Abstract
In hydrological modeling, the longest flow path is an important feature used to characterize a catchment. Many existing GIS platforms offer dedicated software tools for its identification and delineation, generally implementing methods based on searching through the flow direction data. Unfortunately, currently available algorithms for this task often turn out to be inefficient, especially when working with modern large datasets. Moreover, existing methods often rely on incorrect assumptions or perform calculations in a way that can lead to precision issues. In this work, new parallel algorithms were developed, tested and presented. Measurements show that two of the newly proposed implementations are able to identify the longest flow paths in significantly less time compared with other existing methods.
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