Plant type selection for reclamation of Sarcheshmeh copper mine using fuzzy-TOPSIS approach

• Autorzy: Ebrahimabadi A. , Alavi I.

Warianty tytułu

PL

Wybór gatunków roślin do wykorzystania w projekcie rekultywacji terenów kopalni miedzi Sarcheshmeh z wykorzystaniem metod logiki rozmytej TOPSIS

• Języki publikacji: EN

Abstrakty

EN

Plant species selection is a multi-criteria evaluation decision and has a strategic importance for many companies. The conventional methods for plant species selection are inadequate for dealing with the imprecise or vague nature of linguistic assessment. To overcome this difficulty, fuzzy multi-criteria decision-making methods are proposed. The aim of this study is to use the fuzzy technique for order preference by similarity to ideal solution (F.TOPSIS) methods for the selection of plant species in mine reclamation plan. Plant type selection and planting to protect the environment and the reclamation of the mine are some of the most important solutions. Therefore, the objective of the current research study is to choose the proper plant types for reclamation of Sarcheshmeh Copper Mine using Fuzzy-topsis method. In this regard, primarily, surrounding area of Sarcheshmeh copper mine, one of the world’s 10 biggest copper mine which is located near Kerman city of Iran, are surveyed, to choose the best plant type for reclamation of disturbance area. With this respect, based on reclamation plan, primary criteria were consisted of kinds of post mining land use, climate, and nature of soil. Comparison matrixes were then obtained based on experts’ opinion and plant types were subsequently prioritized using the Fuzzy Topsis method. Secondary factors considered through the analysis were as follows: perspective of the region, resistance against disease and insects, strength and method of growth, availability to plant type, economic efficiency, protection of soil, storing water, and prevention of pollution. Finally, suitable plant types in the mining perimeter were prioritized as: Amygdalus scoparia, Tamarix, Pistachio Wild, Ephedra, Astragalus, Salsola, respectively.

PL

Wybór gatunków roślin jest decyzją podejmowaną w oparciu o wiele kryteriów i stanowi poważne wyzwanie strategiczne dla wielu firm. Konwencjonalne metody wyboru gatunków roślin okazują się niewystarczające w przypadku nieprecyzyjnej oceny i nie w pełni zdefiniowanych określeń językowych. W celu przezwyciężenia tych trudności, zaproponowano wielo-kryterialną metodę decyzyjną wykorzystującą logikę rozmytą. Celem tego opracowania jest ukazanie zastosowania podejścia rozmytego do uzyskania kolejnych przybliżeń do rozwiązania idealnego (F.TOPSIS) przy wyborze odpowiednich gatunków roślin do użycia w projekcie rekultywacji terenów kopalni. Wybór gatunków roślin i ich kultywacja dla zapewnienia ochrony środowiska i projektu rekultywacji terenu pogórniczego to bardzo ważne zagadnienia. Głównym celem obecnego studium jest wybór odpowiednich gatunków roślin do wykorzystania projekcie rekultywacji terenów kopalni miedzi Sarcheshmeh z wykorzystaniem metod logiki rozmytej TOPSIS. W pierwszym rzędzie przeprowadzono badania gruntów wokół kopalni miedzi Sarchesmeh, w pobliżu miejscowości Kerman w Iranie (jednej z dziesięciu największych na świecie kopalni miedzi) w celu wyboru najlepszych typów roślin do wykorzystania do rekultywacji naruszonych działalnością górniczą terenów. Określono podstawowe kryteria wyboru, biorąc pod uwagę plan rekultywacji: sposoby wykorzystania terenu, klimat oraz rodzaje gleb. Otrzymano macierze porównawcze uzyskane na podstawie opinii ekspertów, następnie dokonano określenia priorytetów dla poszczególnych roślin przy pomocy metody TOPSIS, wykorzystującej logikę rozmytą. W analizie uwzględniono następujące czynniki drugorzędne: perspektywy dla regionu, odporność na choroby i owady szkodniki, wytrzymałość i sposób uprawy, dostępność danego gatunku roślin, wydajność ekonomiczna, ochrona gleb, zdolność zatrzymywania wody, zapobieganie zanieczyszczeniom. W końcowym etapie dokonano wyboru najkorzystniejszych dla danego terenu górniczego gatunków roślin, podając kolejno: Amygdalus scoparia, Tamarix, Pistachio Wild, Ephedra, Astragalus, Salsola.

Słowa kluczowe

EN

mine reclamation; plant type selection; Sarcheshmeh copper mine; fuzzy TOPSIS

PL

rekultywacja terenów kopalni; wybór gatunków roślin; kopalnia miedzi Sarcheshmeh; metoda logiki rozmytej TOPSIS

• Wydawca: Instytut Mechaniki Górotworu PAN
• Czasopismo: Archives of Mining Sciences
• Rocznik: 2013
• Tom: Vol. 58, no. 3
• Strony: 953--968
• Opis fizyczny: Bibliogr. 44 poz., tab., wykr.

