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Identification of dust generation potential in Mighan watershed

  • M. Fooladi
  • F. GhadimiEmail author
  • S. J. Sheikh Zakariaee
  • H. Rahimpour Bonab
Original Paper
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Abstract

In recent years, soil erosion and dust generation have been one of the major environmental challenges facing Iran. The purpose of this study is to provide a new strategy for identifying dust collection centers in the Arak Mighan Area. In this regard, the amount of erosion in rocky outcrops was investigated using the Fargas erodibility method. The results showed that shale and marl outcrops as well as sediments deposited during the quaternary period have the highest degree of erosion. To identify the potential of dust generation in the area, limiting layers or rock outcrops were considered in eliminating areas with no potential for dust production. Through field observations, the sedimentology map of the region and two maps of land types and land use were drawn and selected as the main layers. In this study, the limiting layers are standardized with the Bolin method and the main layers are fuzzy. The weight of the main layers was determined by the Bureau of land management method. After multiplying each of the main layers in the corresponding weight, the final incorporation of the layers was performed and the potential generation map of the area was produced in five classes. According to the results of this study, the central part of the Mighan wetland and its surroundings have the highest potential for dust generation in the region. Dust sources according to the type of use mostly include Mighan wetland and its surrounding fields and dried ponds, destroyed range, ruined agriculture lands, bare lands and irrigated agriculture lands.

Keywords

Fargas erodibility Dust potential Mighan watershed Arak 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study.

