Reference : Different methods for spatial interpolation of rainfall data for operational hydrolog...
Scientific journals : Article
Physical, chemical, mathematical & earth Sciences : Earth sciences & physical geography
Different methods for spatial interpolation of rainfall data for operational hydrology and hydrological modeling at watershed scale: a review
[en] Méthodes de spatialisation de données pluviométriques dédiées à l’hydrologie opérationnelle et à la modélisation hydrologique à l’échelle du bassin versant : une revue bibliographique
Ly, Sarann mailto [Université de Liège - ULg > > > Doct. sc. agro. & ingé. biol.]
Charles, Catherine mailto [Université de Liège - ULg > Sciences agronomiques > Statistique, Inform. et Mathém. appliquée à la bioingénierie >]
Degré, Aurore mailto [Université de Liège - ULg > Sciences et technologie de l'environnement > Systèmes Sol-Eau >]
Biotechnologie, Agronomie, Société et Environnement = Biotechnology, Agronomy, Society and Environment [=BASE]
Presses Agronomiques de Gembloux
Yes (verified by ORBi)
[en] Rainfall ; precipitation ; spatial interpolation ; geostatistics ; kriging ; Thiessen polygon ; Inverse Distance Weighting (IDW) ; hydrological modeling
[en] Watershed management and hydrological modeling require data related to the very important matter of precipitation, often measured using raingages or weather stations. Hydrological models often require a preliminary spatial interpolation as part of the modeling process. The success of spatial interpolation varies according to the type of model chosen, its mode of geographical management and the resolution used. The quality of a result is determined by the quality of the continuous spatial rainfall which ensues from the interpolation method used. The objective of this article is to review the existing methods for interpolation of rainfall data that are usually required in hydrological modeling. We review the basis for the application of certain common methods and geostatistical approaches used in interpolation of rainfall. Previous studies have highlighted the need for new research to investigate ways of improving the quality of rainfall data and ultimately, the quality of hydrological modeling.
Univ. of Liège, Gembloux Agro-Bio Tech, Soil-Water Systems ; Institute of Technology of Cambodia, Department of Rural Engineering
Commission universitaire pour le Développement - CUD
Researchers ; Professionals ; General public ; Others

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