OWA Analysis for Ecological Capability Assessment in Watersheds

Document Type : Original Research Paper


1 Department of the Environmental Management, Planning and Education, Faculty of Environment, University of Tehran, Tehran, Iran

2 Department of the Environment, Faculty of Environment, Gorgan University of Agriculture and Natural Resources Science, Golestan Province, Iran

3 Department of the Forestry, Faculty of Natural Resources and Marine Science, TarbiatModares University, Noor, Mazandaran Province, Iran

4 Faculty of Environment, University of Tehran, Tehran, Iran


Fuzzylogic computes a multi-criteria evaluation by means of either a Boolean analysis, Weighted
Linear Combination (WLC) and Ordered Weighted Averaging (OWA) of factor images. OWA works with
standardized factor images and employs a variant of the WLC. It takes into account the risk associated with
the decision and degree of tradeoff associated with the variables in the analysis. In this research, for Ecological Capability Assessment and watersheds management in study area, we have studied 22 biological and physiological factors. For ecological capability evaluation, the method of OWA was deployed. This method involves criterion weights and order weights. The generality of OWA is related to its capability to implement different combination operators by selecting appropriate order weights. By specifying suitable order weights, it is possible to change the form of aggregation from the minimum-type combination through all intermediate types including the conventional weighted linear combination, to the maximum-type combination. The paper focuses on the OWA method as well as an approach for integrating Geographic Information System (GIS) and OWA. OWA has been developed as a generalization of multi-criteria combination. The OWA concept has been extended to the GIS applications as part of a decision support module in GIS. In this study to obtain the criteria weights, comparisons were made by evaluating 22 criteria against each other, therefore we attained comparable data via the technique of Analytical Hierarchy Process (AHP) and five scenarios of OWA method were used. The results of field studies, third scenario for the study area proposed.