Outline

  • Abstract
  • Keywords
  • 1. Introduction
  • 2. Study Area and Geological Setting
  • 3. Materials and Methods
  • 3.1. Field and Laboratory Investigation
  • 3.2. Sinkhole Inventory and Nomenclature
  • 3.3. Factor Weighting by Ahp and Susceptibility Assessment
  • 4. Magnitude and Frequency Relationships
  • 5. Sinkhole Susceptibility Mapping
  • 5.1. Controlling Factors
  • 5.1.1. Distance to Faults (df)
  • 5.1.2. Water Level Decline (wld)
  • 5.1.3. Groundwater Exploitation (ge)
  • 5.1.4. Penetration of Deep Wells into the Karst Aquifer (pka)
  • 5.1.5. Distance to Deep Wells (ddw)
  • 5.1.6. Groundwater Alkalinity (ga)
  • 5.1.7. Bedrock Lithology (bl)
  • 5.1.8. Alluvium Thickness (at)
  • 6. Discussion and Conclusions
  • Acknowledgments
  • References

رئوس مطالب

  • چکیده
  • 1. مقدمه
  • 2. منطقه مطالعاتی و موقعیت زمین شناسی
  • 3. مواد و روش ها
  • 3.1. بررسی های میدانی و آزمایشگاهی
  • 3.2. فهرست فروچاله ها و نامگذاری آن ها
  • 3.3. وزن دهی فاکتور ها با استفاده از AHP و ارزیابی حساسیت
  • 4. روابط بزرگی و فرکانس
  • 5. نقشه حساسیت فروچاله
  • 5.1. فاکتور های کنترلی
  • 5.1.1. فاصله تا گسل (DF)
  • 5.1.2. کاهش تراز آب (WLD)
  • 5.1.3. بهره برداری از آب زیرزمینی (GE)
  • 5.1.4. نفوذ چاه های عمیق در آبخوان کارست (PKA)
  • 5.1.5. فاصله تا چاه های عمیق (DDW)
  • 5.6.1. قلیایی بودن آب زیرزمینی (GA)
  • 5.1.7. لیتولوژی سنگ بستر (BL)
  • 5.1.8. ضخامت رسوب (AT)
  • 6. بحث و نتیجه گیری

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.

Keywords: - - - -
دانلود ترجمه تخصصی این مقاله دانلود رایگان فایل pdf انگلیسی