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International Agrophysics

The Journal of Institute of Agrophysics of Polish Academy of Sciences

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2300-8725
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Soil temperature prediction from air temperature for alluvial soils in lower Indo-Gangetic plain

D. Barman
  • Corresponding author
  • ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata-700 120, West Bengal, India
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/ D.K. Kundu
  • ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata-700 120, West Bengal, India
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  • De Gruyter OnlineGoogle Scholar
/ Soumen Pal / Susanto Pal
  • ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata-700 120, West Bengal, India
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/ A.K. Chakraborty
  • ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata-700 120, West Bengal, India
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/ A.K. Jha
  • ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata-700 120, West Bengal, India
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/ S.P. Mazumdar
  • ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata-700 120, West Bengal, India
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/ R. Saha
  • ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata-700 120, West Bengal, India
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/ P. Bhattacharyya
  • ICAR-Central Research Institute for Jute and Allied Fibres, Barrackpore, Kolkata-700 120, West Bengal, India
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Published Online: 2017-02-07 | DOI: https://doi.org/10.1515/intag-2016-0034

Abstract

Soil temperature is an important factor in biogeochemical processes. On-site monitoring of soil temperature is limited in spatiotemporal scale as compared to air temperature data inventories due to various management difficulties. Therefore, empirical models were developed by taking 30-year long-term (1985-2014) air and soil temperature data for prediction of soil temperatures at three depths (5, 15, 30 cm) in morning (0636 Indian standard time) and afternoon (1336 Indian standard time) for alluvial soils in lower Indo-Gangetic plain. At 5 cm depth, power and exponential regression models were best fitted for daily data in morning and afternoon, respectively, but it was reverse at 15 cm. However, at 30 cm, exponential models were best fitted for both the times. Regression analysis revealed that in morning for all three depths and in afternoon for 30 cm depth, soil temperatures (daily, weekly, and monthly) could be predicted more efficiently with the help of corresponding mean air temperature than that of maximum and minimum. However, in afternoon, prediction of soil temperature at 5 and 15 cm depths were more precised for all the time intervals when maximum air temperature was used, except for weekly soil temperature at 15 cm, where the use of mean air temperature gave better prediction.

Keywords: soil temperature; air temperature; regression analysis; alluvial soil; Indo-Gangetic plain

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About the article

Received: 2016-08-31

Accepted: 2017-01-25

Published Online: 2017-02-07

Published in Print: 2017-01-01


Citation Information: International Agrophysics, ISSN (Online) 2300-8725, DOI: https://doi.org/10.1515/intag-2016-0034.

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© 2017 D. Barman et al., published by De Gruyter Open. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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