Blue tab
Green tab
Brown Tab

Preliminary results (examples)

 

 

Test Site 3. - Makmal - Hierarchised drainage pattern computation from DEMs


Background

Surface drainage is a major contamination pathway in the source – pathway – receptor paradigm commonly used in mining-related risk assessment. It is hence important to make available a comprehensive drainage pattern that provides information about the most probable downstream flow, perennial or not, from a potential contamination source.
The identification of drainage pathways and runoff contributing areas based on DEMs is hence important in assessing the potential downstream contamination of rivers and soils from a given contamination source, being a pit, a waste heap, a mining facility or even a contaminated soil or area.


Methods

Several flow accumulation algorithms can be used to compute a drainage pattern from a DEM grid or image (Wilson et al 2008).
The ArcGis Spatial analyst algorithm uses a deterministic approach (Jenson and Domingue, 1988) based on the maximum slope, i.e. the algorithm directs flow from each grid cell to one of eight nearest neighbor cells based on slope gradient (selecting the greatest slope).  This algorithm tends to produce parallel flow paths on planar surfaces.

The stochastic algorithm used here, developed with J. Fairfield (University of Virginia) introduces a degree of randomness to break up this unwanted parallel flow paths; This algorithm starts by identifying all the neighboring downslope cells, then calculates the slope gradients in each of these directions, and finally extracts random numbers from a table to direct the flow to one of these candidate cells. The random numbers are allocated on a slope-weighted basis such that the potential flow paths with the steepest gradients have the greatest probability of being selected, and the overall flow pattern more or less matches the one produced with the deterministic approach.

Illustration of determination process for flow patterns
Illustration of determination process for flow patterns


Results

Attempts over Makmal using SRTM and ASTER DEM

Flow accumulation algorithms have been applied to both SRTM and ASTER DEMS over the Makmal area. Both results are very similar, but small differences are likely due to the better resolution of the ASTER DEM which introduces possible artifacts, one of them being related to a dirt road some 10 km west of Kazarman.

There are only few differences between the drainage computed from SRTM DEM and from ASTER DEM. Both show that the surface drainage coming out from the Makmal tailings dam should not directly affect the town of Kazarman, as the town is not located downstream of the tailings dam. Moreover, in case of dam failure, it appears unlikely the town of Kazarman will be affected by related mudflow, apart from the western end of the town. The later has to be confirmed however.

Click on image to see it full-sized.

Makmal SRTM drainage image   Makmal SRTM drainage and slopes image
     
Drainage system computed from SRTM Digital Elevation model (DEM), overlaid on the colored (according to elevation) and shaded SRTM   Same drainage overlaid on slope map computed from SRTM DEM
     
Makmal ASTRA drainage image   Makmal ASTER drainage and slopes image
     
Drainage system computed from ASTER DEM overlaid on the colored (according to elevation) and shaded ASTER DEM   Same drainage overlaid on slope map computed from ASTER DEM
     
Makmal Drainage ASTER overlaid on WVII shaded image    
     
The drainage system computed from ASTER DEM is overlaid on the colored (according to elevation) and shaded DEM computed from the WorldView stereo pair images.