MORPHOMETRIC ANALYSIS OF THE BASIN LOW MIDDLE SÃO FRANCISCO RIVER

Authors

  • Madson T. Silva Doutorando da Universidade Federal de Campina Grande
  • Vicente de P. R. da Silva UFCG
  • Enio Pereira de Souza
  • Verônica G. de Oliveira

DOI:

https://doi.org/10.29150/jhrs.v4.8.p168-174

Keywords:

Drainage network, elevation digital model, geoprocessing

Abstract

This study aimed to generate the components for morphometric analysis of the watershed of the São Francisco River Lower Basin from geoprocessing and remote sensing surface. SRTM data were used for preparation of digital elevation model (DEM), elements such as flow accumulation, flow direction, flow length and others were obtained by processing ArcHydro tool of ArcGIS 9.3 software. The results showed that the São Francisco River Low middle Basin has a total area of 110.446,0 km ² and a perimeter of 3.834,8 km, the drainage network is moderately branched having a total length of 22.283,6 km with a main course of 720 km, the basin showed a more elongated shape, with a density of less than 0.2 km/km2 drainage as well as low-density area, the predominant class of slope is the floodplain type and plan to undulated represented about 90% of the total area the basin. Classes roofing composed of arborel and shrubby Caatinga, shrubby low Caatinga and Grasslands dominate the landscape occupying an area of 60.385,7; 18.998,5 and 22.737,5 km2, respectively. Different landforms were identified in the watershed based on SRTM (DEM) data with 90 m spatial resolution. GIS techniques were thus characterized by high precision mapping and measurement of morphometric indices and revealed themselves as a tool with great potential for watershed management.

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Published

2015-05-06

How to Cite

Silva, M. T., da Silva, V. de P. R., de Souza, E. P., & de Oliveira, V. G. (2015). MORPHOMETRIC ANALYSIS OF THE BASIN LOW MIDDLE SÃO FRANCISCO RIVER. Journal of Hyperspectral Remote Sensing, 4(8), 168–174. https://doi.org/10.29150/jhrs.v4.8.p168-174

Issue

Vol. 4 No. 8 (2014): Journal of Hyperspectral Remote Sensing

Section

Hyperspectral remote sensing and Atmosphere

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