scholarly journals Development of Shallow-Depth Soil Temperature Estimation Model Based on Thermal Response in Permafrost Area

2018 ◽  
Vol 8 (10) ◽  
pp. 1886 ◽  
Author(s):  
Keunbo Park ◽  
Heekwon Yang ◽  
Bang Lee ◽  
Dongwook Kim
Keyword(s):  
Soil Temperature ◽  
Temperature Measurement ◽  
Thermal Response ◽  
Estimation Model ◽  
Temperature Estimation ◽  
Soil Temperatures ◽  
Different Depths ◽  
The Relationship ◽  
Temperature Depth ◽  
Good Agreement

A soil temperature estimation model for increasing depth in a permafrost area in Alaska near the Bering Sea is proposed based on a thermal response concept. Thermal response is a measure of the internal physical heat transfer of soil due to transferred heat into the soil. Soil temperature data at different depths from late spring to the early autumn period at multiple permafrost sites were collected using automatic sensor measurements. From the analysis results, a model was established based on the relationship between the normalized cumulative soil temperatures (CRCST*i,m and CST*ud,m) of two different depths. CST*ud,m is the parameter of the soil temperature measurement at a depth of 5 cm, and CRCST*i,m is the parameter of the soil temperature measured at deeper depths of i cm (i = 10, 15, 20, and 30). Additionally, the fitting parameters of the mathematical models of the CRCST*i,m–CST*ud,m relationship were determined. The measured soil temperature depth profiles at a different site were compared with their predicted soil temperatures using the developed model for the model validation purpose. Consequently, the predicted soil temperatures at different soil depths using the soil temperature measurement of the uppermost depth (5 cm) were in good agreement with the measured results.

scholarly journals Development of a Shallow-Depth Soil Temperature Estimation Model Based on Air Temperatures and Soil Water Contents in a Permafrost Area

2020 ◽  
Vol 10 (3) ◽  
pp. 1058
Author(s):  
Keunbo Park ◽  
Yongwon Kim ◽  
Kichoel Lee ◽  
Dongwook Kim
Keyword(s):  
Soil Temperature ◽  
Soil Water ◽  
Air Temperature ◽  
Thermal Response ◽  
Shallow Depth ◽  
Estimation Model ◽  
Temperature Estimation ◽  
Layer Development ◽  
Water Contents ◽  
Soil Water Contents

A model for predicting shallow depth soil temperatures is important and effective to assess the changes in soil conditions related to global climate change and local disturbances. Shallow-depth soil temperature estimation model in cold region in Alaska is developed based on thermal response using air temperature and shallow-depth soil water content during active layer development period of 160 days from May to October. Among the seven soil temperature measurement sites, data from four sites were used for model development, and the remaining three sites were used for model validation. Near the middle of the seven measurement sites, air temperature is monitored at one location. The proposed model implemented concepts of thermal response and cumulative temperature. Temperatures and soil water contents were measured using automated remote sensing technology. Consequently, it was confirmed that the developed model enables fast and accurate assessment of shallow-depth soil temperature during active soil layer development period.

scholarly journals Quality control of 10-min soil temperatures data at RMI

2015 ◽  
Vol 12 (1) ◽  
pp. 23-30 ◽  
Author(s):  
C. Bertrand ◽  
L. González Sotelino ◽  
M. Journée
Keyword(s):  
Quality Control ◽  
Soil Temperature ◽  
Bare Soil ◽  
Climate Conditions ◽  
Air Temperatures ◽  
Temperature Observation ◽  
Soil Temperatures ◽  
Different Depths ◽  
Temperature Records ◽  
Energy Processes

Abstract. Soil temperatures at various depths are unique parameters useful to describe both the surface energy processes and regional environmental and climate conditions. To provide soil temperature observation in different regions across Belgium for agricultural management as well as for climate research, soil temperatures are recorded in 13 of the 20 automated weather stations operated by the Royal Meteorological Institute (RMI) of Belgium. At each station, soil temperature can be measured at up to 5 different depths (from 5 to 100 cm) in addition to the bare soil and grass temperature records. Although many methods have been developed to identify erroneous air temperatures, little attention has been paid to quality control of soil temperature data. This contribution describes the newly developed semi-automatic quality control of 10-min soil temperatures data at RMI.

