Title: The implications of data selection for regional erosion and sediment yield modelling
Authors: de Vente, Joris ×
Poesen, Jean
Govers, Gerard
Boix-Fayos, Carolina #
Issue Date: 2009
Publisher: Wiley
Series Title: Earth Surface Processes and Landforms vol:34 issue:15 pages:1994-2007
Abstract: Regional environmental models often require detailed data on topography, land cover, soil, and climate. Remote
sensing derived data form an increasingly important source of information for these models. Yet, it is often not easy to decide
what the most feasible source of information is and how different input data affect model outcomes. This paper compares the
quality and performance of remote sensing derived data for regional soil erosion and sediment yield modelling with the WATEMSEDEM
model in south-east Spain. An ASTER-derived digital elevation model (DEM) was compared with the DEM obtained from
the Shuttle Radar Topography Mission (SRTM), and land cover information from the CORINE database (CLC2000) was compared
with classifi ed ASTER satellite images. The SRTM DEM provided more accurate estimates of slope gradient and upslope drainage
area than the ASTER DEM. The classifi ed ASTER images provided a high accuracy (90%) land cover map, and due to its higher
resolution, it showed a more fragmented landscape than the CORINE land cover data. Notwithstanding the differences in quality
and level of detail, CORINE and ASTER land cover data in combination with the SRTM DEM or ASTER DEM allowed accurate
predictions of sediment yield at the catchment scale. Although the absolute values of erosion and sediment deposition were different,
the qualitative spatial pattern of the major sources and sinks of sediments was comparable, irrespective of the DEM and
land cover data used. However, due to its lower accuracy, the quantitative spatial pattern of predictions with the ASTER DEM
will be worse than with the SRTM DEM. Therefore, the SRTM DEM in combination with ASTER-derived land cover data presumably
provide most accurate spatially distributed estimates of soil erosion and sediment yield. Nevertheless, model calibration is
required for each data set and resolution and validation of the spatial pattern of predictions is urgently needed.
ISSN: 0197-9337
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Division of Geography & Tourism
× corresponding author
# (joint) last author

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