Influence of seasonal soil temperature variation and global warming on the seismic response of frozen soils in permafrost regions

2021 ◽  
Author(s):  
Jamin Park ◽  
Oh‐Sung Kwon ◽  
Luigi Di Sarno
Keyword(s):  
Global Warming ◽  
Soil Temperature ◽  
Seismic Response ◽  
Temperature Variation ◽  
Frozen Soils ◽  
Permafrost Regions

Analytical Model to Predict Nonhomogeneous Soil Temperature Variation

1995 ◽  
Vol 117 (2) ◽  
pp. 100-107 ◽  
Author(s):  
M. Krarti ◽  
D. E. Claridge ◽  
J. F. Kreider
Keyword(s):  
Thermal Properties ◽  
Soil Temperature ◽  
Temperature Variation ◽  
Analytical Model ◽  
Soil Surface ◽  
Deep Soil ◽  
Soil Thermal Properties ◽  
Order Of Magnitude ◽  
Soil Surface Temperature ◽  
Annual Time

This paper presents an analytical model to predict the temperature variation within a multilayered soil. The soil surface temperature is assumed to have a sinusoidal time variation for both daily and annual time scales. The soil thermal properties in each layer are assumed to be uniform. The model is applied to two-layered, three-layered, and to nonhomogeneous soils. In case of two-layered soil, a detailed analysis of the thermal behavior of each layer is presented. It was found that as long as the order of magnitude of the thermal diffusivity of soil surface does not exceed three times that of deep soil; the soil temperature variation with depth can be predicted accurately by a simplified model that assumes that the soil has constant thermal properties.

scholarly journals Experimental Test and Prediction Model of Soil Thermal Conductivity in Permafrost Regions

2020 ◽  
Vol 10 (7) ◽  
pp. 2476 ◽  
Author(s):  
Fu-Qing Cui ◽  
Zhi-Yun Liu ◽  
Jian-Bing Chen ◽  
Yuan-Hong Dong ◽  
Long Jin ◽  
...  
Keyword(s):  
Neural Network ◽  
Thermal Conductivity ◽  
Prediction Model ◽  
Rbf Neural Network ◽  
Soil Thermal Conductivity ◽  
Engineering Applications ◽  
Frozen Soils ◽  
Fitting Method ◽  
Network Method ◽  
Permafrost Regions

Soil thermal conductivity is a dominant parameter of an unsteady heat-transfer process, which further influences the stability and sustainability of engineering applications in permafrost regions. In this work, a laboratory test for massive specimens is performed to reveal the distribution characteristics and the parameter-influencing mechanisms of soil thermal conductivity along the Qinghai–Tibet Engineering Corridor (QTEC). Based on the measurement data of 638 unfrozen and 860 frozen soil specimens, binary fitting, radial basis function (RBF) neural network and ternary fitting (for frozen soils) prediction models of soil thermal conductivity have been developed and compared. The results demonstrate that, (1) particle size and intrinsic heat-conducting capacity of the soil skeleton have a significant influence on the soil thermal conductivity, and the typical specimens in the QTEC can be classified as three clusters according to their thermal conductivity probability distribution and water-holding capacity; (2) dry density as well as water content sometimes does not have a strong positive correlation with thermal conductivity of natural soil samples, especially for multiple soil types and complex compositions; (3) both the RBF neural network method and ternary fitting method have favorable prediction accuracy and a wide application range. The maximum determination coefficient (R2) and quantitative proportion of relative error within ±10% ( P ± 10 % ) of each prediction model reaches up to 0.82, 0.88, 81.4% and 74.5%, respectively. Furthermore, because the ternary fitting method can only be used for frozen soils, the RBF neural network method is considered the optimal approach among all three prediction methods. This study can contribute to the construction and maintenance of engineering applications in permafrost regions.

Response of N2O and N2 Emissions in Forest Soils to Temperature Change across China

2020 ◽  
Author(s):  
Haoming Yu ◽  
Yunting Fang ◽  
Ronghua Kang
Keyword(s):  
Global Warming ◽  
Soil Temperature ◽  
Forest Soil ◽  
Temperature Change ◽  
Temperature Sensitivity ◽  
Forest Soils ◽  
Soil Samples ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
N Cycle

