A novel parallel depression removing algorithm for hydrology analysis in digital elevation models

The creation of “depressionless” DEMs is the essential work of hydrological analysis, which is usually a time-consuming task, especially for huge terrain datasets. This paper proposes an improved and versatile parallel algorithm which consists of three steps. Firstly, a parallel conflict detection based on flow direction of the border of each partition is proposed to check out the depressions on the boundary. Secondly, the depressions detected are filled by a bigger DEM received from other processors. Based on the conflict detection, the parallel filling process is done at last. Finally, the efficiency and scalability of the algorithm are tested on the DEMs of different size.