scholarly journals Soil Temperature Estimation with Meteorological Parameters by Using Tree-Based Hybrid Data Mining Models

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1407
Author(s):  
Mohammad Taghi Sattari ◽  
Anca Avram ◽  
Halit Apaydin ◽  
Oliviu Matei
Keyword(s):  
Soil Temperature ◽  
Soil Depth ◽  
Sunshine Duration ◽  
Evaluation Criteria ◽  
Nonlinear Problems ◽  
Soil Temperatures ◽  
Different Depths ◽  
Windowing Technique ◽  
Using Data ◽  
Research Decision

The temperature of the soil at different depths is one of the most important factors used in different disciplines, such as hydrology, soil science, civil engineering, construction, geotechnology, ecology, meteorology, agriculture, and environmental studies. In addition to physical and spatial variables, meteorological elements are also effective in changing soil temperatures at different depths. The use of machine-learning models is increasing day by day in many complex and nonlinear branches of science. These data-driven models seek solutions to complex and nonlinear problems using data observed in the past. In this research, decision tree (DT), gradient boosted trees (GBT), and hybrid DT–GBT models were used to estimate soil temperature. The soil temperatures at 5, 10, and 20 cm depths were estimated using the daily minimum, maximum, and mean temperature; sunshine intensity and duration, and precipitation data measured between 1993 and 2018 at Divrigi station in Sivas province in Turkey. To predict the soil temperature at different depths, the time windowing technique was used on the input data. According to the results, hybrid DT–GBT, GBT, and DT methods estimated the soil temperature at 5 cm depth the most successfully, respectively. However, the best estimate was obtained with the DT model at soil depths of 10 and 20 cm. According to the results of the research, the accuracy rate of the models has also increased with increasing soil depth. In the prediction of soil temperature, sunshine duration and air temperature were determined as the most important factors and precipitation was the most insignificant meteorological variable. According to the evaluation criteria, such as Nash-Sutcliffe coefficient, R, MAE, RMSE, and Taylor diagrams used, it is recommended that all three (DT, GBT, and hybrid DT–GBT) data-based models can be used for predicting soil temperature.

scholarly journals Recognition of Changes in Air and Soil Temperatures at a Station Typical of China’s Subtropical Monsoon Region (1961–2018)

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Ming-jin Zhan ◽  
Lingjun Xia ◽  
Longfei Zhan ◽  
Yuanhao Wang
Keyword(s):  
Climate Change ◽  
Soil Temperature ◽  
Air Temperature ◽  
Soil Depth ◽  
Terrestrial Ecosystems ◽  
Soil Temperatures ◽  
Different Depths ◽  
Change Impact ◽  
The Mean ◽  
Autumn And Winter

Trends in soil temperature are important but rarely reported indicators of climate change. Based on daily air and soil temperatures (depth: 0, 20, 80, and 320 cm) recorded at the Nanchang Weather Station (1961–2018), this study investigated the variation trend, abrupt changes, and years of anomalous annual and seasonal mean air and soil temperatures. The differences and relationships between annual air and soil temperatures were also analyzed. The results showed close correlations between air temperature and soil temperature at different depths. Annual and seasonal mean air and soil temperatures mainly displayed significant trends of increase over the past 58 years, although the rise of the mean air temperature and the mean soil temperature was asymmetric. The rates of increase in air temperature and soil temperature (depth: 0, 20, and 80 cm) were most obvious in spring; the most significant increase in soil temperature at the depth of 320 cm was in summer. Mean soil temperature displayed a decreasing trend with increasing soil depth in both spring and summer. Air temperature was lower than the soil temperature at depths of 0 and 20 cm but higher than the soil temperature at depths of 80 and 320 cm in spring and summer. Mean ground temperature had a rising trend with increasing soil depth in autumn and winter. Air temperature was lower than the soil temperature at all depths in autumn and winter. Years with anomalously low air temperature and soil temperature at depths of 0, 20, 80, and 320 cm were relatively consistent in winter. Years with anomalous air and soil temperatures (depths: 0, 20, and 80 cm) were generally consistent; however, the relationship between air temperature and soil temperature at 320 cm depth was less consistent. The findings provide a basis for understanding and assessing climate change impact on terrestrial ecosystems.

