scholarly journals An Empirical Method of Estimating Soil Thermal Inertia

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Jing Tian ◽  
Hongbo Su ◽  
Honglin He ◽  
Xiaomin Sun
Keyword(s):  
Heat Flux ◽  
Surface Temperature ◽  
Empirical Relationship ◽  
Thermal Inertia ◽  
Soil Surface ◽  
Bare Soil ◽  
Soil Heat Flux ◽  
Empirical Method ◽  
The Difference ◽  
Fourier Series Analysis

A method of estimating soil thermal inertia (STI), which uses midday soil heat flux (Gm) and diurnal surface temperature amplitude as the inputs, is presented in the paper.Gmis achieved from an empirical relationship between net radiation (Rn) and soil heat flux (G). To validate the STI method, a method proposed by Verhoef, which requires STI and a Fourier series analysis on surface temperature, is used to estimate diurnalG. By comparing diurnalGestimates and diurnalGmeasurements, the STI method is evaluated indirectly. The results show that the diurnal curve ofGestimates can coincide with that ofGmeasurements for bare soil, with the correlation coefficient (R2) of 0.64, bias of 10.1 W·m−2, and root mean squared errors (RMSE) of 40.9 W·m−2. For the vegetated surface,R2is 0.56, bias is −11.9 W·m−2, and RMSE is 49.2 W·m−2. The large uncertainty in the estimation ofGmresulting from the wider variation of the empirical relationship between Rn andGand the difference between mixed surface temperature and soil surface temperature may be the two primary factors for the larger deviation of the diurnal shape and the magnitude betweenGestimates andGmeasurements for the vegetated surface.

Remote estimation of thermal inertia and soil heat flux for bare soil

2004 ◽  
Vol 123 (3-4) ◽  
pp. 221-236 ◽  
Author(s):  
Anne Verhoef
Keyword(s):  
Heat Flux ◽  
Thermal Inertia ◽  
Bare Soil ◽  
Soil Heat Flux ◽  
Remote Estimation

scholarly journals Applying Infrared Thermography to Soil Surface Temperature Monitoring: Case Study of a High-Resolution 48 h Survey in a Vineyard (Anadia, Portugal)

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2444
Author(s):  
William Frodella ◽  
Giacomo Lazzeri ◽  
Sandro Moretti ◽  
Jacob Keizer ◽  
Frank G. A. Verheijen
Keyword(s):  
Surface Temperature ◽  
Soil Temperature ◽  
Infrared Thermography ◽  
Thermal Inertia ◽  
Soil Surface ◽  
Bare Soil ◽  
Control Treatment ◽  
Soil Surface Temperature ◽  
Monitoring Protocols

The soil surface albedo decreases with an increasing biochar application rate as a power decay function, but the net impact of biochar application on soil temperature dynamics remains to be clarified. The objective of this study was to assess the potential of infrared thermography (IRT) sensing by monitoring soil surface temperature (SST) with a high spatiotemporal and thermal resolution in a scalable agricultural application. We monitored soil surface temperature (SST) variations over a 48 h period for three treatments in a vineyard: bare soil (plot S), 100% biochar cover (plot B), and biochar-amended topsoil (plot SB). The SST of all plots was monitored at 30 min intervals with a tripod-mounted IR thermal camera. The soil temperature at 10 cm depth in the S and SB plots was monitored continuously with a 5 min resolution probe. Plot B had greater daily SST variations, reached a higher daily temperature peak relative to the other plots, and showed a faster rate of T increase during the day. However, on both days, the SST of plot B dipped below that of the control treatment (plot S) and biochar-amended soil (plot SB) from about 18:00 onward and throughout the night. The diurnal patterns/variations in the IRT-measured SSTs were closely related to those in the soil temperature at a 10 cm depth, confirming that biochar-amended soils showed lower thermal inertia than the unamended soil. The experiment provided interesting insights into SST variations at a local scale. The case study may be further developed using fully automated SST monitoring protocols at a larger scale for a range of environmental and agricultural applications.

