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

Taheri, Kamal; Gutiérrez, Francisco; Mohseni, Hassan; Raeisi, Ezzat; Taheri, Milad

doi:10.1016/j.geomorph.2015.01.005

Cited by 123 publications

(62 citation statements)

References 48 publications

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“…Remote sensing and GIS technique facilitate time and cost effective, rapid assessment of groundwater resource, which otherwise through traditional method becomes very costly, laborious and time consuming work (Moore et al 1991;Krishnamurthy et al 2000;Jha et al 2010;Arkoprovo et al 2012;Hammouri et al 2012;Lee et al 2012a;Davoodi et al 2015). To delineate groundwater potential lineament and hydrogeomorphology, groundwater level decline and its impacts on regional subsidences and karst hazards, and groundwater vulnerability to pollution are applied by GIS-based approaches by several researchers (Nag 2005;Taheri et al 2015;Singh et al 2015;Taheri et al 2016). In delineation of groundwater potential zone various factors such as lineament, faults and hydrogeomorphology (Nag 2005;Senthil-Kumar and Shankar 2014;Singh et al 2014;Taheri et al 2015), rainfall, soil, lithology and soil texture (Magesh et al 2012), slope, elevation (Magesh et al 2011;Thomas et al 2012), drainage systems (Rassam et al 2008;Preeja et al 2011;Dabral et al 2013) and groundwater table distribution (Arkoprovo et al 2012) play a crucial role.…”

Section: Introductionmentioning

confidence: 99%

Assessment of groundwater potential zones using multi-influencing factor (MIF) and GIS: a case study from Birbhum district, West Bengal

et al. 2017

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Remote sensing and GIS play a vital role in exploration and assessment of groundwater and has wide application in detection, monitoring, assessment, conservation and various other fields of groundwater-related studies. In this research work, delineation of groundwater potential zone in Birbhum district has been carried out. Various thematic layers viz. geology, geomorphology, soil type, elevation, lineament and fault density, slope, drainage density, land use/land cover, soil texture, and rainfall are digitized and transformed into raster data in ArcGIS 10.3 environment as input factors. Thereafter, multi-influencing factor (MIF) technique is employed where ranks and weights, assigned to each factor are computed statistically. Finally, groundwater potential zones are classified into four categories namely low, medium, high and very high zone. It is observed that 18.41% (836.86 km 2 ) and 34.41% (1563.98 km 2

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Section: Introductionmentioning

confidence: 99%

Assessment of groundwater potential zones using multi-influencing factor (MIF) and GIS: a case study from Birbhum district, West Bengal

et al. 2017

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“…It was found that the North West part can be categorized as high and very high hazard area. This area is mostly occurred in Kuala Lumpur Limestone Formation bedrock geology consisting limestone/marble and acid intrusive (undifferentiated) lithology (Taheri, et al, 2015). In this study area, most of sinkhole hazard occurred at the high value of water level decline which is -22 to -70 cubic meter of approximate yield.…”

Section: Sinkhole Susceptibility Hazard Zonation Mapmentioning

confidence: 86%

“…Every parameter was calculated based on sinkhole location and a spatial database. Other paper by (Taheri, et al, 2015) using analytical hierarchy process (AHP) to determine sinkhole susceptibility map in Hamadan province, Iran. It combine with GIS environment considering eight causal factors namely distance to faults, water level decline, groundwater exploitation, penetration of deep wells into karst bedrock, distance to deep wells, groundwater alkalinity, bedrock lithology and alluvium thickness.…”

Section: Multi-criteria Decision Making Techniques (Mcdm)mentioning

confidence: 99%

Sinkhole Susceptibility Hazard Zones Using Gis and Analytical Hierarchical Process (Ahp): A Case Study of Kuala Lumpur and Ampang Jaya

Rosdi¹,

Othman²,

Zubir³

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Sinkhole is not classified as new phenomenon in this country, especially surround Klang Valley. Since 1968, the increasing numbers of sinkhole incident have been reported in Kuala Lumpur and the vicinity areas. As the results, it poses a serious threat for human lives, assets and structure especially in the capital city of Malaysia. Therefore, a Sinkhole Hazard Model (SHM) was generated with integration of GIS framework by applying Analytical Hierarchical Process (AHP) technique in order to produced sinkhole susceptibility hazard map for the particular area. Five consecutive parameters for main criteria each categorized by five sub classes were selected for this research which is Lithology (LT), Groundwater Level Decline (WLD), Soil Type (ST), Land Use (LU) and Proximity to Groundwater Wells (PG). A set of relative weights were assigned to each inducing factor and computed through pairwise comparison matrix derived from expert judgment. Lithology and Groundwater Level Decline has been identified gives the highest impact to the sinkhole development. A sinkhole susceptibility hazard zones was classified into five prone areas namely very low, low, moderate, high and very high hazard. The results obtained were validated with thirty three (33) previous sinkhole inventory data. This evaluation shows that the model indicates 64% and 21% of the sinkhole events fall within high and very high hazard zones respectively. Based on this outcome, it clearly represents that AHP approach is useful to predict natural disaster such as sinkhole hazard.

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“…map was then subdivided into three categories in accordance with the degree of vulnerability of each factor/layer based on Natural break criterion in the GIS environment. The natural break classification method has commonly been used in landslide susceptibility mapping to categorize the susceptibility classes (Falaschi et al, 2009;Bednarik et al, 2010;Pourghasemi et al, 2013) and sinkhole susceptibility mapping (Taheri et al, 2015).…”

Section: Protective Covermentioning

confidence: 99%

Sinkholes and the Engineering and Environmental Impacts of Karst: Proceedings of the Fourteenth Multidisciplinary Conference

2015

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

Cited by 123 publications

References 48 publications

Assessment of groundwater potential zones using multi-influencing factor (MIF) and GIS: a case study from Birbhum district, West Bengal

Assessment of groundwater potential zones using multi-influencing factor (MIF) and GIS: a case study from Birbhum district, West Bengal

Sinkhole Susceptibility Hazard Zones Using Gis and Analytical Hierarchical Process (Ahp): A Case Study of Kuala Lumpur and Ampang Jaya

Sinkholes and the Engineering and Environmental Impacts of Karst: Proceedings of the Fourteenth Multidisciplinary Conference

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