scholarly journals Horizontal Heat Impacts of a Building on Various Soil Layer Depths in Beijing City

2019 ◽  
Vol 11 (7) ◽  
pp. 1979 ◽  
Author(s):  
Hongxuan Zhou ◽  
Huan Chen ◽  
Yue Wu ◽  
Jianfeng Zha ◽  
Jing Sun ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Thermal Environment ◽  
Soil Layer ◽  
Heat Sources ◽  
Beijing City ◽  
Soil Temperatures ◽  
Stabilized Soil ◽  
Different Depths ◽  
Urban Thermal Environment ◽  
Beijing China

There is a lot of research on the urban thermal environment, mainly on air temperature. However, fewer studies focus on soil temperature that is influenced by built environment, especially on the horizontal heat impacts from buildings. In this research, soil temperature was investigated at different depths in Beijing, China, to compare the differences between two locations. One was next to the building and the other was far away from the building (10 m). The locations are referred to as site A and site B, respectively. These two sites were chosen to compare the differences in soil temperatures between them to present the horizontal heat impact from facade. The results show that facades caused horizontal heat impacts on the soil at different depths in the winter, spring, and summer. Basically, facades functioned as heat sources to the soil surrounding them. The mean temperature differences between the two sites were 3.282, 4.698 and 0.316 K in the winter, spring and summer, respectively. Additionally, the thermal effects of the buildings were not only exhibited as higher soil temperatures but the temporal appearance of the maximum and minimum temperature was also influenced. Buildings functioned as heat sources to heat soil in the winter and spring and stabilized soil temperature so that it would not fluctuate too much in the summer. Additionally, the coefficient of variation indicates that buildings primarily increased the soil temperature in the winter and spring and stabilized the soil temperature in the summer.

scholarly journals Soil temperature estimation at different depths, using remotely-sensed data

2020 ◽  
Vol 19 (1) ◽  
pp. 277-290 ◽  
Author(s):  
Ran HUANG ◽  
Jian-xi HUANG ◽  
Chao ZHANG ◽  
Hong-yuan MA ◽  
Wen ZHUO ◽  
...  
Keyword(s):  
Soil Temperature ◽  
Remotely Sensed ◽  
Remotely Sensed Data ◽  
Temperature Estimation ◽  
Different Depths

Parameter Optimization for a Temperature Estimation Model

2003 ◽  
Author(s):  
J. Cole Smith ◽  
Alfonso Ortega ◽  
Colleen M. Gabel ◽  
Dale Henderson
Keyword(s):  
Optimization Problems ◽  
Thermal Response ◽  
Future Research ◽  
Optimization Approach ◽  
Estimation Model ◽  
Temperature Estimation ◽  
Nonconvex Optimization Problems ◽  
The Subject

We consider a problem arising in designing Compact Thermal Models (CTMs) for the purpose of simulating the thermal response of a package. CTMs are often preferred over more detailed models due to their minimal representation and the reduced computations required to obtain accurate nodal temperature predictions under hypothetical scenarios. The quality of CTM performance depends on the determination of an appropriate set of parameters that drive the model. The subject of this paper is a heuristic nonlinear optimization approach to computing the set of CTM parameters that best predicts the thermal response of a package. Our algorithm solves a series of one-dimensional nonconvex optimization problems to obtain these parameters, exploiting the special structure of the CTM in order to improve both the execution time of the algorithm and the quality of the CTM performance. We conclude the paper by providing a brief array of computational results as a proof of concept, along with several possible future research extensions.

scholarly journals ON THE ISSUE OF STUDYING THE TEMPERATURE REGIME OF THE BASTAK NATURE RESERVE SOILS WITH THE PROFESSIONAL WEATHER STATION «SOKOL-M»

2021 ◽  
Vol 24 (2-3) ◽  
pp. 85-89
Author(s):  
А.M. Alexandrova
Keyword(s):  
Soil Temperature ◽  
Temperature Regime ◽  
Soil Profile ◽  
Nature Reserve ◽  
Heat Propagation ◽  
Weather Station ◽  
Soil Temperatures ◽  
Different Depths ◽  
Using Data

The paper presents the experience of using data on soil temperature obtained with the help of a professional weather station «Sokol-M» in the Bastak nature reserve. The author has made the analysis of average daily air and soil temperature indicators at different depths. The process of heat propagation deep into the soil is observed, due to the absence of negative soil temperatures at a depth of 25 cm, with negative indicators in the upper 10 cm of the soil profile.