A method to estimate diurnal surface soil heat flux from MODIS data for a sparse vegetation and bare soil

2014 ◽  
Vol 511 ◽  
pp. 139-150 ◽  
Author(s):  
Weiwei Zhu ◽  
Bingfang Wu ◽  
Nana Yan ◽  
Xueliang Feng ◽  
Qiang Xing
Keyword(s):  
Heat Flux ◽  
Surface Soil ◽  
Bare Soil ◽  
Soil Heat Flux ◽  
Modis Data ◽  
Sparse Vegetation

Hourly estimation of soil heat flux density at the soil surface with three models and two field methods

2012 ◽  
Vol 112 (1-2) ◽  
pp. 45-59 ◽  
Author(s):  
P. Venegas ◽  
A. Grandón ◽  
J. Jara ◽  
J. Paredes
Keyword(s):  
Heat Flux ◽  
Flux Density ◽  
Heat Flux Density ◽  
Soil Surface ◽  
Soil Heat Flux ◽  
Field Methods

scholarly journals Soil-Surface Straw Influences Micrometeorological Conditions Affecting Canola Mortality During Nighttime Frosts

2020 ◽  
Vol 12 (11) ◽  
pp. 246
Author(s):  
Samuel Kovaleski ◽  
Arno B. Heldwein ◽  
Genei A. Dalmago ◽  
Jorge A. de Gouvêa ◽  
Gilberto R. da Cunha ◽  
...  
Keyword(s):  
Heat Flux ◽  
Ground Surface ◽  
Soil Surface ◽  
Soil Heat Flux ◽  
Growth Cycle ◽  
The Other ◽  
Net Radiation ◽  
Plant Mortality ◽  
Seedling Mortality ◽  
Micrometeorological Conditions

Our objective was to measure alterations in the micrometeorological conditions surrounding canola seedlings during frost periods, and to quantify seedling mortality as a function of straw distribution on the ground surface. The data was acquired from 15 frosts in 2014. We used four treatments, comprising ground surface without straw (SWS), ground surface entirely straw-covered (SEC), sowing line without straw (SLW), and soil with preexisting surface straw (SES), over three experiments. Net radiation (NR), soil heat flux (G), air (Ta), leaf (Lf), rosette (Tr), and surface temperature (Ts), and plant mortality were evaluated. NR was higher in the SEC treatment and lower in the SLW treatment, whereas G was higher on straw-covered ground; Ts and Ta were lower in the SEC than in the other treatments during the most intense frosts. On 06/19, Tr in the SEC and SLW treatments was -0.66 °C and 0.42 °C, respectively; on 08/14, Lf was -3.62 °C and -2.88 °C in the SEC and SLW treatments, respectively. Plant mortality due to the frost on 06/19 was 30% in the SEC treatment, but 0% in the SLW treatment; the frost of 08/14 caused 33.8% mortality in the SEC treatment and 1.25% in the SLW treatment. This therefore showed that removing straw from the sowing line improved the microclimate around the plants, thus reducing canola mortality at the beginning of the growth cycle, which is when frost events most frequently occur.

scholarly journals Temporal variations of evapotranspiration: reconstruction using instantaneous satellite measurements in the thermal infra red domain

2012 ◽  
Vol 9 (2) ◽  
pp. 1699-1740 ◽  
Author(s):  
E. Delogu ◽  
G. Boulet ◽  
A. Olioso ◽  
B. Coudert ◽  
J. Chirouze ◽  
...  
Keyword(s):  
Heat Flux ◽  
Surface Temperature ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Interpolation Method ◽  
Empirical Relationship ◽  
Surface Energy Budget ◽  
Evaporative Fraction ◽  
Clear Sky ◽  
Extrapolation Algorithm

Abstract. Evapotranspiration estimates can be derived from remote sensing data and ancillary, mostly meterorological, information. For this purpose, two types of methods are classically used: the first ones estimate a potential evapotranspiration rate from vegetation indices, and adjust this rate according to water availability derived from either a surface temperature index or a first guess obtained from a rough estimate of the water budget, while the second family of methods rely on the link between the surface temperature and the latent heat flux through the surface energy budget. The latter provide an instantaneous estimate at the time of satellite overpass. In order to compute daily evapotranspiration, one needs an extrapolation algorithm. Since no image is acquired during cloudy conditions, these methods can only be applied during clear sky days. In order to derive seasonal evapotranspiration, one needs an interpolation method. Two combined interpolation/extrapolation methods based on the self preservation of evaporative fraction and the stress factor are compared to reconstruct seasonal evapotranspiration from instantaneous measurements acquired in clear sky conditions. Those measurements are taken from instantaneous latent heat flux from 11 datasets in Southern France and Morocco. Results show that both methods have comparable performances with a clear advantage for the evaporative fraction for datasets with several water stress events. Both interpolation algorithms tend to underestimate evapotranspiration due to the energy limiting conditions that prevail during cloudy days. Taking into account the diurnal variations of the evaporative fraction according to an empirical relationship derived from a previous study improved the performance of the extrapolation algorithm and therefore the retrieval of the seasonal evapotranspiration for all but one datasets.

