Handling Challenging Catchment Delineation Data

Asif Khan, who is a graduate student working with me, has recently published a paper in the Journal of Hydrology on one finding from some of his (ongoing) Ph.D. thesis work. The abstract reads:

Extraction of watershed areas from Digital Elevation Models (DEMs) is increasingly required in a variety of environmental analyses. It is facilitated by the availability of DEMs based on remotely sensed data, and by Geographical Information System (GIS) software. However, accurate delineation depends on the quality of the DEM and the methodology adopted. This paper considers automated and supervised delineation in a case study of the Upper Indus Basin (UIB), Pakistan, for which published estimates of the basin area show significant disagreement, ranging from 166,000 to 266,000 km 2 . Automated delineation used Arc- GIS Archydro and hydrology tools applied to three good quality DEMs (two from SRTM data with 90m resolution, and one from 30m resolution ASTER data). Automatic delineation defined a basin area of c.440,000 km 2 for the UIB, but included a large area of internal drainage in the western Tibetan Plateau. discrepancies between different estimates reflect differences in the initial extent of the DEM used for watershed delineation, and the unchecked effect of iterative pit-filling of the DEM (going beyond the filling of erroneous pixels to filling entire closed basins). For the UIB we have identified critical points where spurious addition of catchment area has arisen, and use Google Earth to examine the geomorphology adjacent to these points, and also examine the basin boundary data provided by the HydroSHEDS database. We show that the Pangong Tso watershed and some other areas in the western Tibetan plateau are not part of the UIB, but are areas of internal drainage. Our best estimate of the area of the Upper Indus Basin (at Besham Qila) is 164,867 km 2 based on the SRTM DEM, and 164,853 km 2 using the ASTER DEM). This matches the catchment area measured by WAPDA SWHP. An important lesson from this investigation is that one should not rely on automated delineation, as iterative pit-filling can produce spurious drainage networks and basins, when there are areas of internal drainage nearby.

It is shown that discrepancies between different estimates reflect differences in the initial extent of the DEM used for watershed delineation, and the unchecked effect of iterative pit-filling of the DEM (going beyond the filling of erroneous pixels to filling entire closed basins). For the UIB we have identified critical points where spurious addition of catchment area has arisen, and use Google Earth to examine the geomorphology adjacent to these points, and also examine the basin boundary data provided by the HydroSHEDS database. We show that the Pangong Tso watershed and some other areas in the western Tibetan plateau are not part of the UIB, but are areas of internal drainage. Our best estimate of the area of the Upper Indus Basin (at Besham Qila) is 164,867 km 2 based on the SRTM DEM, and 164,853 km 2 using the ASTER DEM). This matches the catchment area measured by WAPDA SWHP. An important lesson from this investigation is that one should not rely on automated delineation, as iterative pit-filling can produce spurious drainage networks and basins, when there are areas of internal drainage nearby.

This work stemmed from a realization that was a significant problem in the literature in that estimates of the catchment size varied widely – one author having the catchment as being about 70% larger than another. This suggested that there was likely to be a problem with the delineation algorithm or dataset, and indeed we found it is the interaction of both these factors in this particular case that leads to thes quite divergent estimates.