AN EMPIRICAL METHOD OF ESTIMATING SOIL TEMPERATURE ON CROPPED LAND ON CANADIAN PRAIRIES

1981 ◽  
Vol 61 (3) ◽  
pp. 565-573 ◽  
Author(s):  
C. A. CAMPBELL ◽  
W. NICHOLAICHUK ◽  
V. O. BIEDERBECK ◽  
H. UKRAINETZ ◽  
J. BOLE
Keyword(s):  
Soil Temperature ◽  
Air Temperature ◽  
Cropping Systems ◽  
Soil Surface ◽  
Growing Season ◽  
Empirical Method ◽  
Canadian Prairies ◽  
Cereal Production ◽  
Soil Temperatures ◽  
The Relationship

Agronomists often require quick, easy methods of estimating soil temperatures under cereal production, either to fill in missing experimental measurements or to help explain apparent discrepancies in results. Methods available in the literature allow such estimates to be made from meteorological measurements and soil physical characteristics, but these methods are often mathematically complex. In the present paper a simple empirical regression and correlation approach was used to relate soil temperatures under cereal and fallow cropping systems to air temperature, and also to soil temperature at corresponding depths under grass plots at Swift Current, Saskatchewan. Relationships for the top 22.5 cm of soil were developed for the growing season and also for the whole year. Relationships between soil and air temperature were good near the soil surface, but deteriorated with depth even though highly significant r2 values were obtained. The best relationships were obtained between soil temperatures under the cereal system and temperatures under grass (r2 > 0.8 for growing season and > 0.9 for whole year). The relationships between mean daily temperatures under cereals (y) and those under grass at corresponding depths (x) were generally represented by y = x. The best Swift Current relationships for the growing season were used successfully [Formula: see text] to predict data for different years at Swift Current and Scott, Saskatchewan and at Lethbridge, Alberta. The error in prediction at the 10-cm depth was, on the average, 1–3 °C and at the 20-cm depth, 0–4 °C. The relationship developed will be more accurate in drier regions such as the southern prairies.

scholarly journals Experimental studies on the transformation from firn to ice in the wet-snow zone of temperate glaciers

1997 ◽  
Vol 24 ◽  
pp. 181-185 ◽  
Author(s):  
Katsuhisa Kawashima ◽  
Tomomi Yamada
Keyword(s):  
Experimental Studies ◽  
Ice Formation ◽  
Compression Tests ◽  
Densification Rate ◽  
Overburden Pressure ◽  
Proportionality Constant ◽  
Wet Snow ◽  
Water Saturated ◽  
The Relationship ◽  
Good Agreement

The densification of water-saturated firn, which had formed just above the firn-ice transition in the wet-snow zone of temperate glaciers, was investigated by compression tests under pressures ranging from 0.036 to 0.173 MPa, with special reference to the relationship between densification rate, time and pressure. At each test, the logarithm of the densification rate was proportional to the logarithm of the time, and its proportionality constant increased exponentially with increasing pressure. The time necessary for ice formation in the firn aquifer was calculated using the empirical formula obtained from the tests. Consequently, the necessary time decreased exponentially as the pressure increased, which shows that the transformation from firn in ice can be completed within the period when the firn aquifer exists, if the overburden pressure acting on the water-saturated firn is above 0.12–0.14 MPa. This critical value of pressure was in good agreement with the overburden pressure obtained from depth–density curves of temperate glaciers. It was concluded that the depth of firn–ice transition was self-balanced by the overburden pressure to result in the concentration between 20 and 30 m.

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