<p>N<sub>2</sub>O and N<sub>2</sub> Emissions from soil in terrestrial ecosystems is a crucial component of the global nitrogen (N) cycle. The response of these two gases emissions from forest soil to temperature change and its underlying mechanisms are essential for predicting N cycle to global warming. Despite the warming-induced effects on soil N cycle is considered to be positive in general, our understanding of temperature sensitivity (Q<sub>10</sub>) of N<sub>2</sub>O and N<sub>2</sub> emissions is rather limited. We quantified the Q<sub>10</sub> of N<sub>2</sub>O and N<sub>2</sub> emissions in forest soils and explored their major driving factors by conducting an incubation experiment using <sup>15</sup>N tracer (Na<sup>15</sup>NO<sub>3</sub>) with soil samples from nineteen forest sites from temperate to tropical zones. The environmental conditions largely varied: mean annual temperature (MAT) ranging from -5.4 to 21.5<sup>o</sup>C and mean annual precipitation (MAP) ranging from 300 to 2449 mm. The soil pH varied between 3.62 to 6.38. We incubated soil samples under an anaerobic condition with temperature from 5 to 35<sup>o</sup>C with an interval of 5<sup>o</sup>C for 12 or 24 hours, respectively. Soil temperature strongly affected the production of N<sub>2</sub>O and N<sub>2</sub>. N<sub>2</sub>O and N<sub>2</sub> production rates showed a positive exponential relation with incubate time and temperature for all forest soils. Our results showed that the Q<sub>10</sub> values ranged from 1.31 to 2.98 for N<sub>2</sub>O emission and 1.69 to 3.83 for N<sub>2</sub> emission, indicating a generally positive feedback of N<sub>2</sub>O and N<sub>2</sub> production to warming. Higher Q<sub>10</sub> values for N<sub>2</sub> than N<sub>2</sub>O implies that N<sub>2</sub> emission is more sensitive to temperature increase. The N<sub>2</sub>O/(N<sub>2</sub>O+N<sub>2</sub>) decreased with increasing temperature in fifteen of nineteen forest soils, suggesting that warming accelerates N<sub>2</sub> emission. Strong spatial variation in Q<sub>10</sub> were also observed, with tropical forest soils exhibiting high Q<sub>10</sub> values and relatively low Q<sub>10</sub> in temperate forest soils. This variation is attributed to the inherent differences in N biogeochemical cycling behavior between the microbial communities among sites. Despite soil temperature primarily controls the N<sub>2</sub>O and N<sub>2</sub> emissions, we  explored the effects of other factors such as pH, C/N, DOC and related functional genes. In addition, we partitioned N<sub>2</sub>O and N<sub>2</sub> emissions to different microbial processes (e.g., denitrification, co-denitrification and anammox). The results indicated that denitrification was the main pathway of N<sub>2</sub>O and N<sub>2</sub> production under anaerobic environment and the contribution increased as temperature rise.</p><p>Key words: Temperature sensitivity, N<sub>2</sub>O, N<sub>2</sub>, Forest soil, Nitrogen cycle, Global warming, Denitrification</p>

scholarly journals Sub-soil temperature variation and estimation of soil heat flux at Pune

MAUSAM ◽  
2021 ◽  
Vol 42 (4) ◽  
pp. 357-360
Author(s):  
A. CHOWDHURY ◽  
H. P. DAS ◽  
A. D. PUJARI
Keyword(s):  
Experimental Data ◽  
Heat Flux ◽  
Soil Temperature ◽  
Temperature Variation ◽  
Heat Balance ◽  
Thermal Wave ◽  
Heat Storage ◽  
Soil Heat Flux ◽  
Temperature Ranges ◽  
Maximum Minimum

Utilising experimental data from 23 November to 8.December 1989. temperature and heat storage variations at Pune have been studied, based on 3 hourly observations.. pattern of penetration of .thermal wave within the soil has been examined and time of occurrence of maximum/minimum temperatures discussed for various depths. Temperature ranges in different layers have been theoretically computed and compared with those based on actual observations. Heat balance at various depths has also been presented and discussed.

scholarly journals A parameterization of respiration in frozen soils based on substrate availability

2015 ◽  
Vol 12 (14) ◽  
pp. 12027-12059 ◽  
Author(s):  
K. Schaefer ◽  
E. Jafarov
Keyword(s):  
Time Scales ◽  
Substrate Availability ◽  
Scaling Factors ◽  
Frozen Soils ◽  
Water Fraction ◽  
Water Films ◽  
Incubation Experiments ◽  
Substrate Diffusion ◽  
Permafrost Regions ◽  
Continuous Loss

