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Developing a new method for spatial assessment of drought vulnerability (case study: Zayandeh-Rood river basin in Iran)

  1. Hamid Babaei*,
  2. Shahab Araghinejad,
  3. Abdolhossein Hoorfar

Article first published online: 3 JUL 2012

DOI: 10.1111/j.1747-6593.2012.00326.x

Issue

Water and Environment Journal

Water and Environment Journal

Volume 27, Issue 1, pages 50–57, March 2013

Additional Information

How to Cite

Babaei, H., Araghinejad, S. and Hoorfar, A. (2013), Developing a new method for spatial assessment of drought vulnerability (case study: Zayandeh-Rood river basin in Iran). Water and Environment Journal, 27: 50–57. doi: 10.1111/j.1747-6593.2012.00326.x

Author Information

  1. Department of Water Science & Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran

* Correspondence
H. Babaei, Department of Water Science & Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, P.O. Box 4111, Karaj 31587-77871, Iran. Email: hamidbabaei1@gmail.com

Publication History

  1. Issue published online: 17 FEB 2013
  2. Article first published online: 3 JUL 2012

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Keywords:

  • AHP;
  • GIS;
  • TOPSIS;
  • vulnerability drought;
  • Zayandeh-Rood river basin

Abstract

The paper presents an approach to spatially representative depiction for assessing the vulnerability of central Iran's Zayandeh-Rood river basin to drought using multiple indicators. Drought conditions prevailed in the study basin from 2002 to 2007, with an annual rainfall deficiency of 45 to 55%. Multi-attribute decision making (MADM) methods develop a framework to evaluate the relative priorities of drought assessment based on a set of preferences, criteria and indicators. The proposed MADM process uses well-known techniques for product weights analytic hierarchy process (AHP) and order preference (TOPSIS). These indicators include the Standard Precipitation Index (SPI), water demand, the Palmer Drought Severity Index (PDSI) and the Groundwater Balance and Surface Water Supply Index (SWSI). Indicators' spatial information was categorised in layers prepared in the spatial domain using a geographic information system (GIS). The alternatives were ranked and presented using TOPSIS. Results show that the proposed method was highly effective in representing assessments of drought vulnerability.

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