Estimate Soil Heat Flux Research Articles

Estimating Soil Heat Flux in Jordan Based on ERA5 Parameters and NCEP/NCAR Energy Outputs: Definite Radiative Forcing of Climate Change Using PCA

Estimating Soil Heat Flux in Jordan Based on ERA5 Parameters and NCEP/NCAR Energy Outputs: Definite Radiative Forcing of Climate Change Using PCA

Estimating the components of apparent thermal conductivity of soils at various water contents and temperatures

Soil thermal conductivity is an important parameter for estimating soil heat flux and soil thermal regime. Knowledge on the components of apparent soil thermal conductivity (λ) across various water contents (θ) and temperatures is important to accurately understand soil heat transfer mechanisms. In this study, soil thermal conductivity was measured for sandy loam and silty clay soils at various temperatures and air pressures using a transient method. Four components of λ, namely, heat conduction, latent heat transfer by water vapor diffusion, sensible heat transfer by liquid water, and sensible heat transfer by water vapor diffusion were quantified. Results showed that in uniform soils, the magnitudes of sensible heat transfers by liquid water and water vapor were negligible during these transient measurements. The contribution of latent heat transfer through vapor diffusion to total heat transfer increased as temperature increased, and the peak value occurred at an intermediate water content. The water content at which the maximum vapor diffusion occurred varied with soil texture. In addition to the four calculated components, a significant residual contribution to λ caused by an unidentified vapor transfer mechanism was observed between 3.5°C and 81°C. For example, calculations indicated that approximately 66% of the sandy loam λ at θ=0.11 m3 m−3 was caused by an unidentified vapor transfer mechanism at 81°C. This extra contribution by vapor transfer could be explained either as enhanced vapor diffusion or by an advection mechanism. Further investigation is needed to clarify whether enhanced diffusion or advection is occurring in unsaturated soils.

Fluxo de calor no solo modelado a partir de dados de temperatura em dois níveis de profundidade em uma floresta tropical na Amazônia Ocidental

The global climate is dependent of ecological balance of forests, especially tropical. The heat flux in the soil is an important factor in studies of energy balance representing the main form of energy exchange between soil and atmosphere. The aim of the present work was to estimate soil heat flux using soil temperature measurements at two depth levels in a tropical forest in the Western Amazon, in order to obtain coherent data for both the use of the values and for the filling of failures in database. Had been used data on temperature and soil heat flux collected in a micrometeorological tower belonging to the towers network of the Large Scale Biosphere-Atmosphere Program in the Amazon, located in the Jaru Biological Reserve. The estimated data presented 94% agreement with the measured data, the two have similar behaviors that allow the use in filling of failures in a demonstrative way. However, there is a delay in the estimated values of the heat flux in the soil in relation to the measured one, which interferes in the result of the model, provoking more studies to improve it.

Estimation of surface energy fluxes in the Arctic tundra using the remote sensing thermal-based Two-Source Energy Balance model

Abstract. The Arctic has become generally a warmer place over the past decades leading to earlier snow melt, permafrost degradation and changing plant communities. Increases in precipitation and local evaporation in the Arctic, known as the acceleration components of the hydrologic cycle, coupled with land cover changes, have resulted in significant changes in the regional surface energy budget. Quantifying spatiotemporal trends in surface energy flux partitioning is key to forecasting ecological responses to changing climate conditions in the Arctic. An extensive local evaluation of the Two-Source Energy Balance model (TSEB) – a remote-sensing-based model using thermal infrared retrievals of land surface temperature – was performed using tower measurements collected over different tundra types in Alaska in all sky conditions over the full growing season from 2008 to 2012. Based on comparisons with flux tower observations, refinements in the original TSEB net radiation, soil heat flux and canopy transpiration parameterizations were identified for Arctic tundra. In particular, a revised method for estimating soil heat flux based on relationships with soil temperature was developed, resulting in significantly improved performance. These refinements result in mean turbulent flux errors generally less than 50 W m−2 at half-hourly time steps, similar to errors typically reported in surface energy balance modeling studies conducted in more temperate climatic regimes. The MODIS leaf area index (LAI) remote sensing product proved to be useful for estimating energy fluxes in Arctic tundra in the absence of field data on the local biomass amount. Model refinements found in this work at the local scale build toward a regional implementation of the TSEB model over Arctic tundra ecosystems, using thermal satellite remote sensing to assess response of surface fluxes to changing vegetation and climate conditions.

