Spatial and temporal rainfall variability in mountainous areas: A case study from the south Ecuadorian Andes

Journal of Hydrology

dc.creatorBuytaert, Wouter
dc.creatorCélleri, Rolando
dc.creatorWillems, Patrick
dc.creatorBievre, Bert De
dc.creatorWyseure, Guido
dc.date2015-06-11T13:34:34Z
dc.date2015-06-11T13:34:34Z
dc.date2006-10-15
dc.date.accessioned2018-03-14T20:12:26Z
dc.date.available2018-03-14T20:12:26Z
dc.identifierhttp://dspace.ucuenca.edu.ec/handle/123456789/22053
dc.identifierdoi:10.1016/j.jhydrol.2006.02.031
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1129393
dc.descriptionParticularly in mountain environments, rainfall can be extremely variable in space and time. For many hydrological applications such as modelling, extrapolation of point rainfall measurements is necessary. Decisions about the techniques used for extrapolation, as well as the adequacy of the conclusions drawn from the final results, depend heavily on the magnitude and the nature of the uncertainty involved. In this paper, we examine rainfall data from 14 rain gauges in the western mountain range of the Ecuadorian Andes. The rain gauges are located in the western part of the rio Paute basin. This area, between 3500 and 4100 m asl, consists of mountainous grasslands, locally called páramo, and acts as major water source for the inter-Andean valley. Spatial and temporal rainfall patterns were studied. A clear intraday pattern can be distinguished. Seasonal variation, on the other hand, is low, with a difference of about 100 mm between the dryest and the wettest month on an average of about 100 mm month−1, and only 20% dry days throughout the year. Rain gauges at a mutual distance of less than 4000 m are strongly correlated, with a Pearson correlation coefficient higher than 0.8. However, even within this perimeter, spatial variability in average rainfall is very high. Significant correlations were found between average daily rainfall and geographical location, as well as the topographical parameters slope, aspect, topography. Spatial interpolation with thiessen gives good results. Kriging gives better results than thiessen, and the accuracy of both methods improves when external trends are incorporated.
dc.descriptionvol. 329; no. 3-4
dc.formatapplication/pdf
dc.languageeng
dc.rightsopenAccess
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/3.0/ec/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/3.0/ec/
dc.sourceinstname:Universidad de Cuenca
dc.sourcereponame:Repositorio Digital de la Universidad de Cuenca
dc.subjectRAINFALL VARIABILITY
dc.subjectMOUNTAIN ENVIRONMENTS
dc.subjectINTERPOLATION
dc.subjectKRIGING
dc.subjectTHIESSEN
dc.subjectECUADOR
dc.titleSpatial and temporal rainfall variability in mountainous areas: A case study from the south Ecuadorian Andes
dc.titleJournal of Hydrology
dc.typeArtículos de revistas


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