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dc.contributor.authorMeersmans, J
dc.contributor.authorVan Weverberg, K
dc.contributor.authorDe Baets, S
dc.contributor.authorDe Ridder, F
dc.contributor.authorPalmer, SJ
dc.contributor.authorvan Wesemael, B
dc.contributor.authorQuine, TA
dc.date.accessioned2016-11-16T09:22:40Z
dc.date.issued2016-06-09
dc.description.abstractAccurate precipitation maps are essential for ecological, environmental, element cycle and hydrological models that have a spatial output component. It is well known that topography has a major influence on the spatial distribution of precipitation and that increasing topographical complexity is associated with increased spatial heterogeneity in precipitation. This means that when mapping precipitation using classical interpolation techniques (e.g. regression, kriging, spline, inverse distance weighting, etc.), a climate measuring network with higher spatial density is needed in mountainous areas in order to obtain the same level of accuracy as compared to flatter regions. In this study, we present a mean total annual precipitation mapping technique that combines topographical information (i.e. elevation and slope orientation) with average total annual rain gauge data in order to overcome this problem. A unique feature of this paper is the identification of the scale at which topography influences the precipitation pattern as well as the direction of the dominant weather circulation. This method was applied for Belgium and surroundings and shows that the identification of the appropriate scale at which topographical obstacles impact precipitation is crucial in order to obtain reliable mean total annual precipitation maps. The dominant weather circulation is determined at 260°. Hence, this approach allows accurate mapping of mean annual precipitation patterns in regions characterized by rather high topographical complexity using a climate data network with a relatively low density and/or when more advanced precipitation measurement techniques, such as radar, aren't available, for example in the case of historical data.en_GB
dc.identifier.citationVol. 540, pp. 96-105en_GB
dc.identifier.doi10.1016/j.jhydrol.2016.06.013
dc.identifier.urihttp://hdl.handle.net/10871/24457
dc.language.isoenen_GB
dc.publisherElsevieren_GB
dc.relation.sourceWe are grateful to the National Meteorological Institutes of Belgium (Koninklijk Meteorologisch Instituut (KMI)), France (Meteo France), The Netherlands (Koninklijk Nederlands Meteorologisch Instuut (KNMI)) and Germany (Deutscher Wetterdienst (DWD)) for providing the data.en_GB
dc.relation.urlhttp://www.sciencedirect.com/science/article/pii/S002216941630364Xen_GB
dc.rights.embargoreasonPublisher policyen_GB
dc.rightsThis is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.en_GB
dc.subjectPrecipitationen_GB
dc.subjectInterpolationen_GB
dc.subjectWeather circulationen_GB
dc.subjectSlopeen_GB
dc.subjectAltitudeen_GB
dc.subjectTopographyen_GB
dc.titleMapping mean total annual precipitation in Belgium, by investigating the scale of topographic control at the regional scaleen_GB
dc.typeArticleen_GB
dc.identifier.issn0022-1694
dc.identifier.journalJournal of Hydrologyen_GB


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