Improved reconstruction of soil thermal field using two-depth measurements of soil temperature

• An improved method was proposed to reconstruct soil thermal field. • A higher accuracy was achieved by the improved method. • Two-depth soil temperatures with optional air temperatures are the only input. The accurate estimation of soil thermal field is crucially important because soil temperature is a key parameter widely used in many related fields. This paper proposed an improved heat-conduction-equation (HCE) method to reconstruct soil thermal field using two-depth measurements of soil temperature. The revised HCE method employed a direct approach as well as an indirect approach to estimate both the daily average soil temperature (DST) and the instantaneous soil temperature (IST), during which the annual temperature cycle and the diurnal temperature cycle are combined. Two validation experiments (i.e., Test-1 and Test-2) were performed with soil temperature measurements at five stations chosen from the Soil Climate Analysis Network (SCAN). The results show that the revised HCE method improves the accuracy of modeling soil thermal field in comparison to its traditional form. The root mean square errors (RMSEs) of the ISTs estimated by the traditional HCE method range from 1.0 to 2.1 °C (2.4 to 4.8 °C) in Test-1 (Test-2); while the errors of the revised HCE method by the indirect approach are reduced to less than 1.0 °C in both Test-1 and Test-2; the errors by the direct approach are further reduced to less than 0.7 °C in both Test-1 and Test-2. The improved method has further potential to estimate soil heat flux, a variable that can be inferred using soil temperature gradients associated with soil apparent thermal conductivity .

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

Summary This paper proposes a mathematical method based on a one-dimensional diffusion equation to derive diurnal variation of surface soil heat flux using cloudless MODIS data for a sparse vegetation and bare soil. Diurnal variation of the surface temperature and near-surface real soil thermal inertia are both simulated from the MODIS data. The study was carried out for the Yingke oasis plains area and the Arou alpine meadow area, which are located in the midstream and upstream, respectively, of the Heihe River Basin. Statistical results showed that the proposed method performs well to estimate soil heat flux for both study areas. In the oasis plains case, the coefficient of determination (R2) was 0.958 and the index of agreement (d) was 0.989. In the alpine meadow case, the coefficient of determination (R2) was 0.972 and the index of agreement (d) was 0.993. Close agreement of the estimated surface soil heat flux with measured observations indicates that the method is promising. Future work will focus on scaling this mathematical method to create a diurnal surface soil heat flux map.

Linking Surface Temperature Based Approaches for Estimating Soil Heat Flux with Error Propagation

Soil heat flux is an inseparable component of the surface energy balance. Accurate estimation of regional soil heat flux is valuable to studies of meteorology and hydrology. Conventional measurement of using soil heat flux plates at the site scale is impractical to estimate large-scale flux. Other approaches generally require soil temperature to be measured in at least two soil layers, which is also difficult to implement at the regional scale. In the last decade, single-layer based approaches were developed to fulfill the regional requirement. This study used a simple but more general approach for estimating soil heat flux solely with surface temperature. The generalized approach can be conditionally linked to two existing single-layer based approaches but has fewer restrictions or assumptions. Error analysis revealed that measurement error in surface temperature would have limited effects on soil heat flux estimated from the new approach. Model simulations showed that soil heat flux estimated from the approach agreed with those simulated from the heat transfer equation. Furthermore, case examinations at two sites with contrasting climate regimes demonstrated that the generalized approach had better performance than the existing single-layer approaches. It achieved the highest correlation of determination and the lowest mean, standard deviation, and root mean squared error of the differences between the estimates and the field measures at either site. The generalized approach can estimate soil heat flux at a depth but it requires only surface temperature data as input, which is an advantage to remote sensing applications.

