A GPU algorithm for identifying the longest flow paths in catchments

Abstract

The longest flow path is one of the key features of a catchment, commonly considered in hydrological analysis and modeling. Recent literature highlights that identifying the longest flow paths using existing software tools is time-consuming. Over the last few years, attempts have been made to develop more computationally efficient algorithms for this particular task. This paper extends previously published research and presents a new GPU algorithm designed for fast identification of the longest flow paths using DEM-derived flow directions. Performance measurements show significantly shorter execution times compared to other existing algorithms for the same task. Additionally, this algorithm is able to efficiently process multiple catchments in the same run, offering further performance improvements.