Twórcy

autor

Ebrahimabadi A.

• Department of Mining Engineering, Faculty of Engineering, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran

autor

Alavi I.

• Department of Mining Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

Bibliografia

• Alavi I., Akbari A., Parsaei M., 2011. Plant Type Selection for Sarcheshmeh Copper Mine Reclamation by Fuzzy-AHPMethod. Blour Science and Expertism Magazine, Amirkabir University of Technology, No. 29, 10-17.
• Alavi I., Alinejad R.H., 2011. Comparison of Fuzzy AHP and Fuzzy TOPSIS Methods for Plant Species Selection (Casestudy: Reclamation Plan of Sungun Copper Mine; Iran). Australian Journal of Basic and Applied Sciences, Vol. 5, No. 12, p. 1104-1113.
• Alavi I., Alinejad R.H., Sadegh Zadeh M., 2011. Prioritizing Crescive Plant Species in Choghart Iron Mine DesertRegion (Used method: Fuzzy AHP). Australian Journal of Basic and Applied Sciences, Vol. 5, No. 12, p. 1075-1078.
• Alexander M.J., 1996. The Effectiveness of Small-scale Irrigated Agriculture in the Reclamation of Mine Land Soils onthe Jos Plateau of Nigeria. Land Degradation and Development, Vol. 7, p. 77-85.
• Askenasy P., Brandt J., 1998. Land Capability Classification in Report of the Soil Working Group. Texas Mineland Reclamation Monitoring Program Issues, p. 47-58.
• Bakhshandeh H.A., Mozdianfard M.R., Siamaki A., 2010. Predicting of Blasting Vibrations in Sarcheshmeh CopperMine by Neural Network. Safety Science, Vol. 48, p. 319-325.
• Bangian A.H., Osanloo M., 2008. Multi Attribute Decision Model for Plant Species Selection in Mine Reclamation Plans:Case Study Sungun Copper Mine. Post-Mining, February 6-8, Nancy, France, 1-11.
• Bellman R.E., Zadeh L.A., 1977. Local and fuzzy Logics. Modern Uses of Multiple-valued Logic, Kluwer, Boston, 105-151 and 158-165.
• Belsky A.J., Canham C.D., 1994. Forest Gaps and Isolated Savanna Trees; an Application of Patch Dynamics in TwoEcosystems. Bioscience, Vol. 44, p. 77-84.
• Bojadziev G., Bojadziev M., 1996. Fuzzy Sets and Fuzzy Logic Applications. World Scientific, Singapore.
• Cairns J., 1982. Ecological Considerations in Reclaiming Surface Mined Lands. Minerals and the Environment, Vol. 1, p. 83-89.
• Carrick P.J., Kruger R., 2007. Restoring Degraded Landscapes in Lowland Namaqua-land: Lessons from the MiningExperience and from Regional Ecological Dynamics. Journal of Arid Environments, Vol. 32, p. 52-67.
• Chen C.T., 2000. Extensions of the TOPSIS for Group Decision Making under Fuzzy Environment. Fuzzy Sets and Systems, Vol. 114, p. 1-9.
• Chen C.T., Lin C.T., Huang S.F., 2006. A Fuzzy Approach for Supplier Evaluation and Selection in Supply Chain Management. International Journal of Production Economics, Vol. 102, p. 289-301.
• Chen H., Zheng C., Zhu Y., 1998. Phosphorus: A limiting Factor for Restoration of Soil Fertility in a Newly ReclaimedCoal Mined Site in Xuzhou, China. Land Degradation and Development, Vol. 9, p. 115-121.
• Coppin N.J., Box J., 1999. Sustainable Rehabilitation and Revegetation: the Identification of after-use Options forMines and Quarries using a Land Suitability Classification Involving Nature Conservation. Environmental Policy in Mining-Corporate Strategy and Planning for Closure, Published by CRC Press, p. 229-243.
• Coppin N.J., Bradshaw A.D., 1982. Quarry Reclamation: The Establishment of Vegetation in Quarries and Open PitNon metal Mines. Mining Journal Books Ltd., London, England, p. 18-25.
• Deng H., 1999. Multi-criteria Analysis with Fuzzy Pair-wise Comparison. International Journal of Approximate Reasoning, Vol. 21, p. 215-231.
• Errington J.C., 2001. Mine Reclamation in British Columbia - Twenty-five Years of Progress. 25th Annual British Columbia Mine Reclamation Symposium, Campbell River, BC.
• Ertuğrul I., Karakaşoğlu N., 2006. Fuzzy TOPSIS Method for Academic Member Selection in Engineering Faculty. International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering (CIS2E 06), p. 4-14.
• Ertuğrul I., Karakaşoğlu N., 2007. Comparison of Fuzzy AHP and Fuzzy TOPSIS Methods for Facility Location Selection. International Journal of Advanced Manufacturing Technology, DOI 10.1007/s00170-007-1249-8, Vol. 39, p. 783-795.
