The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLI-B8
https://doi.org/10.5194/isprs-archives-XLI-B8-159-2016
https://doi.org/10.5194/isprs-archives-XLI-B8-159-2016
22 Jun 2016
 | 22 Jun 2016

ASSESSMENT OF FLOODED AREAS PROJECTIONS AND FLOODS POTENTIAL IMPACTS APPLYING REMOTE SENSING IMAGERY AND DEMOGRAPHIC DATA

D. A. Rodriguez, F. Carriello, P. J. F. Fernandes, L. Garofolo Lopes, and J. L. Siqueira Júnior

Keywords: Floods, Climate Change Impacts, Climate Change Vulnerability

Abstract. Assessing vulnerability and potential impacts associated with extreme discharges requires an accurate topographic description in order to estimate the extension of flooded areas. However, in most populated regions, topographic data obtained by in-situ measurements is not available. In this case, digital elevation models derived from remote sensing date are usually applied. Moreover, this digital elevation models have intrinsic errors that introduce bigger uncertainty in results than the associated to hydrological projections. On the other hand, estimations of flooded areas through remote sensing images provide accurate information, which could be used for the construction of river level-flooded area relationships regarding vulnerability assessment. In this work, this approach is applied for the city of Porto Velho in the Brazilian Amazonia to assess potential vulnerability to floods associated with climate change projections. The approach is validated using census data, provided by the Brazilian Institute of Geography and Statistics, and information about socio-economical injuries associated to historical floods, provided by the Brazilian Civil Defence. Hydrological projections under climate change are carried out using several downscaling of climate projections as inputs in a hydrological model. Results show more accurate estimation of flood impacts than the obtained using digital elevation models derivate from remote sensing data. This reduces uncertainties in the assessment of vulnerability to floods associated with climate change in the region.