Estimation of sodium adsorption ratio in a river with kernel-based and decision-tree models-Reference-Cited by-同舟云学术

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Estimation of sodium adsorption ratio in a river with kernel-based and decision-tree models

Published:2020-08-09 Issue:9 Volume:192 Page:
ISSN:0167-6369
Container-title:Environmental Monitoring and Assessment
language:en
Short-container-title:Environ Monit Assess

Author:

Sattari Mohammad Taghi^ORCID,Feizi Hajar^ORCID,Colak Muslume Sevba^ORCID,Ozturk Ahmet^ORCID,Apaydin Halit^ORCID,Ozturk Fazli^ORCID

Funder

Yükseköğretim Kurulu

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/s10661-020-08506-9.pdf

Reference30 articles.

1. Anonymous. (2008). Water quality monitoring in rivers of Turkey (in Turkish). Ankara: EIE Gen. Dir.

2. Anonymous. (2016). Ankara and agriculture (in Turkish) (p. 56). Ankara Dev: Agency Publ.

3. Apaydin, H., Sonmez, F. K., & Yildirim, Y. E. (2004). Spatial interpolation techniques for climate data in the GAP region in Turkey. Climate Research, 28, 31–40. https://doi.org/10.3354/cr028031

4. Asadollahfardi, G., Hemati, A., Moradinejad, S., Asadollahfardi, R. (2013). Sodium adsorption ratio (SAR) prediction of the Chalghazi River using artificial neural network (ANN) Iran 8, 169–178. https://doi.org/10.12944/CWE.8.2.02

5. Ayers, R.S., Westcot, D.W. (1985). Water quality for agriculture. Food and Agriculture Organization of the United Nations Rome.

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