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Communication incl. Poster: ID no. (ISBN etc.):  1029-7006 BibTeX citation key:  Massuel
Massuel, S. & Cappelaere, B. 2005. Hydrological model upscaling for regionalization of runoff flow and accumulation over the AMMA-Niger meso-site. Work presented at EGU General Assembly 2005, April 24—29, at Vienna, Austria.
Last Edited by: Deleted user 2008-10-01 10:39:49
 B  
Categories: General
Creators: Cappelaere, Massuel
Publisher: European Geosciences Union (Vienna, Austria)
Collection: EGU General Assembly 2005

Peer reviewed
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Abstract
The hydrological landscape of the Sahelian AMMA-Niger meso-site around Niamey, Rep. of Niger, consists of a mosaic of small endoreic catchments (a few km2) supplying storm runoff to water accumulation areas, such as ponds and humid spots. A fine-scale, spatially-distributed and physically-based hydrologic model for storm water redistribution over a catchment was developed from a 9-year field record by Cappelaere et al. (2003) and Peugeot et al. (2003). The work presented here deals with the upscaling of this fine-scale surface water model, to cover the domain of the so-called “KD basin” mesoscale entity (ca 6000 km2) over which a consistent land water cycle analysis, including the aquifer compartment, can be led.
This new, mesoscale surface water redistribution model, named Zarbhy, is made of two separate information pre-processors that compile rainfall and land surface characteristics, respectively, and that feed synthetic catchment and storm event descriptors into the core runoff submodel (Massuel et al.). The pre-processors transform fine-scale distributions over time and space, from 1-5 min and 20-40 m resolutions into lumped storm-event and catchment variables, respectively, which have been identified as efficient runoff predictors. The rainfall pre-processor filters-aggregates-and-kriges point storm hyetographs from the mesoscale ground raingauge network into a catchmentblocked, scalar spatial field for runoff-prone event rainfall. The land surface preprocessor extracts information from the DEM and land surface maps to synthesize maps of runoff-controlling physiographic catchment descriptors. The core catchment-×-event runoff submodel yields the space-time distribution of runoff volumes contributed to the 377 water accumulating sites identified over the KD basin.
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