Soil Heat Flux Modeling Using Artificial Neural Networks and Multispectral Airborne Remote Sensing Imagery

The estimation of spatially distributed crop water use or evapotranspiration (ET) can be achieved using the energy balance for land surface algorithm and multispectral imagery obtained from remote sensing sensors mounted on air- or space-borne platforms. In the energy balance model, net radiation (Rn) is well estimated using remote sensing; however, the estimation of soil heat flux (G) has had mixed results. Therefore, there is the need to improve the model to estimate soil heat flux and thus improve the efficiency of the energy balance method based on remote sensing inputs. In this study, modeling of airborne remote sensing-based soil heat flux was performed using Artificial Neural Networks (ANN). Soil heat flux was modeled using selected measured data from soybean and corn crop covers in Central Iowa, U.S.A. where measured values were obtained with soil heat flux plate sensors. Results in the modeling of G indicated that the combination Rn with air temperature (Tair) and crop height (hc) better reproduced measured values when three independent variables were considered. The combination of Rn with leaf area index (LAI) from remote sensing, and Rn with surface aerodynamic resistance (rah) yielded relative larger overall correlation coefficient values when two independent variables were included using ANN. In addition, air temperature (Tair) may be a key variable in the modeling of G as suggested by the ANN application (r of 0.83). Therefore, it is suggested that Rn, LAI, rah and hc and potentially Tair be considered in future modeling studies of G.

Comparison and Analysis of Empirical Equations for Soil Heat Flux for Different Cropping Systems and Irrigation Methods

We evaluated the performance of four models for estimating soil heat flux density (G) in maize (Zea mays L.) and soybean (Glycine max L.) fields under different irrigation methods (center-pivot irrigated fields at Mead, Nebraska, and subsurface drip irrigated field at Clay Center, Nebraska) and rainfed conditions at Mead. The model estimates were compared against measurements made during growing seasons of 2003, 2004, and 2005 at Mead and during 2005, 2006, and 2007 at Clay Center. We observed a strong relationship between the G and net radiation (Rn) ratio (G/Rn) and the normalized difference vegetation index (NDVI). When a significant portion of the ground was bare soil, G/Rn ranged from 0.15 to 0.30 and decreased with increasing NDVI. In contrast to the NDVI progression, the G/Rn ratio decreased with crop growth and development. The G/Rn ratio for subsurface drip irrigated crops was smaller than for the center-pivot irrigated crops. The seasonal average G was 13.1%, 15.2%, 10.9%, and 12.8% of Rn for irrigated maize, rainfed maize, irrigated soybean, and rainfed soybean, respectively. Statistical analyses of the performance of the four models showed a wide range of variation in G estimation. The root mean square error (RMSE) of predictions ranged from 15 to 81.3 W m-2. Based on the wide range of RMSE, it is recommended that local calibration of the models should be carried out for remote estimation of soil heat flux.

Application of Harmonic Analysis to Estimate Soil Heat Flux Using Remotely Measured Surface Temperature

Soil heat flux is an important component of surface energy balance,and harmonic analysis can be used to estimate soil heat flux based on the surface temperature.However,it is necessary to know the daily change in surface temperature to estimate the soil heat flux through harmonic analysis.In this study,a simplified method of harmonic analysis for simulation of the daily change in surface temperature that uses satellite data obtained twice a day and the time when the daily maximum surface temperature occurs is proposed.Evaluation of the simulated results using field data from Monsoon'90 revealed that the precision of the model was high.Moreover,the harmonic analysis was simplified because of its complex calculation.Furthermore,the simulated soil heat flux generated using the simplified method was found to be quite similar to the observed heat flux,as well as those simulated using the original harmonic analysis;therefore,the simplified method is applicable.

