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dc.contributor.authorMéndez-Morales, Maikel
dc.contributor.authorCalvo-Valverde, Luis Alexander
dc.date.accessioned2018-03-21T18:31:15Z
dc.date.available2018-03-21T18:31:15Z
dc.date.issued2016
dc.identifierhttps://www.scopus.com/record/display.uri?eid=2-s2.0-84997795554&doi=10.1016%2fj.proeng.2016.07.595&origin=inward&txGid=d4035bb978ce1f3e36a7bf9ae33405b7es
dc.identifier.citationMendez, M., & Calvo-Valverde, L. (2016). Assessing the performance of several rainfall interpolation methods as evaluated by a conceptual hydrological model. Procedia Engineering, 154, 1050-1057es
dc.identifier.urihttps://hdl.handle.net/2238/9665
dc.descriptionArtículoes
dc.description.abstractThe objective of this study was to assess the performance of several rainfall interpolation methods as evaluated by a conceptual hydrological model. To this purpose, the upper Toro River catchment (43.15 km2) located in Costa Rica was selected as case study. Deterministic and geostatistical interpolation methods were selected to generate time-series of daily and hourly average rainfall over a period of 10 years (2001-2010). These time-series were used as inputs for the HBV-TEC hydrological model and were individually calibrated against observed streamflow data. Based on model results, the performance of the deterministic methods can be said to be comparable to that of the geostatistical methods at daily time-steps. However, at hourly time-steps, deterministic methods considerably outperformed geostatistical methods.es
dc.language.isoenges
dc.publisherScopuses
dc.relation.hasversion10.1016/j.proeng.2016.07.595es
dc.rightsacceso abierto*
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.source12th International Conference on Hydroinformatics, HIC 2016es
dc.subjectHBV-TECes
dc.subjectPESTes
dc.subjectLluviaes
dc.subjectMétodoses
dc.subjectResearch Subject Categories::FORESTRY, AGRICULTURAL SCIENCES and LANDSCAPE PLANNINGes
dc.titleAssessing the performance of several rainfall interpolation methods as evaluated by a conceptual hydrological modeles
dc.typeinfo:eu-repo/semantics/articlees


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