High-performance watershed delineation algorithm for GPU using CUDA and OpenMP. (February 2023)

• Record Type: Journal Article
• Authors: Kotyra, Bartłomiej
• Is Part Of: Environmental modelling & software. Volume 160(2023)
• Publication Date: 2023-02
• Subjects: Watershed delineation -- GIS -- Parallel algorithms -- GPU -- CUDA -- OpenMP; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2022.105613
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Watershed delineation is one of the fundamental tasks in hydrological studies. Tools for extracting watersheds from digital elevation models and flow direction rasters are commonly implemented in GIS software packages. However, the performance of available techniques and algorithms often turns out to be far from sufficient, especially when working with large datasets. While modern hardware offers high computing performance through massive parallelism, there is still a need for algorithms that can effectively use these capabilities. This paper proposes an algorithm for rapid watershed delineation directly from flow direction rasters, using the possibilities offered by modern GPU devices. Performance measurements show a significant reduction in execution time compared to other parallel solutions proposed for this task in the literature. Moreover, this implementation makes it possible to delineate multiple watersheds from the same dataset simultaneously, each having one or more outlet cells, with virtually no additional computational cost. Highlights: This paper proposes a fast, parallel watershed delineation algorithm for GPU. Watersheds are rapidly delineated directly from basic flow direction data. Results show a significant reduction of computing time compared to other solutions. Multiple watersheds can be delineated simultaneously with no additional cost.