Development of a System for Practical Prediction of Flood and Debris Flow Throughout Japan

9 pages•Published: September 20, 2018

Ryosuke Arai, Kazuyuki Ota, Yasushi Toyoda and Takahiro Sato

Abstract

It is an important practical concern to be able to promptly predict the effect and extent of flood and debris flow. We developed a GUI system to predict the effect and extent of flood and debris flow. The system has two features. First, the system can extract the target domain using digital elevation model (DEM) data by specifying the LAT/LON of the occurrence site. Second, a raster-based, 2D diffusion wave model was used as a numerical flow model to reduce the computational time. Although this system had difficulty in predicting the impact of micro-topography as a result of the coarse mesh data, overall it satisfactorily represented the scale and potential risk of these disasters. In addition, this system can access DEM data throughout Japan to generate exact target domains. Thus, this system can be used to efficiently predict flood and debris flows at a large number of sites.

Keyphrases: dem, diffusion wave model, horizontal 2d simulation

In: Goffredo La Loggia, Gabriele Freni, Valeria Puleo and Mauro De Marchis (editors). HIC 2018. 13th International Conference on Hydroinformatics, vol 3, pages 45-53.

Links:	https://easychair.org/publications/paper/tNjt
	https://doi.org/10.29007/l5l5

BibTeX entry

@inproceedings{HIC2018:Development_System_Practical_Prediction,
  author    = {Ryosuke Arai and Kazuyuki Ota and Yasushi Toyoda and Takahiro Sato},
  title     = {Development of a System for Practical Prediction of Flood and Debris Flow Throughout Japan},
  booktitle = {HIC 2018. 13th International Conference on Hydroinformatics},
  editor    = {Goffredo La Loggia and Gabriele Freni and Valeria Puleo and Mauro De Marchis},
  series    = {EPiC Series in Engineering},
  volume    = {3},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {/publications/paper/tNjt},
  doi       = {10.29007/l5l5},
  pages     = {45-53},
  year      = {2018}}

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