year 4, Issue 3 (2014 autumn 2014)                   E.E.R. 2014, 4(3): 33-46 | Back to browse issues page

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Matkan 1 A, Tanasan 2, Shakiba 3, Mirbagheri 4, Akbari 5 K, Shaygan 6 M. Designing a multi-objective optimization model of Management Canopy, based on genetic algorithms Approach to soil conservation - Case study: Kerman- Roodbar watershed. E.E.R. 2014; 4 (3) :33-46
URL: http://magazine.hormozgan.ac.ir/article-1-109-en.html
Shahid Beheshti University , tanasan.mohammad@gmail.com
Abstract:   (6556 Views)

Reducing the amount and intensity of surface runoff, thus reducing erosion is one of the important aspects of natural resource management, watershed management and soil conservation. Land surface conditions and particularly vegetation is Mitigating or aggravating factor in erosion. Studies on the effect of ground cover to reduce erosion rates indicate that is not necessary to ground cover to reduce erosion. The purpose of this research is to design a model to optimize pasture cover, NSGA-II algorithm is based on the GIS platform. To illustrate identified areas whit the sensitivity of the corrosive medium to large and studied of grassland types, then using the ability NSGA-II algorithm’s to determined optimum percentage of canopy. Output of the model might be introduced patterns for canopy that reduction of erosion to an acceptable level and enhancing the economic benefits. The developed model in the study was implemented in Kerman-Rodbar watershed Evaluation results show that the model is able to suggest patterns to canopy planning that reduce erosion with and enhancing the economic benefits that each of these patterns for canopy will be selected and implemented in based on local conditions and expertise. One of the patterns, capable reduce erosion of 4.3 in current situation to about 1.2, Without charge, but with proper management Canopy That it is Show The importance of proper management of Coverage. In this study, use of Hyper Volume and Value Path methods for the efficiency and accuracy of model. The results show that the model is able to good optimization process and results of the model will be reliable.

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Type of Study: Research |
Received: 2014/05/3 | Published: 2015/10/15

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