Getirana Augusto, Bonnet Marie-Paule, Martinez Jean-Michel. (2009). Evaluating parameter effects in a DEM 'burning' process based on land cover data. Hydrological Processes, 23 (16), p. 2316-2325. ISSN 0885-6087.
Titre du document
Evaluating parameter effects in a DEM 'burning' process based on land cover data
Hydrological Processes, 2009,
23 (16), p. 2316-2325 ISSN 0885-6087
Over the last years, various methods regarding the use of digital land cover data to change digital elevation models (DEMs) have been reported in the literature. Usually, these methods rely on digital river networks (DRNs) or digital river and lake networks (DRLNs) to force preferential flow directions of pixels composing a DEM to get more realistic hydrological information, and reduce the accumulated number of errors in the information acquisition process. More recently, a new method that takes advantage of spatial distribution of rivers and floodplains derived from classified radar images has been presented. The method is based on a double 'burning' process. The first process uses stream lines to reduce elevations in the DEM (traditional stream burning approach-SB approach) and the second uses the floodplains to create valleys forcing the drainage of these areas to the main river. This approach, referred to as floodplain burning approach (FB approach), was applied to a basin in the Amazon basin. It greatly improved the results compared to the SB approach. However, this method requires the calibration of various parameters to represent accurately land cover types. This study proposes a comprehensive evaluation of the influence of these parameters on the DEM-based hydrological information acquisition and on the original DEM. Consequently, a method of parameters set selection is provided. The method was applied to a sub-basin of the Negro River basin in Amazonia. Several parameter combinations were evaluated in the watershed delineation process. Particular attention was paid to whether those parameters with a greater impact on DEM yielded better results in the case study. However, these DEM changes can be reduced with the knowledge of vegetation's heights, the vegetation having a substantial effect on remote acquisition of DEMs in tropical forests.
