Numerical modeling of soil temperature variation under an extreme desert climate

被引:1
|
作者
Rios-Arriola, J. [1 ]
Gomez-Arias, E. [2 ]
Zavala-Guillen, I. [3 ]
Velazquez-Limon, N. [1 ]
Bojorquez-Morales, G. [4 ]
Lopez-Velazquez, J. E. [5 ]
机构
[1] Univ Autonoma Baja Calif, Ctr Estudio Energias Renovables CEENER, Inst Ingn, Mexicali 21280, Mexico
[2] CONACYT Ctr Invest Cient & Educ Super Ensenada, Ensenada 22860, BC, Mexico
[3] Ctr Invest Cient & Educ Super Ensenada, Ensenada 22860, BC, Mexico
[4] Univ Autonoma Baja Calif, Fac Arquitectura, Mexicali 21280, Mexico
[5] Univ Autonoma Baja Calif, Lab Meteorol & Climatol, Inst Ingn, Mexicali 21280, BC, Mexico
关键词
Soil temperature variation; Extreme climate; Soil temperature measurements; Soil surface water content; PREDICT GROUND TEMPERATURE; HEAT-EXCHANGERS; WATER;
D O I
10.1016/j.geothermics.2023.102731
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The soil temperature profile is useful for different engineering, architecture, and agriculture areas. In recent years, the growth of direct uses of geothermal energy has increased the interest in soil temperature prediction models. This research paper numerically models the soil temperature variation under extreme desert climate conditions and compares it with experimental data measured on-site to evaluate the reliability of numerical models based on the one-dimensional transient state heat conduction equation as a tool for the evaluation of low enthalpy geothermal resource using meteorological data and soil thermal properties. From the study results, it can be concluded that the numerical models present temperature values close to those measured experimentally. The model that presents the more significant mismatches concerning the experimental data is the 1 m model, presenting the following statistical values; R2 of 0.97, mean absolute error of 0.61 degrees C, RMSE of 0.76 degrees C, NRMSE of 3.01%, and a MBIAS of 0.23. Although the numerical models present values are close to those measured, some coefficients, such as the soil surface water content greatly influence the model's accuracy regardless of depth.
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页数:10
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