References

  1. Abdi N (2016) Evaluate the accuracy of Fargas and BLM models for identification of erosion intensity. Open J Geol 6:1457–1468CrossRefGoogle Scholar
  2. Abdi N, Mohammadi A (2014) Assessment fargas and BLM models for identification of erosion degree and critical sediment sources (Case Study: Aghbolagh Drainage Basin, Hashtrood City). Res J Environ Earth Sci 6(8):408–415CrossRefGoogle Scholar
  3. Al-Hemoud A, Al-Dousari A, Al-shatti A, Al-Khayat A, Behbahani W, Malak M (2018) Health impact assessment associated with exposure to PM10 and dust storms in Kuwait. Atmosphere 9:6.  https://doi.org/10.3390/atmos9010006 CrossRefGoogle Scholar
  4. Al-Hemoud A, Gasana J, Al-Aabbous A, Al-Shatti A, Al-Khayat A (2019) Disability adjusted life years (DALYs) in terms of years of life lost (YLL) due to premature adult mortalities and postneonatal infant mortalities attributed to PM2.5 and PM10 exposures in Kuwait. Int J Environ Res Public Health 15:2609.  https://doi.org/10.3390/ijerph15112609 CrossRefGoogle Scholar
  5. Banihabib N, Eshaghi M, Zare S, Farrokhi F (2016) The effect of oral administration of methylphenidate on hippocampal tissue in adult male rats. Neurosurg Q 26(4):315–318CrossRefGoogle Scholar
  6. Bartocci P, Fantozzi P, Fantozzi F (2017) Environmental impact of Sagrantino and Grechetto grapes cultivation for wine and vinegar production in central Italy. J Clean Prod 140:569–580CrossRefGoogle Scholar
  7. Bissonnais YL, Montier C, Jamagne M, Daroussin J, King D (2001) Mapping erosion risk for cultivated soil in France. CATENA 46(2–3):207–220.  https://doi.org/10.1016/S0341-8162(01)00167-9 Google Scholar
  8. Burnett RT, Pope CA III, Ezzati M, Olives C et al (2014) An integrated risk function for estimating the global burden of disease attributable to ambient fine particulate matter exposure. Environ Health Prospect 122(4):397–403.  https://doi.org/10.1289/ehp.1307049 Epub 2014 Feb 11 CrossRefGoogle Scholar
  9. Cerda A, Rodrigo-Comino J, Novara A et al (2018) Long-term impact of rain fed agricultural land abandonment on soil erosion in the Western Mediterranean basin. Prog Phys Geogr Earth Environ 42(2):202–219CrossRefGoogle Scholar
  10. Chappell A, Webb NP, Guerschman JP, Thomas DT, Mata G, Handcock RN, Leys JF, Butler HJ (2018) Improving ground cover monitoring for wind erosion assessment using MODIS BRDF parameters. Remote Sens Environ 204:756–768CrossRefGoogle Scholar
  11. Eckhoff RK (2009) Understanding dust explosions. The role of powder science and technology. J Loss Prev Process Ind 22(1):105–116CrossRefGoogle Scholar
  12. Erskine WD, Mahmoudzadeh A, Myers C (2002) Land use effects on sediment yields and soil loss rates in small basins of Triassic sandstone near Sydney, NSW, Australia. CATENA 49:271–287CrossRefGoogle Scholar
  13. Fantozzi F, Bartocci P, D’Alessandro B, Testarmata F, Fantozzi P (2015) Carbon footprint of truffle sauce in central Italy by direct measurement of energy consumption of different olive harvesting techniques. J Clean Prod 87:188–196CrossRefGoogle Scholar
  14. Fargas D, Martínez-Casanovas JA, Poch R (1997) Identification of critical sediment source areas at regional level. J Phys Chem Earth 22:355–359CrossRefGoogle Scholar
  15. Funk R (2015) Assessment and measurement of wind erosion; novel methods for monitoring and managing land and water resources in Siberia, Part of the Springer Water book series (SPWA), vol 21, Chap. 18, pp 425–449Google Scholar
  16. Goudie AS, Middleton NJ (2001) Saharan dust storms: nature and consequences. Earth Sci Rev 56:179–204CrossRefGoogle Scholar
  17. Horton RE (1945) Erosional development of steams and their drainage basins; hydrolophysical approach to quantitative morphology. Bulletin of the Geological Society of America, LVI, pp 275–370Google Scholar
  18. Kaskaoutisa DG, Kambezidisa HD, Nastosb PT, Kosmopoulosb PG (2008) Study on an intense dust storm over Greece. Atmos Environ 42:6884–6896CrossRefGoogle Scholar
  19. Miller SD, Kuciauskas AP, Qiang MLS, Je Reid, Breed DW, Walker AL, Mandoos AAI (2008) Haboob dust storms of the southern Arabian Peninsula. J Geophys Res 113:D01202.  https://doi.org/10.1029/2007JD008550 Google Scholar
  20. Morgan RPC (1996) Soil erosion and conservation, 2nd edn. Silsoe College, Cranfield University, Bedford, p 198Google Scholar
  21. Noori H, Karami H, Farzin S, Siadatmousavi SM, Mojaradi B, Kisi O (2018) Investigation of RS and GIS techniques on MPSIAC model to estimate soil erosion. Nat Hazards 91(1):221–238CrossRefGoogle Scholar
  22. Pan C, Shangguan Z, Lei T (2006) Influences of grass and moss on runoff and sediment yield on sloped loess surfaces under simulated rainfall. Hydrol Process 20:3815–3824CrossRefGoogle Scholar
  23. Rashki A, Kaskaoutis DG, Goudie AS, Kahn RA (2013) Dryness of ephemeral lakes and consequences for dust activity: the case of the Hamoun drainage basin, Southeastern Iran. Sci Total Environ 463–464:552–564.  https://doi.org/10.1016/j.scitotenv.2013.06.045 CrossRefGoogle Scholar
  24. Shao Y (2008) Physics and modelling of wind erosion, 2nd edn. Springer, BerlinGoogle Scholar
  25. Turner LB, Fuhrerb M, Wuellnercd H, Menendezd B, Dunne Roger G (2018) Scientific case studies in land-use driven soil erosion in the central United States: why soil potential and risk concepts should be included in the principles of soil health. Int Soil Water Conserv Res 6(1):63–78CrossRefGoogle Scholar
  26. Woldemariam GW, Derribew Iguala A, Tekalign S (2018) Spatial modeling of soil erosion risk and its implication for conservation planning: the case of the Gobele Watershed, East Hararghe Zone, Ethiopia. Land 7:25.  https://doi.org/10.3390/land7010025 (force base, Illinois (1991), Virginia, pp 16 and 483) CrossRefGoogle Scholar
  27. Xie J, Yang C, Zhou B, Huang Q (2010) High-performance computing for the simulation of dust storms. Comput Environ Urban Syst 34(4):278–290CrossRefGoogle Scholar
  28. Zhang LW, Chen X, Xue XD, Sun M, Han B et al (2014) Long-term exposure to high particulate matter pollution and cardiovascular mortality: a 12-year cohort study in four cities in northern China. Environ Int 62:41–47.  https://doi.org/10.1016/j.envint.2013.09.012 CrossRefGoogle Scholar
  29. Zheng X (2009) Mechanics of wind-blown sand movements. Springer, BerlinCrossRefGoogle Scholar
  30. Zizala D, Zadorova T, Kapicka J (2017) Assessment of soil degradation by erosion based on analysis of soil properties using aerial hyperspectral images and ancillary data, Czech Republic. Remote Sens 9:28.  https://doi.org/10.3390/rs9010028 CrossRefGoogle Scholar

Copyright information

© Islamic Azad University (IAU) 2019

Authors and Affiliations

  • M. Fooladi
    • 1
  • F. Ghadimi
    • 2
    Email author
  • S. J. Sheikh Zakariaee
    • 1
  • H. Rahimpour Bonab
    • 3
  1. 1.Department of GeologyIslamic Azad University, Science and Research BranchTehranIran
  2. 2.Department of Mining EngineeringArak University of TechnologyArākIran
  3. 3.Department of GeologyTehran UniversityTehranIran

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