Karst database implementation in Minnesota: Analysis of sinkhole distribution

Y. Gao, E. C. Alexander, Randal J Barnes

Research output: Contribution to journalArticlepeer-review

55 Scopus citations

Abstract

This paper presents the overall sinkhole distributions and conducts hypothesis tests of sinkhole distributions and sinkhole formation using data stored in the Karst Feature Database (KFD) of Minnesota. Nearest neighbor analysis (NNA) was extended to include different orders of NNA, different scales of concentrated zones of sinkholes, and directions to the nearest sinkholes. The statistical results, along with the sinkhole density distribution, indicate that sinkholes tend to form in highly concentrated zones instead of scattered individuals. The pattern changes from clustered to random to regular as the scale of the analysis decreases from 10-100 km2 to 5-30 km 2 to 2-10 km2. Hypotheses that may explain this phenomenon are: (1) areas in the highly concentrated zones of sinkholes have similar geologic and topographical settings that favor sinkhole formation; (2) existing sinkholes change the hydraulic gradient in the surrounding area and increase the solution and erosional processes that eventually form more new sinkholes.

Original languageEnglish (US)
Pages (from-to)1083-1098
Number of pages16
JournalEnvironmental Geology
Volume47
Issue number8
DOIs
StatePublished - May 1 2005

Keywords

  • Complete spatial randomness (csr)
  • Distance to nearest neighbor (DNN)
  • Karst Feature database (KFD)
  • Minnesota
  • Nearest neighbor analysis (NNA)
  • Nearest neighbor index (NNI)

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