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Discussion papers | Copyright
https://doi.org/10.5194/hess-2018-466
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 08 Oct 2018

Research article | 08 Oct 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).

Implementation of salt-induced freezing point depression function into CoupModel_v5 for improvement of modelling seasonally frozen soils

Mousong Wu1,2,3, Per-Erik Jansson2, Jingwei Wu1, Xiao Tan1,4, Kang Wang1, Peng Chen5, and Jiesheng Huang1 Mousong Wu et al.
  • 1State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, 430072 Wuhan, Hubei, China
  • 2Department of Sustainable Development, Environmental Science and Engineering, KTH Royal Institute of Technology, 10044 Stockholm, Sweden
  • 3Department of Physical Geography and Ecosystem Science, Lund University, 23362 Lund, Sweden
  • 4State Key Laboratory of Hydraulics and Mountain River Engineering, College of Water Resource & Hydropower, Sichuan University, 610065 Chengdu, Sichuan, China
  • 5Department of Geology, Lund University, 23362 Lund, Sweden

Abstract. Soil freezing/thawing is important for soil hydrology and water management in cold regions. Salt in agricultural field impacts soil freezing/thawing characteristics and therefore soil hydrologic process. In this context, we conducted field experiments on soil water, heat and salt dynamics in two seasonally frozen agricultural regions of northern China to understand influences of salt on cold regions hydrology. We developed CoupModel by implementing impacts of salt on freezing point depression. We employed a Monte-Carlo sampling method to calibrate the new model with field observations. The new model improved soil temperature mean error (ME) by 16% to 77% when new freezing point equations were implemented into CoupModel. Nevertheless, we found that parameters related to energy balance and soil freezing characteristics in the new model were sensitive to soil heat and water transport at both sites. However, a systematic model sensitivity and calibration has shown to be able to improve model performance, with mean values of R2 from behavioral simulations for soil temperature at 5cm depth as high as 0.87 and 0.90, and mean value of R2 for simulated soil water (liquid or total water contents at 5cm depth) of 0.31 and 0.80 at site Qianguo and site Yonglian, respectively. This study provided a new approach considering influences of salt on soil freezing/thawing in numerical models and highlighted the importance of salt in soil hydrology of seasonally frozen agricultural soils.

Mousong Wu et al.
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