4.7 Article

Geoscience model service integrated workflow for rainstorm waterlogging analysis

Journal

INTERNATIONAL JOURNAL OF DIGITAL EARTH
Volume 14, Issue 7, Pages 851-873

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/17538947.2021.1898686

Keywords

Geoscience model; workflow; waterlogging; OGC; geospatial service

Funding

  1. National Key Research and Development Program of China [2018YFB2100504, 2017YFB0504202]
  2. National Science Foundation of China (NSFC) [41871312]
  3. Fundamental Research Funds for the Central Universities [2042019kf0226]
  4. Hubei Natural Science Foundation [2017CFB433]
  5. Open Research Project of The Hubei Key Laboratory of Intelligent Geo-Information Processing [KLIGIP-2017A09]
  6. Beijing Key Laboratory of Urban Spatial Information Engineering [2017209]

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This study proposes an integrated workflow-based rainstorm waterlogging analysis method, which reconstructs the waterlogging analysis model through different service invocation strategies and mechanisms. It can automatically integrate and compute geospatial data, models, and computing resources, demonstrating efficiency and flexibility.
This paper proposed a geoscience model service integrated workflow-based rainstorm waterlogging analysis method to overcome the defects of conventional waterlogging analysis systems. In this research, we studied a general OGC WPS service invoking strategy, an automatic asynchronous invoking mechanism of WPS services in the BPEL workflow, and a distributed waterlogging analysis services integrated workflow to realize the reconstruction of a waterlogging analysis model based on the proposed method. The proposed method can make use of the flexible adjustment capability of the workflow and not only overcomes the inherent defects of conventional geoscience analysis methods but also realizes the integration and calculation of distributed geospatial data, models and computing resources automatically. The method has better construction convenience, execution reliability, extensibility and intelligence potential than a conventional method and has important value for dealing with more natural disasters and environmental challenges.

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