Abstract. Respiration in frozen soils is limited to thawed substrate within the thin water films surrounding soil particles. As temperatures decrease and the films become thinner, the available substrate also decreases, with respiration effectively ceasing at −8 °C. Traditional exponential scaling factors to model this effect do not account for substrate availability and do not work at the century to millennial time scales required to model the fate of the nearly 1700 Gt of carbon in permafrost regions. The exponential scaling factor produces a false, continuous loss of simulated permafrost carbon in the 20th century and biases in estimates of potential emissions as permafrost thaws in the future. Here we describe a new frozen biogeochemistry parameterization that separates the simulated carbon into frozen and thawed pools to represent the effects of substrate availability. We parameterized the liquid water fraction as a function of temperature based on observations and use this to transfer carbon between frozen pools and thawed carbon in the thin water films. The simulated volumetric water content (VWC) as a function of temperature is consistent with observed values and the simulated respiration fluxes as a function of temperature are consistent with results from incubation experiments. The amount of organic matter was the single largest influence on simulated VWC and respiration fluxes. Future versions of the parameterization should account for additional, non-linear effects of substrate diffusion in thin water films on simulated respiration. Controlling respiration in frozen soils based on substrate availability allows us to maintain a realistic permafrost carbon pool by eliminating the continuous loss caused by the original exponential scaling factors. The frozen biogeochemistry parameterization is a useful way to represent the effects of substrate availability on soil respiration in model applications that focus on century to millennial time scales in permafrost regions.

scholarly journals Contribution of the nongrowing season to annual N<sub>2</sub>O emissions from the continuous permafrost region in Northeast China

2020 ◽  
Author(s):  
Weifeng Gao ◽  
Dawen Gao ◽  
Liquan Song ◽  
Houcai Sheng ◽  
Tijiu Cai ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Climate Warming ◽  
Growing Season ◽  
N2o Emission ◽  
N2o Emissions ◽  
Permafrost Region ◽  
Carbon And Nitrogen ◽  
Annual Budget ◽  
The Mean ◽  
Permafrost Regions

Abstract. Permafrost regions store large amounts of soil organic carbon and nitrogen, which are major sources of greenhouse gas. With climate warming, permafrost regions are thawing, releasing an abundance of greenhouse gases to the atmosphere and contributing to climate warming. Numerous studies have shown the mechanism of nitrous oxide (N2O) emissions from the permafrost region during the growing season. However, little is known about the temporal pattern and drivers of nongrowing season N2O emissions from the permafrost region. In this study, N2O emissions from the permafrost region were investigated from June 2016 to June 2018 using the static opaque chamber method. Our aims were to quantify the seasonal dynamics of nongrowing season N2O emissions and its contribution to the annual budget. The results showed that the N2O emissions ranged from −35.75 to 74.16 μg·m−2·h−1 during the nongrowing season in the permafrost region. The mean N2O emission from the growing season were 1.75–2.86 times greater than that of winter and 1.31–1.53 times greater than that of spring thaw period due to the mean soil temperature of the different specified periods. The nongrowing season N2O emissions ranged from 0.89 to 1.44 kg ha−1, which contributed to 41.96–53.73 % of the annual budget, accounting for almost half of the annual emissions in the permafrost region. The driving factors of N2O emissions were different among during the study period, growing season, and nongrowing season. The N2O emissions from total two-year observation period and nongrowing season were mainly affected by soil temperature, while the N2O emissions from growing season were controlled by soil temperature, water table level, and their interactions. In conclusion, nongrowing season N2O emissions is an important component of annual emissions and cannot be ignored in the permafrost region.

scholarly journals The ERA5-Land soil temperature bias in permafrost regions

2020 ◽  
Vol 14 (8) ◽  
pp. 2581-2595 ◽  
Author(s):  
Bin Cao ◽  
Stephan Gruber ◽  
Donghai Zheng ◽  
Xin Li
Keyword(s):  
Soil Temperature ◽  
Land Surface ◽  
Soil Column ◽  
Land Surface Model ◽  
Surface Model ◽  
Active Layer Thickness ◽  
Near Surface ◽  
Warm Bias ◽  
Temperature Bias ◽  
Permafrost Regions

Abstract. ERA5-Land (ERA5L) is a reanalysis product derived by running the land component of ERA5 at increased resolution. This study evaluates ERA5L soil temperature in permafrost regions based on observations and published permafrost products. We find that ERA5L overestimates soil temperature in northern Canada and Alaska but underestimates it in mid–low latitudes, leading to an average bias of −0.08 ∘C. The warm bias of ERA5L soil is stronger in winter than in other seasons. As calculated from its soil temperature, ERA5L overestimates active-layer thickness and underestimates near-surface (<1.89 m) permafrost area. This is thought to be due in part to the shallow soil column and coarse vertical discretization of the land surface model and to warmer simulated soil. The soil temperature bias in permafrost regions correlates well with the bias in air temperature and with maximum snow height. A review of the ERA5L snow parameterization and a simulation example both point to a low bias in ERA5L snow density as a possible cause for the warm bias in soil temperature. The apparent disagreement of station-based and areal evaluation techniques highlights challenges in our ability to test permafrost simulation models. While global reanalyses are important drivers for permafrost simulation, we conclude that ERA5L soil data are not well suited for informing permafrost research and decision making directly. To address this, future soil temperature products in reanalyses will require permafrost-specific alterations to their land surface models.

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