scholarly journals Ramdas layer and thermal wave during winter period

MAUSAM ◽  
2022 ◽  
Vol 52 (4) ◽  
pp. 697-702
Author(s):  
S. ABRAHAM THAMBI RAJA ◽  
G. RENUKA ◽  
K. RETNAKUMARI
Keyword(s):  
Mathematical Model ◽  
Heat Flux ◽  
Energy Balance ◽  
Thermal Wave ◽  
Soil Surface ◽  
Soil Heat Flux ◽  
Rate Of Change ◽  
Winter Period ◽  
Maximum Height ◽  
Lower Height

Earlier works on Ramdas Layer were about its certainty, its existence, energy balance on the layer and a matching mathematical model. We, first identified it in Thiruvananthapuram, Kerala, for eight days during a fortnight study on soil heat flux. A lifted minimum in temperature could have implications in agriculture and horticulture and so with a view to finding out a range of height through which Ramdas layer occurs, Ramdas-max, Ramdas-min are identified. On 24 January 1994, Ramdas layer occurred at a maximum height of 0.8m from the surface and the day is labeled as Ramdas-max. On 1 February 1994, it occurred at a lower height of 0.4m from the surface and the day is labeled as Ramdas-min.   The thermal wave at the ground and at 0.05m depth, the range of thermal wave, its relationship with Ramdas layer, the temperature profile, the rate of change of heat in that layer with that at the surface and the subsoil heat flux at the sub-soil surface stratum(surface-0.05m) during R~mdas-max and Ramdas-min are duly compared and discussed.

scholarly journals Reconstruction of temporal variations of evapotranspiration using instantaneous estimates at the time of satellite overpass

2012 ◽  
Vol 16 (8) ◽  
pp. 2995-3010 ◽  
Author(s):  
E. Delogu ◽  
G. Boulet ◽  
A. Olioso ◽  
B. Coudert ◽  
J. Chirouze ◽  
...  
Keyword(s):  
Heat Flux ◽  
Surface Temperature ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Interpolation Method ◽  
Empirical Relationship ◽  
Surface Energy Budget ◽  
Evaporative Fraction ◽  
Clear Sky ◽  
Extrapolation Algorithm

Abstract. Evapotranspiration estimates can be derived from remote sensing data and ancillary, mostly meterorological, information. For this purpose, two types of methods are classically used: the first type estimates a potential evapotranspiration rate from vegetation indices, and adjusts this rate according to water availability derived from either a surface temperature index or a first guess obtained from a rough estimate of the water budget, while the second family of methods relies on the link between the surface temperature and the latent heat flux through the surface energy budget. The latter provides an instantaneous estimate at the time of satellite overpass. In order to compute daily evapotranspiration, one needs an extrapolation algorithm. Since no image is acquired during cloudy conditions, these methods can only be applied during clear sky days. In order to derive seasonal evapotranspiration, one needs an interpolation method. Two combined interpolation/extrapolation methods based on the self preservation of evaporative fraction and the stress factor are compared to reconstruct seasonal evapotranspiration from instantaneous measurements acquired in clear sky conditions. Those measurements are taken from instantaneous latent heat flux from 11 datasets in Southern France and Morocco. Results show that both methods have comparable performances with a clear advantage for the evaporative fraction for datasets with several water stress events. Both interpolation algorithms tend to underestimate evapotranspiration due to the energy limiting conditions that prevail during cloudy days. Taking into account the diurnal variations of the evaporative fraction according to an empirical relationship derived from a previous study improved the performance of the extrapolation algorithm and therefore the retrieval of the seasonal evapotranspiration for all but one datasets.

Sign in / Sign up

Export Citation Format

Share Document