in remote mountain areas such as the Tropical Andes. Nevertheless, reduction of the temporal and spatial resolution might severely reduce the quality of QPE. Thus, the main objective of this study was to analyze the impact of spatial and temporal resolutions of radar data on the cumulative QPE. For this, data from the world's highest X-band weather radar (4450 m a.s.l.), located in the Andes of Ecuador (Paute River basin), and from a rain gauge network were used. Different time resolutions (1, 5, 10, 15, 20, 30, and 60 min) and spatial resolutions (0.5, 0.25, and 0.1 km) were evaluated. An optical flow method was validated for 11 rainfall events (with different features) and applied to enhance the temporal resolution of radar data to 1-min intervals. The results show that 1-min temporal resolution images are able to capture rain event features in detail. The radar-rain gauge correlation decreases considerably when the time resolution increases (r from 0.69 to 0.31, time resolution from 1 to 60 min). No significant difference was found in the rain total volume (3%) calculated with the three spatial resolution data. A spatial resolution of 0.5 km on radar imagery is suitable to quantify rainfall in the Andes Mountains. This study improves knowledge on rainfall spatial distribution in the Ecuadorian Andes, and it will be the basis for future hydrometeorological studies. © 2019 by the authors.-
dc.description.abstractWeather radar networks are an excellent tool for quantitative precipitation estimation (QPE), due to their high resolution in space and time, particularly in remote mountain areas such as the Tropical Andes. Nevertheless, reduction of the temporal and spatial resolution might severely reduce the quality of QPE. Thus, the main objective of this study was to analyze the impact of spatial and temporal resolutions of radar data on the cumulative QPE. For this, data from the world’s highest X-band weather radar (4450 m a.s.l.), located in the Andes of Ecuador (Paute River basin), and from a rain gauge network were used. Different time resolutions (1, 5, 10, 15, 20, 30, and 60 min) and spatial resolutions (0.5, 0.25, and 0.1 km) were evaluated. An optical flow method was validated for 11 rainfall events (with different features) and applied to enhance the temporal resolution of radar data to 1-min intervals. The results show that 1-min temporal resolution images are able to capture rain event features in detail. The radar−rain gauge correlation decreases considerably when the time resolution increases (r from 0.69 to 0.31, time resolution from 1 to 60 min). No significant difference was found in the rain total volume (3%) calculated with the three spatial resolution data. A spatial resolution of 0.5 km on radar imagery is suitable to quantify rainfall in the Andes Mountains. This study improves knowledge on rainfall spatial distribution in the Ecuadorian Andes, and it will be the basis for future hydrometeorological studies.-
dc.language.isoes_ES-
dc.sourceWater (Switzerland)-
dc.subjectRainfall advection-
dc.subjectRadar temporal sampling error-
dc.subjectQPE-
dc.subjectWeather radar-
dc.subjectEcuador Tropical Andes-
dc.subjectOptical flow method-
dc.titleTropical Andes radar precipitation estimates need high temporal and moderate spatial resolution-
dc.typeARTÍCULO-
dc.ucuenca.idautor0302224068-
dc.ucuenca.idautor0104162268-
dc.ucuenca.idautorSgrp-2762-3-
dc.identifier.doi10.3390/w11051038-
dc.ucuenca.versionVersión publicada-
dc.ucuenca.areaconocimientounescoamplio05 - Ciencias Físicas, Ciencias Naturales, Matemáticas y Estadísticas-
dc.ucuenca.afiliacionOrellana, J., Universidad de Cuenca, Departamento de Recursos Hídricos y Ciencias Ambientales, Cuenca, Ecuador; Orellana, J., University of Marburg, Marburg, Alemania-
dc.ucuenca.afiliacionBendix, J., University of Marburg, Marburg, Alemania-
dc.ucuenca.afiliacionGuallpa, M., ETAPA, Cuenca , Ecuador; Guallpa, M., Universidad de Cuenca, Departamento de Recursos Hídricos y Ciencias Ambientales, Cuenca, Ecuador; Guallpa, M., Universidad de Cuenca, Facultad de Ingeniería, Cuenca, Ecuador-
dc.ucuenca.correspondenciaGuallpa Guallpa, Mario Xavier, mario.x.guallpa@gmail.com-
dc.ucuenca.volumenVolumen 11, número 5-
dc.ucuenca.indicebibliograficoSCOPUS-
dc.ucuenca.factorimpacto0.67-
dc.ucuenca.cuartilQ2-
dc.ucuenca.numerocitaciones0-
dc.ucuenca.areaconocimientofrascatiamplio1. Ciencias Naturales y Exactas-
dc.ucuenca.areaconocimientofrascatiespecifico1.5 Ciencias de la Tierra y el Ambiente-
dc.ucuenca.areaconocimientofrascatidetallado1.5.10 Recursos Hídricos-
dc.ucuenca.areaconocimientounescoespecifico052 - Medio Ambiente-
dc.ucuenca.areaconocimientounescodetallado0521 - Ciencias Ambientales-
dc.ucuenca.urifuentehttps://www.mdpi.com/2073-4441/11/5-
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