气候变化领域集成服务门户(CCPortal): A new model for predicting soil thermal conductivity for dry soils

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DOI	10.1016/j.ijthermalsci.2022.107487
	A new model for predicting soil thermal conductivity for dry soils
	Du, Yizhen; Li, Ren; Wu, Tonghua; Yang, Chengsong; Zhao, Lin; Hu, Guojie; Xiao, Yao; Yang, Shuhua; Ni, Jie; Ma, Junjie; Shi, Jianzong; Qiao, Yongping
通讯作者	Li, R (通讯作者)，Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, 320 Donggang West Rd, Lanzhou 730000, Peoples R China.
发表日期	2022
ISSN	1290-0729
EISSN	1778-4166
卷号	176
英文摘要	Soil thermal conductivity (lambda), describing the ability of transferring heat in the soil, plays an important role in soil thermal behavior. The estimation of lambda at dryness (lambda(dry)) is essential for obtaining accurate lambda. This study aims to develop a new model for lambda(dry) across a wide range of the soil dry density (rho(d)) for soils with different textures. The lambda(dry) measurements of 75 soil samples from literature and 19 new soils from Qinghai-Tibet Plateau are used to establish the segmented relationships between lambda(dry) and rho(d) based on clustering algorithms. Our analyses reveal that when rho(d) < 1.4 g cm(-3), rho(d) significantly influences lambda(dry), while for rho(d & nbsp;)>= 1.4 g cm(-3), other soil properties must be taken into account. So, the performances of 12 widely used models are evaluated in these two different rho(d)& nbsp;ranges. Results show that when rho(d)& nbsp;< 1.4 g cm(-3), the previous developed models generally perform well. On the contrary, all these models produce large calculation errors when rho(d)& nbsp;>=& nbsp;1.4 g cm(-3). This further confirms the necessity of segmentation. Finally, with a demarcation point of 1.4 g cm(-3), a new model with different calculation methods is proposed herein for predicting dry. The new model exhibits the highest accuracy in predicting & nbsp;lambda(dry) with the highest correlation coefficient (R), lowest root mean square error (RMSE), and smaller mean bias error values; compared to the previous models, the new model RMSE values are reduced by 16.6% on average for soils with rho(d)& nbsp;< 1.4 g cm(-3)& nbsp;and 21.0% for rho(d)& nbsp;>=& nbsp;1.4 g cm(-3), respectively. Namely, the new model is highly suitable for studying lambda(dry)& nbsp;for different rho(d)& nbsp;due to its simplicity and applicability.
关键词	PERMAFROST REGIONS WATER-CONTENT TEMPERATURE SANDY FIELD PARAMETERIZATIONS UNFROZEN LAYER PROBE ROCK
英文关键词	Soil thermal conductivity; Dry soil; Model; Soil dry density
语种	英语
WOS研究方向	Thermodynamics ; Engineering
WOS类目	Thermodynamics ; Engineering, Mechanical
WOS记录号	WOS:000778314500002
来源期刊	INTERNATIONAL JOURNAL OF THERMAL SCIENCES
来源机构	中国科学院西北生态环境资源研究院
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/253694
作者单位	[Du, Yizhen; Li, Ren; Wu, Tonghua; Hu, Guojie; Xiao, Yao; Yang, Shuhua; Ma, Junjie; Shi, Jianzong; Qiao, Yongping] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, State Key Lab Cryospher Sci, Cryosphere Res Stn Qinghai Tibet Plateau, Lanzhou 730000, Peoples R China; [Du, Yizhen; Ni, Jie] ZaoZhuang Univ, Coll Tourism Resources & Environm, Zaozhuang 277160, Peoples R China; [Wu, Tonghua] Southern Marine Sci & Engn Guangdong Lab, Guangzhou 511458, Peoples R China; [Yang, Chengsong] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, State Key Lab Frozen Soil Engn, Lanzhou 730000, Peoples R China; [Zhao, Lin] Nanjing Univ Informat Sci & Technol, Sch Geog Sci, Nanjing 210044, Peoples R China
推荐引用方式 GB/T 7714	Du, Yizhen,Li, Ren,Wu, Tonghua,et al. A new model for predicting soil thermal conductivity for dry soils[J]. 中国科学院西北生态环境资源研究院,2022,176.
APA	Du, Yizhen.,Li, Ren.,Wu, Tonghua.,Yang, Chengsong.,Zhao, Lin.,...&Qiao, Yongping.(2022).A new model for predicting soil thermal conductivity for dry soils.INTERNATIONAL JOURNAL OF THERMAL SCIENCES,176.
MLA	Du, Yizhen,et al."A new model for predicting soil thermal conductivity for dry soils".INTERNATIONAL JOURNAL OF THERMAL SCIENCES 176(2022).