Monday, March 12, 2012

Multi-criteria Decision Making for Water Resource Management: A Case Study of the Gediz River Basin, Turkey


In this case study, of the Gediz river basin in Turkey, Baris Yilmaz and Nilmun Harmancioglu explore water resource management using an MCDM (multi-criteria decision making) tool. They account for environmental, social and economic factors in their study of the water distribution, primarily focused on the irrigation aspect.


Using a baseline and two scenarios; better and worse conditions, they explore three hydro-meteorological scenarios to get an assessment of water budget and the possible alternative uses of the water under different scenarios. In order to rank the methods of water usage, several methods were used. Simple additive weighting, compromise programming and technique for order preference by similarity to ideal solution are all used in the MCDM.


  • · Clearly defined parameters for making decisions

  • · Criteria can be weighted to allow varying importance to be accounted for

  • · It is flexible in the factors that it can incorporate

  • · Used in conjunction with other analytic techniques


  • · Different techniques may yield different results

  • · Reliability and success are reliant on the right criteria being chosen


A water resource management model that uses environmental, social and economic factors can be used to decide the best water resource management techniques. However, this relies strongly on the weighting of the factors involved and can be easily skewed. Coincidentally, the MCDM matches the current decision-makers policies in water resource management. Therefore, in the Gediz river basin example, the MCDM proves to be a useful framework for the evaluation of water resource management techniques.


Multi-criteria decision making for water resource management: a case study of the Basin, Turkey. Harmancioglu, Nilmun. Yilmaz, Baris. 5 October 2010. Retrieved from:

1 comment:

  1. You mentioned in your conclusion that that the weighting of factors can be easily skewed which would could lead to an incorrect conclusion. Are there any techniques that can be used to make the weighting of the criteria less susceptible to being skewed?