Remote sensing and GIS applications of surface and near-surface hydromorphological features in Darfur region, Sudan

Abstract

Groundwater modelling and mapping in a region partly inaccessible using traditional techniques is practically very difficult, and time and cost consuming. However, integration of remote sensing and GIS enables more reliable mapping and analysis of hydromorphological elements such as palaeolakes. In the present study, a set of automated morphometric techniques of fitting a bivariate quadratic surface in a moving window of size 3 × 3 was used and modified to map and analyse hydromorphological elements in northwestern Sudan. Geomorphometry results indicate that the palaeodrainage network incision and depressions may have received most of the rainwater during late Quaternary wet phases. The results revealed that of the total 2000 km² coverage of the unnamed depression, about 49.6% was classified as accumulation zone with a recharge area of about 992 km², while the Wadi Fesh Fesh and Oyo depressions were shown to have the smallest areas of accumulation zone, approximately 31.3% and 37.3%, respectively. Validation of the methods was made by comparing trends and textural features from a Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) with 30 m spatial resolution Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEM and 0.6 m spatial resolution Quickbird images and geological maps of the study area. The maps obtained showed a strong correlation, indicating that the proposed methods are very efficient tools for regional mapping and analysing hydromorphological elements in arid regions and remote and inaccessible regions.

Acknowledgements

The authors would like to thank Prof. Peter Guth from USA Academic Navy, the Earth Remote Sensing Data Analysis Centre (ERSDAC), Japan, the NASA Land Processes Distributed Active Archive Center and the User Services USGS Earth Resources Observation and Science (EROS), and the Consortium for Spatial Information (CSI) of the Consultative Group for International Agricultural Research (CGIAR) for providing and distributing scientific advice and remotely sensed data.