Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Geomorphologyarrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Geomorphology
Article . 2015 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
versions View all 1 versions
addClaim

Sinkhole susceptibility mapping using the analytical hierarchy process (AHP) and magnitude–frequency relationships: A case study in Hamadan province, Iran

Authors: Kamal Taheri; Francisco Gutiérrez; Hassan Mohseni; Ezzat Raeisi; Milad Taheri;

Sinkhole susceptibility mapping using the analytical hierarchy process (AHP) and magnitude–frequency relationships: A case study in Hamadan province, Iran

Abstract

Abstract Since 1989, an increasing number of sinkhole occurrences have been reported in the Kabudar Ahang and Razan–Qahavand subcatchments (KRQ) of Hamadan province, western Iran. The sinkhole-related subsidence phenomenon poses a significant threat for people and human structures, including sensitive facilities like the Hamadan Power Plant. Groundwater over-exploitation from the thick alluvial cover and the underlying cavernous limestone has been identified as the main factor involved in sinkhole development. A sinkhole susceptibility model was produced in a GIS environment applying the analytical hierarchy process (AHP) approach and considering a selection of eight factors, each categorized into five classes: distance to faults (DF), water level decline (WLD), groundwater exploitation (GE), penetration of deep wells into karst bedrock (PKA), distance to deep wells (DDW), groundwater alkalinity (GA), bedrock lithology (BL), and alluvium thickness (AT). Relative weights were preliminarily assigned to each factor and to their different classes through systematic pairwise comparisons based on expert judgment. The resulting sinkhole susceptibility index (SSI) values were then classified into four susceptibility classes: low, moderate, high and very high susceptibility. Subsequently, the model was refined through a trial and error process involving changes in the relative weights and iterative evaluation of the prediction capability. Independent evaluation of the final model indicates that 55% and 45% of the subsidence events fall within the very high and high, susceptibility zones, respectively. The results of this study show that AHP can be a useful approach for susceptibility assessment if data on the main controlling factors have sufficient accuracy and spatial coverage. The limitations of the model are partly related to the difficulty of gathering data on some important geological factors, due to their hidden nature. The magnitude and frequency relationship constructed with the 41 sinkholes with chronological and morphometric data indicates maximum recurrence intervals of 1.17, 2.14 and 4.18 years for sinkholes with major axial lengths equal to or higher than 10 m, 20 m, and 30 m, respectively.

Related Organizations
  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    129
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
129
Top 1%
Top 10%
Top 10%
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!