a new technical and economic approach to aptimal plant species selection for open-pit mine reclamation process

Estimating the costs of mine reclamation is a significant part of mine closure projects. one approach to mine reclamation is planting mine areas. in this approach, the optimum selection of plant types is cosidered a multiple-criteria decision-making (mcdm) problem. once proper plant species are identified, it is required to estminate planting costs through statistical analysis. this work aims to introduce an algorithm for optimal plant type selection and a reclamation cost estimation model for open-pit mines. to this end, the plant species compatible with the sorrounding areas of sungun copper mine are identified and ranked using the promethee technique. in this analysis, the main criteria are local landscape, pest resistance, plant growth ability, availability, economic issues, soil protection, water storage ability, and pollution prevention. among the six plant types, maple trees have the highest score (4.34). after that, to develop the reclamation cost estimation model, the data (99 datasets) is collected from the sungun copper mine, sarcheshmeh copper mine, and chadormaloo iron mine. the variables in the database include soil gradation by graders, slope trimming and topography by bulldozers, the ripping and softening of the compacted soil, chemical fertilizers, natural fertilizers and mulch and biosolid, lime soil ph adjustment, herbicide, seedling, tree planting, workers and drivers, and fuel and maintenance. regression analysis is performed to analyze the data, and a reclamation cost estimation model is developed with high accuracy (r2 = 0.78). on the whole, this study proposes an innovative, step-by-step, technical, and economic approach to the optimal selection of plant species, and presents a reclamation cost estimation model so as to promote the open-pit mine reclamation process.