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Application of Spatial Analysis Techniques to Select the Most Suitable Areas for Flood Spreading

Author

Listed:
  • Mostafa Moradi Dashtpagerdi
  • Ahmad Nohegar
  • Hassan Vagharfard
  • Afshin Honarbakhsh
  • Vafa Mahmoodinejad
  • Akbar Noroozi
  • Diba Ghonchehpoor

Abstract

This study addressed potential areas for flood spreading by evaluating the Boolean Logic, Overlay Index and Fuzzy Clustering techniques for spatial analysis. We applied these techniques on the artificial recharge criteria of slope, infiltration rate, alluvium thickness, land use and alluvial quality. The above criteria were prepared, classified, weighted and integrated in a GIS environment. The resultant maps were organized into two classes of potentiality, suitable and unsuitable, which expressed two different levels of favorability for site selection of flood spreading in the study area. We used 32 controlling areas to compare the performance of these spatial analysis techniques. By validation of the produced maps, the most suitable areas of flood spreading for each technique were determined: Fuzzy Clustering (14.4 %) Overlay Index (10.84 %) and Boolean Logic (10 %). After land use filtering, 72 %, 70 % and 65 % of the most suitable areas were eliminated in the, Overlay Index, Boolean model and Fuzzy Clustering, respectively. According to our results, the spatial analysis techniques can be powerful tools for selecting the most suitable areas for flood spreading. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • Mostafa Moradi Dashtpagerdi & Ahmad Nohegar & Hassan Vagharfard & Afshin Honarbakhsh & Vafa Mahmoodinejad & Akbar Noroozi & Diba Ghonchehpoor, 2013. "Application of Spatial Analysis Techniques to Select the Most Suitable Areas for Flood Spreading," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(8), pages 3071-3084, June.
    • Handle: RePEc:spr:waterr:v:27:y:2013:i:8:p:3071-3084
    DOI: 10.1007/s11269-013-0333-0
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    References listed on IDEAS

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    1. Liu, Chen-Wuing & Chen, Shih-Kai & Jou, Shew-Wen & Kuo, Sheng-Feng, 2001. "Estimation of the infiltration rate of a paddy field in Yun-Lin, Taiwan," Agricultural Systems, Elsevier, vol. 68(1), pages 41-54, April.
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    Cited by:

    1. Seyed Naghibi & Hamid Pourghasemi, 2015. "A Comparative Assessment Between Three Machine Learning Models and Their Performance Comparison by Bivariate and Multivariate Statistical Methods in Groundwater Potential Mapping," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 5217-5236, November.

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