Using multivariate adaptive regression splines and extremely randomized trees algorithms to predict dust events frequency around an international wetland and prioritize its drivers-Reference-Cited by-同舟云学术

Using multivariate adaptive regression splines and extremely randomized trees algorithms to predict dust events frequency around an international wetland and prioritize its drivers

Published:2021-06-22 Issue:7 Volume:193 Page:
ISSN:0167-6369
Container-title:Environmental Monitoring and Assessment
language:en
Short-container-title:Environ Monit Assess

Author:

Ebrahimi-Khusfi Zohre^ORCID,Nafarzadegan Ali Reza^ORCID,Khosroshahi Mohammad

Publisher

Springer Science and Business Media LLC

Subject

Management, Monitoring, Policy and Law,Pollution,General Environmental Science,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s10661-021-09198-5.pdf

Reference74 articles.

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2. Adib, A., Oulapour, M., & Chatroze, A. (2018). Effects of wind velocity and soil characteristics on dust storm generation in Hawr-al-Azim Wetland, Southwest Iran Caspian. Journal of Environmental Sciences, 16, 333–347. https://doi.org/10.22124/cjes.2018.3202

3. Aghasi, B., Jalalian, A., Khademi, H., & Besalatpour, A. A. (2019). Relationship between dust deposition rate and soil characteristics in an arid region of Iran. Atmósfera, 32, 115–128. https://doi.org/10.20937/atm.2019.32.02.03

4. Aghasi, B., Jalalian, A., Khademi, H., Toomanian, N., & Besalatpour, A. A. (2020). Dust production crisis following the recent droughts in the eastern part of the Zayandeh Rud River Basin. In: Standing up to climate change. Springer, pp 239–261. https://doi.org/10.1007/978-3-030-50684-1_11

5. Artaxo, P., et al. (2013). Atmospheric aerosols in Amazonia and land use change: From natural biogenic to biomass burning conditions. Faraday Discussions, 165, 203–235. https://doi.org/10.1039/c3fd00052d

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