A fast and simple algorithm for calculating flow accumulation matrices from raster digital elevation

Calculating the flow accumulation matrix is an essential step for many hydrological and topographical analyses.This study gives an overview of the existing algorithms for flow accumulation calculations for singleflow direction matrices.A fast and simple algorithm for calculating flow accumulation matrices is proposed in this study.The algorithm identifies three types of cells in a flow direction matrix: source cells,intersection cells,and interior cells.It traverses all source cells and traces the downstream interior cells of each source cell until an intersection cell is encountered.An intersection cell is treated as an interior cell when its last drainage path is traced and the tracing continues with its downstream cells.Experiments are conducted on thirty datasets with a resolution of 3 m.Compared with the existing algorithms for flow accumulation calculation,the proposed algorithm is easy to implement,runs much faster than existing algorithms,and generally requires less memory space.

Efficient Priority-Flood depression filling in raster digital elevation models

Depressions in raster digital elevation models(DEM)present a challenge for extracting hydrological networks.They are commonly filled before subsequent algorithms are further applied.Among existing algorithms for filling depressions,the Priority-Flood algorithm runs the fastest.In this study,we propose an improved variant over the fastest existing sequential variant of the Priority-Flood algorithm for filling depressions in floating-point DEMs.The proposed variant introduces a series of improvements and greatly reduces the number of cells that need to be processed by the priority queue(PQ),the key data structure used in the algorithm.The proposed variant is evaluated based on statistics from 30 experiments.On average,our proposed variant reduces the number of cells processed by the PQ by around 70%.The speed-up ratios of our proposed variant over the existing fastest variant of the Priority-Flood algorithm range from 31%to 52%,with an average of 45%.The proposed variant can be used to fill depressions in large DEMs in much less time and in the parallel implementation of the Priority-Flood algorithm to further reduce the running time for processing huge DEMs that cannot be dealt with easily on single computers.