Preprints
https://doi.org/10.5194/hess-2021-164
https://doi.org/10.5194/hess-2021-164

  30 Mar 2021

30 Mar 2021

Review status: a revised version of this preprint was accepted for the journal HESS and is expected to appear here in due course.

Daily soil temperature modeling improved by integrating observed snow cover and estimated soil moisture in the U.S. Great Plains

Haidong Zhao1, Gretchen F. Sassenrath2,3, Mary Beth Kirkham3, Nenghan Wan1, and Xiaomao Lin1 Haidong Zhao et al.
  • 1Department of Agronomy, Kansas Climate Center, Kansas State University, Manhattan, KS
  • 2Southeast Research and Extension Center, Parsons, KS
  • 3Department of Agronomy, Kansas State University, Manhattan, KS

Abstract. Soil temperature data are vital for explaining many biological, physical, and hydrological process in soil surface layer and in near surface atmosphere. However, soil temperature data are limited in the U.S. Great Plains. In this study we developed a model for predicting daily soil temperature at the 10 cm depth across Nebraska, Kansas, Oklahoma, and parts of Texas. This improved model was developed and tested by using 87 weather stations. Our results indicated that our improved model, on average, is able to predict daily soil temperature 0.6 oC better than original methods for all stations in the U.S. Great Plains. This improved model can provide us a daily soil temperature modeling tool that overcomes the deficiencies of soil temperature data used in applications for climatic changes, hydrological modeling, and winter wheat production in the U.S. Great Plains.

Haidong Zhao et al.

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-164', Anonymous Referee #1, 11 May 2021
    • AC1: 'Reply on RC1', Xiaomao Lin, 01 Jun 2021
  • RC2: 'Comment on hess-2021-164', Anonymous Referee #2, 13 May 2021
    • AC2: 'Reply on RC2', Xiaomao Lin, 01 Jun 2021

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-164', Anonymous Referee #1, 11 May 2021
    • AC1: 'Reply on RC1', Xiaomao Lin, 01 Jun 2021
  • RC2: 'Comment on hess-2021-164', Anonymous Referee #2, 13 May 2021
    • AC2: 'Reply on RC2', Xiaomao Lin, 01 Jun 2021

Haidong Zhao et al.

Haidong Zhao et al.

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Short summary
This study was to develop an improved soil temperature model for the U.S. Great Plains by using common weather station variables as inputs. After incorporating knowledge of estimated soil moisture and 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 estimate better soil temperature at the surface soil layer where most hydrological and biological processes occur.