Effect of support size on the accuracy of a distributed rockfall model

L.K.A. Dorren, G.B.M. Heuvelink

Research output: Contribution to journalArticleAcademicpeer-review

11 Citations (Scopus)

Abstract

It is investigated whether a GIS-based distributed model developed for rockfall assessment at slope scale, which uses data with a support of 2.5 x 2.5 m, could be used for rockfall assessment at the regional scale, using input data with a support of 25 x 25m and of poorer quality. It was anticipated that in the latter case the model error would increase. Three types of simulations were applied to the same model and the outcomes were validated with field data. The first simulation used input data with a support of 2.5 x 2.5m and aggregated the output to a support of 25625 m. The second simulation used the same input data as in the first simulation, but these data were aggregated to a support of 25 x 25m before running the model. The third simulation used input data of poorer quality obtained at a support of 25625 m. The results show that simulating the maximum extent of rockfall runout zones with a distributed model using data with a support of 25 x 25m is realistic and feasible. This is also true for data with poorer quality as the third simulation resulted in a slightly larger mean-squared error than the first simulation. Surprisingly, it also gave a smaller error than the second simulation. We investigated the cause of the large error produced by the second simulation and concluded that this was mainly caused by the combination of a high-quality digital elevation model and the loss of spatial structure in the input data due to spatial aggregation.
Original languageEnglish
Pages (from-to)595-609
JournalInternational Journal of Geographical Information Science
Volume18
Issue number6
DOIs
Publication statusPublished - 2004

Keywords

  • uncertainty
  • prediction
  • simulation
  • hillslope
  • scale
  • gis

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