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Jafari, Ghazal
Salehan Institute of Higher Education
Civil Engineering, Building, Construction & Architecture

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Protecting River Environment through Proper Management of Material Mining by Matrix Method (Case Study of Ala River in Iran) Azarang, Farhang; Jafari, Ghazal; Karami, Maryam; Shafaie Bejestan, Mahmood
Civil Engineering Journal Vol 3, No 12 (2017): December
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1400.229 KB) | DOI: 10.28991/cej-030959

Abstract

Regarding the importance of rivers, appropriate management of aggregate mining is of great significance. Mining of river materials has a direct impact on environmental conditions of the river. Today, aggregate mining management represents a crucial topic in river engineering. Often selected based on the pattern of the considered river, matrix method provides a suitable approach to improve the river aggregate mining management. The present research aims at presenting the application of the matrix method in river material mining location evaluation. Given the capabilities of the matrix method for determining potential of mine area and aggregate mining method, this method can be seen as a suitable solution for reducing negative environmental impacts of river material mining. Ala River is one of the most important rivers streaming in Khouzestan Province (Iran), with its sediment load and mining potential being of critical importance. In this research, the reach of Ala River at the intersection of Rood-Zard River and Rahmhormoz diversion dam was studied for aggregate mining and application of matrix method. The main purpose of this work is to study the application of matrix method to Ala River. The results indicate braided pattern of the river and appropriateness of the matrix method. Available volume of aggregate for mining within the mentioned reach of Ala River was estimated as 50,000 m3, and scraping method at a maximum depth of 1 m was proposed for mining of the aggregates.
Co-Authors Azarang, Farhang Karami, Maryam Shafaie Bejestan, Mahmood