Determine the most important criteria and indicators that influence land degradation and desertification

Document Type : Research Paper

Authors

1 University of Shakerian

2 University of Tehran

Abstract

Nowadays, land degradation and desertification are serious and complex problems that have turned into a worldwide crisis in the world. Using evaluative systems to study degradation and adopting an appropriate strategy to deal with this phenomenon is necessary and important.  The first step in the study of land degradation and desertification is determining criteria and indicators that affect upon this process. Therefore, in this study the importance and priority of a considerable number of criteria and indices that influence upon land degradation and desertification were examined. Accordingly, 8 criteria and 49 indicators were chosen based on questionnaires and expert panel and they were evaluated based on eight metrics. We weighted suitable criteria for evaluation indicators with the help of Shannon entropy method, and then by using the TOPSIS method (one of Multiple Attribute Decision Making Methods) we determined the most effective indicators on land degradation and desertification for management and dealing with this phenomenon. The results show that among the evaluation criteria and indices that should be considered for a benchmark or index, a scale, has the highest weight and importance, and being sensitive to change, has the minimum weight and importance.The results of the prioritization and ranking criteria and indicators based on TOPSIS model indicates that the severity of exploitation of water resources in the factor of water with the 0.79 efficiency, has the most effect and the use of facilities and personal management in the management factor with the 0.11 efficiency has less effect in land degradation and desertification.

Keywords


[1] Bowyer, C., Withana, S., Fenn, I., Bassi, S., Lewis, M., Cooper, T., Benito, P. and Mudgal, Sh. (2008). Land Degradation and Desertification. IP/A/ENVI/ST/2008-23, 416-203.
[2] D’Odorico, P., Bhattachan, A., Davis, k., Ravi, and Runyan, Ch. (2013). Global desertification: Drivers and feedbacks. Advances in Water Resources. 51, 326–344.
[3] Eslamian, Z., Ghorbani, M., Mesbah zadeh, T., Rafieie, H. (2016). Application of numerical taxonomy to prioritize socioeconomic effects of desertification (Case Study: Nazrabad area, Aran). JOURNAL OF RANGE AND DESERT RESEARCH Scientific Iran, 23(1)
[4] Ghorbani, M.A., Asadi, H., Jabari khameneh, H. and Farsadi zade, D. (2014). Extraction of instantaneous unit hydrograph (IUH) using the Shannon entropy. Journal of Watershed Management, 10.
[5] Grau, J. B., Ant´on, J. M., Tarquis, A. M., Colombo, F., de los R´ıos, L., and Cisneros, J. M.( 2010). An application of mathematical models to select the optimal alternative for an integral plan to desertification and erosion control (Chaco Area – Salta Province – Argentina). Biogeosciences, 7, 3421–3433.
[6] HELMUT, J., GEIST, L. and ERIC, F. (2004). Dynamic causual patterns of Desertification. Bioscience 817, 54(9).
[7] HELMUT, J., GEIST, L. and ERIC, F. (2015). Dynamic causual patterns of Desertification. Seoul National University Library, December 6.
[8] Holisaz, A., Azarnivand, H., Akrami, M., Mahdavi, M. and Mehrabi, A. (2011). Scale-cognitive methods for environmental studies. Environmental Research, 2(3), 35-48.
[9] Jamali, A., Ghodusib, J. and Farahpour, M. (2005). GIS and Spatial Decision Support System for desertification Mitigation inWatershed. ACRS. M. Izadi؛ F. Abolhasani؛ M.
[10] Nastaran, M., Abolhasani, F. and Izadi, M. (2010), Application of TOPSIS method in analysis and prioritizing sustainable development of urban zones (case study: urban zones of Isfahan), Geography and Environmental Planning, 21(2), 83-100.
[11] Poortaheri, M., (2010). Using Multi-Attribute Decision methods in geography, Research organizations and universities Compilation of Humanities Books. Center of Humanities Research and Development, 223.
[12] Saboori rad, S., Nazari samani, A. and Sepehr, A., (2012). Determine the most important effective indicator of desertification based on DPSIR conceptual framework and methods by multi-criteria decision (Case Study: Miyandehi Faizabad). Earth science research, 21, 39 -34.
[13] Sadeghi ravesh, M. and Khosravi, H., (2014). Using of the the linear allocation method in the evaluation desertification. Watershed Management Research, 105, 81-89.
[14] Sadeghi ravesh, M., Ahmadi, H., Zehtabian, Gh. and Thmoores, M., (2010). Application of Analytic Hierarchy Process (AHP) in the evaluation of desertification (study province: Khezrabad Yazd). RANGE & DESERT RESEARCH Iran, 17(1), 35-50.
[15] Sepehr, A., Ekhtesasi, M. and Almodaresi, A. (2012). Desertification measures to create a system based on the DPSIR (utilizing the fuzzy-Tapsys method). Geography and Environmental Planning, 23, 33-50.
[16] Sepehr, A. and Proyan, N. (2011). Mapping and Prioritization Vulnerability of desertification strategies based on Pramsh algorithms in Khorasan Razavi province. Earth science research, 8, 58-71.
[17] Sepehr, A. and Zucca, C.(2012). “Ranking Desertification Indicators Using TOPSIS Algorithm”. Journal of Natural Hazards, 63 (3), 1137-1153.
 
Volume 70, Issue 2
August 2017
Pages 385-398
  • Receive Date: 19 May 2017
  • Revise Date: 07 August 2017
  • Accept Date: 06 July 2017
  • First Publish Date: 23 July 2017