Long-term estimation of soil heat flux by single layer soil temperature

Soil heat flux is one of the important components of surface energy balance. In this study, long-term estimation of soil heat flux from single layer soil temperature was carried out by the traditional sinusoidal analytical method and the half-order time derivative method of Wang and Bras [Wang and Bras (1999) J Hydrol 216:214-226]. In order to understand the characteristics of soil heat flux and to examine the performances of the two methods, a field experiment was conducted at a temperate and humid grassland in Cork, Ireland. Our results show that the soil heat flux had the same magnitude as the sensible heat flux at this grassland site. It was also demonstrated that the analytical method did not predict the soil heat flux well because the sinusoidal assumption for the temporal variation in soil heat flux was invalid. In contrast, good agreement was found between the soil heat flux measurements and predictions made by the half-order time derivative method. This success suggests that this method could be used to estimate soil heat flux from long-term remotely sensed surface temperature.

A temperature prediction-correction method for estimating surface soil heat flux from soil temperature and moisture data

Surface soil heat flux is a component of surface energy budget and its estimation is needed in land-atmosphere interaction studies. This paper develops a new simple method to estimate soil heat flux from soil temperature and moisture observations. It gives soil temperature profile with the thermal diffusion equation and, then, adjusts the temperature profile with differences between observed and computed soil temperatures. The soil flux is obtained through integrating the soil temperature profile. Compared with previous methods, the new method does not require accurate thermal conductivity. Case studies based on observations, synthetic data, and sensitivity analyses show that the new method is preferable and the results obtained with it are not sensitive to the availability of temperature data in the topsoil. In addition, we pointed out that the soil heat flux measured with a heat-plate can be quite erroneous in magnitude though its phase is accurate.

Use of remote sensing for evapotranspiration monitoring over land surfaces

Abstract Monitoring evapotranspiration (ET) at large scales is important for assessing climate and anthropogenic effects on natural and agricultural ecosystems. This paper describes techniques used in evaluating ET with remote sensing, which is the only technology that can efficiently and economically provide regional and global coverage. Some of the empirical/statistical techniques have been used operationally with satellite data for computing daily ET at regional scales. The more complex numerical simulation models require detailed input parameters that may limit their application to regions containing a large database of soils and vegetation properties. Current efforts are being directed towards simplifying the parameter requirements of these models. Essentially all energy balance models rely on an estimate of the available energy (net radiation less soil heat flux). Net radiation is not easily determined from space, although progress is being made. Simplified approaches for estimating soil heat flux appear promising for operational applications. In addition, most ET models utilize remote sensing data in the shortwave and thermal wavelengths to measure key boundary conditions. Differences between the radiometric surface temperature and aerodynamic temperature can be significant and progress in incorporating this effect is evident. Atmospheric effects on optical data are significant, and optical sensors cannot see through clouds. This has led some to use microwave observations as a surrogate for optical data to provide estimates of surface moisture and surface temperature; preliminary results are encouraging. The approaches that appear most promising use surface temperature and vegetation indices or a time rate of change in surface temperature coupled to an atmospheric boundary layer model. For many of these models, differences with ET observations can be as low as 20% from hourly to daily time scales, approaching the level of uncertainty in the measurement of ET and contradicting some recent pessimistic conclusions concerning the utility of remotely sensed radiometric surface temperature for determining the surface energy balance.

Errors Associated with the Combination Method for Estimating Soil Heat Flux

AbstractErrors are common to all methods of measuring soil heat flux. This study examines some of the errors that result when estimating the heat storage term (employed by the combination method) from measurements of the time rate of change of soil temperatures. Based on analytical models of the vertical profiles of soil temperature, my results indicate that errors of ±3 to 10% in the estimate of soil beat flux can result from following recommended procedures. For homogenous soils, these errors can be reduced by about 67% using two soil thermometers with unequal weighting to estimate the heat storage term. However, minimizing these errors for inhomogeneous soils may not be possible without detailed information on the vertical structure of the soil thermal properties.

