Prediction of the vegetation management impacts on reduction of wind erosion risk in the southern parts of the Varamin Plain, Iran


1 Assistant Professor, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran

2 PhD. Student, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran


Wind erosion is a major environmental issue affecting land resources and socio-economic settings in Iran. This paper outlines a study undertaken to provide a new tool to manage wind erosion from physical and economic perspectives. The southern part of the Varamin Plain in south of Tehran is used as a case study. The focus of this study is on exploring the economic and physical impacts of 16 vegetation-based scenarios for wind erosion management as well as conducting a trade-off analysis using the Multi-Criteria Decision Making (MCDM) technique. This involves developing a modeling system to assist decision makers in formulating scenarios, analyzing the impacts of these scenarios on wind erosion, and interpreting and suggesting appropriate scenarios for implementation in the area. The Iran Research Institute of Forests and Rangelands (IRIFR.1) model has been selected to create the wind erosion hazard maps for the present condition and for the possible vegetative management scenarios. The Spearman’s correlation coefficient indicated a high conformity between the hazard classes of wind erosion map predicted by the IRIFER.1 model and ground evidences. Using the Delphi method weights of wind erosion, gross margin, and establishment costs indices have been determined 0.5, 0.3, and 0.2, respectively. This indicates the high importance of wind erosion issue from experts’ consideration. Standardization and trade-off analysis of indices showed that a scenario with a combination of all possible management actions ranked as the best scenario (highest score) despite incurring the largest establishment costs. On the other hand scenarios with single management actions resulted in lowest scores. Finally, the sensitivity analysis of the chosen modeling approach in this study indicated the robustness of the results.