Articles | Volume 25, issue 8
https://doi.org/10.5194/hess-25-4357-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-4357-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Aug 2021
Research article |
| 10 Aug 2021
| 10 Aug 2021
Daily soil temperature modeling improved by integrating observed snow cover and estimated soil moisture in the USA Great Plains
Haidong Zhao
Department of Agronomy, Kansas State University, Manhattan, KS, USA
Gretchen F. Sassenrath
Department of Agronomy, Kansas State University, Manhattan, KS, USA
Southeast Research and Extension Center, Kansas State University, Parsons, KS, USA
Mary Beth Kirkham
Department of Agronomy, Kansas State University, Manhattan, KS, USA
Nenghan Wan
Department of Agronomy, Kansas State University, Manhattan, KS, USA
Xiaomao Lin
CORRESPONDING AUTHOR
Department of Agronomy, Kansas State University, Manhattan, KS, USA
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Short summary
This study was done to develop an improved soil temperature model for the USA Great Plains by using common weather station variables as inputs. After incorporating knowledge of estimated soil moisture and observed daily snow depth, the improved model showed a near 50 % gain in performance compared to the original model. We conclude that our improved model can better estimate soil temperature at the surface soil layer where most hydrological and biological processes occur.
This study was done to develop an improved soil temperature model for the USA Great Plains by...