• Ertuğrul I., Tuş A., 2007. Interactive Fuzzy Linear Programming and an Application Sample at a Mine firm. Fuzzy Optimization and Decision Making, Vol. 6, p. 29-49.
• Haque N., Peralta-Videa J.R., Duarte-Gardea M., Gardea-Torresdey J.L., 2009. Differential Effect of Metals/metalloidson the Growth and Element Uptake of Mesquite Plants Obtained from Plants Grown at a Copper Mine Tailing andCommercial Seeds. Bioresource Technology, Vol. 100, p. 6177-6182.
• Howat D.R., 2000. Acceptable Salinity, Sodicity and pH Values for Boreal Forest Reclamation, Alberta Environment. Environmental Sciences Division. Edmonton Alberta, (online edition), 191.
• Hwang C.L., Yoon K., 1981. Multiple Attributes Decision Making Methods and Applications. Springer, Berlin.
• Liang G.S., 1999. Fuzzy MCDM Based on Ideal and Anti-ideal Concepts. European Journal Operational Research, Vol. 112, p. 682-691.
• Liao C-N., Kao H-P., 2011. An Integrated Fuzzy TOPSIS and MCGP Approach to Supplier Selection in Supply ChainManagement. Expert Systems with Applications, Vol. 38, p. 10803-10811.
• Maiti S.K., Ghose M.K., 2005. Ecological Restoration of Acidic Coal Mine Overburden Dumps - An Indian Case Study. Journal of Land Contamination and Reclamation, Vol. 13, p. 361-370.
• Monterroso C., Macias F., Bueno G., 1998. Evaluation of the Land Reclamation Project at the as Pontes Mine (NW Spain)in Relation to the Suitability of the Soil for Plant Growth. Land Degradation and Development, Vol. 9, p. 441-458.
• Nourali H., Nourali S., Ataei M., Imanipour N., 2012. A Hierarchical Preference Voting System for Mining MethodSelection Problem. Arch. Min. Sci., Vol. 57, No. 4, p. 1056-1070.
• Osanloo M., 2001. Mine Reclamation. Amirkabir University of Technology, vol. 1, p. 183-193.
• Osanloo M., Parsaei M., 2004. Sarcheshmeh Copper Mine Reclamation. Proceeding of Safety Congress, Iran, p. 316-325.
• Paschke M.W., Redente E.F., Brown S.L., 2003. Biology and Establishment of Mountain Shrubs on Mining Disturbancesin the Rocky Mountains, USA. Land Degradation and Development, Vol. 14, p. 459-480.
• Redente E.F., Baker D.A., 1996. Direct Re-vegetation of Mine Tailings. A case study in Colorado. Planning, Rehabilitation and Treatment of Disturbed Lands, Billings Symposium, p. 183-191.
• Soltanmohammadi H., Osanloo M., Aghajani A.B., 2010. An Analytical Approach with a Reliable Logic and a RankingPolicy for Post-mining Land-use Determination. Land Use Policy, vol. 27, p. 364-372.
• Stellin J.R., Hennies A., Soares L., Fujimura F., Lauand V., 2005. Area Recovery Project of Dimension Stone QuarryMine. COMI and MPES 2005, Banff, Alberta, Canada, p. 951-965.
• Tafi T.C., Neuman D., Wraith J., Fedock J., 2006. Reclamation Effectiveness at Three Reclaimed Abandoned Mine Sitesin Jefferson County, Montana. A Thesis Submit-ted in Partial Fulfillment of the Requirements for the Degree of Master of Science in Land Rehabilitation, Montana State University, Bozeman, Montana.
• Tavili A., 2010. Influence Tamarisk, Haloxylon Ammodendron and Seidlitzia Rosmarinus Species against Soil in the Areaof Chah Afzal Yazd. Iranian Journal of the Forest, Vol. 4, p. 357-365.
• Wang Y.M., Elhag T.M.S., 2006. Fuzzy TOPSIS Method Based on Alpha Level Sets with an Application to Bridge RiskAssessment. Expert System with Application, Vol. 31, p. 309-319.
• Wisconsin L., 2000. Flambeau Copper Mine Reclamation. Applied Ecological Services Inc.
• Xia L.U., Zhen-qi H.U., Wei-jie L.I.U., Xiao-yan H., 2007. Vegetation Growth Monitoring Under Coal Exploitation Stressby Remote Sensing in the Bulianta Coal Mining Area. Institute of Land Reclamation and Ecological Restoration, China University of Mining and Technology, Beijing, Vol. 17, No. 4, p. 0479-0483.
• Zadeh L.A., 1965. Fuzzy Sets. Information and Control, Vol. 8, p. 338-353.
• Zadeh L.A., 1975. The Concept of a Linguistic Variable and its Application to Approximate Reasoning. Information Sciences, Vol. 8, p. 199-249.
• Zimmermann H.J., 1992. Fuzzy Set Theory and its Spplications. Kluwer, Boston.