Estimation of the soil heat flux/net radiation ratio from spectral data

Reliable spatial averages of surface energy balance components are difficult to obtain without an extensive hydrological measurement system. Our objective was to develop a method using remote sensing for estimating soil heat flux, one component of the surface energy balance, for a range of canopy conditions that will be applicable to regional surface energy balance studies. Net radiation ( Rn) and soil heat flux ( G) were measured during several days in fields of bare soil, alfalfa, and cotton at the Maricopa Agricultural Center, near Phoenix, AZ. Ground-based measurements of reflectance factors were also obtained with a multiband radiometer. Midday values of the ratio of soil heat flux and net radiation ( G/ Rn) were linearly related to the simple ratio and normalized difference vegetation indices. Relative to measurement errors, the estimates of G/ Rn for cotton were found to be practically insensitive to changes in the value of the vegetative indices caused by spectral data collected at significantly different solar zenith and azimuth angles. Thus, multispectral data may provide a means of computing a more accurate area-averaged soil heat flux for regional energy balance studies.

Estimation of soil heat flux from net radiation during the growth of alfalfa

Soil heat flux studies have indicated that the instantaneous daytime flux can be estimated as a fraction of the net radiation, the ratio ranging from 0.1 to 0.5, depending on the amount of vegetation present and on the time of day. Soil heat flux and net radiation were measured for an alfalfa crop over two regrowth cycles during the fall growing season. For both sparse alfalfa stubble and full vegetative canopy, the surface soil water content did not significantly affect the fraction of net radiation consumed as soil heat flux. The ratio of soil heat flux to net radiation around midday was found to be a linearly decreasing function of crop height only for heights up to 450 mm. As crop growth continued beyond this height, the ratio remained nearly constant at 0.1. The ratio data were also found to be well-fitted by a linearly decreasing function of a spectral vegetation index (near-IR to Red ratio) over both regrowth cycles. These results indicate that both crop height and spectral vegetation indices can be used to estimate soil heat flux from net radiation measurements.

Soil Heat Flux, Thermal Conductivity, and the Null‐alignment Method

AbstractThe null‐alignment method of estimating soil heat flux density(q) and thermal conductivity (λ) depends on calorimetry, and ignores convection of sensible heat by mass flow and processes involving latent heat. Study of the energy balance of drying bare soils indicates that the major errors of null‐point calorimetry are likely to arise from net evaporation in upper soil layers. A net evaporation rate of at least 1 mm/d probably occurred in the example used to introduce null‐alignment. This small evaporation rate changes the q profile so radically that null‐alignment may give λ‐values averaging about 52% of the correct ones. Diurnal variations of latent heat sink strengths, null‐points, and temperature gradients, combine to produce diurnal variation of the error in null‐aligned λ's, thereby explaining the reported diurnal variation of null‐aligned λ. Since errors tend to be large and negative in daytime, and small and positive at night, 24h avg are likely to be too small. Null‐alignment does not provide the precise measures of q and λ its exponents supposed, so that various null‐alignment‐based critiques of the Philip‐De Vries theory of heat and moisture transfer in soils, and of the De Vries model of λ, cannot be sustained. Of course there is much scope for improving both through incisive theory and precise experiment. All calorimetric methods of estimating q that ignore latent heat, not only null‐alignment, must involve serious errors in the presence of significant net evaporation in the soil.

Estimating the Soil Heat Flux from Observations of Soil Temperature Near the Surface

AbstractA method was described for estimating soil heat flux by measuring soil moisture content and soil temperature at two or three depths near the soil surface. The method utilizes an analytical expression of heat flux for a semi‐infinite homogeneous soil profile for which the surface temperature is described by a Fourier series. For relatively homogeneous soil, the estimates of soil heat flux, based on observation of temperature at two depths, compared well with values of heat flux determined with the temperature integral method. Estimates were best when one of the measurement depths was very near the surface (≤ 1 cm) and the other between the 10‐ and 20‐cm depths. When soil profiles were nonhomogeneous it was found that three rather than two depths of temperature observation should be considered. Although the analytical solution for estimating the heat flux strictly does not apply to nonhomogeneous soils, heat flux values obtained with the proposed method compared favorably with those computed with the temperature integral method.