Critical analysis of thermal inertia approaches for surface soil water content retrieval

Abstract

The “thermal inertia” method to retrieve surface soil water content maps on bare or sparsely-vegetated soils is analysed. The study area is a small experimental watershed, where optical and thermal images (in day and night time) and in situ data were simultaneously acquired. The sensitivity of thermal inertia to the phase difference between incoming radiation and soil temperature is demonstrated. Thus, to obtain an accurate value of the phase difference, the temporal distance between thermographs using a three-temperature approach is evaluated. We highlight when a cosine correction of the temperature needs to be applied, depending on whether the thermal inertia formulation includes two generic acquisition times, or not. Finally, the deviation in soil water content retrieval is quantifies for given values of each parameter by performing a sensitivity analysis on the basic parameters of the thermal inertia method that are usually affected by calibration errors.

Citation Maltese, A., Bates, P.D., Capodici, F., Cannarozzo, M., Ciraolo, G., and La Loggia, G., 2013. Critical analysis of thermal inertia approaches for surface soil water content retrieval. Hydrological Sciences Journal, 58 (5), 1144–1161.

Editor D. Koutsoyiannis; Associate editor D. Hughes     

Analysis of surface roughness in relation to soil loss and runoff at high rainfall intensities

The decay of roughness is an important factor governing surface processes such as infiltration and soil erosion. Thus the decay of surface roughness under different surface conditions was investigated and related to quantitative amounts of soil loss, runoff and sediment concentration in a laboratory experiment. Rainfall with an intensity of 128 mm/h was applied to a bare or mulched surfaces of a sandy loam soil with known surface roughness at specified time intervals. The decay of roughness as expressed by roughness ratio, in this experiment, was better predicted when related to an exponential function of the square root of cumulative kinetic energy of rainfall rather than with the cumulative rainfall. The roughness decay equations in literature did not predict breakdown under mulched surfaces accurately. Thus the exponent parameters of the roughness decay equations were adjusted to reflect the reduced decay occurring under mulched surfaces. In a bare soil, regression equations expressing the dependent variables as a function of initial roughness index were significant, but with low coefficients of determination, being 0·39 for soil loss, 0·12 for runoff and 0·36 for sediment concentration. In addition to initial roughness index, cumulative kinetic energy of rainfall was further included in the regressions. This led to an increase in coefficients of determination, which was 0·81 for soil loss, 0·74 for runoff and 0·49 for sediment concentration. The coefficients of determination (0·87 for soil loss, 0·85 for runoff and 0·51 for sediment concentration) were further increased when the final roughness index was included in addition to initial roughness index and cumulative kinetic energy in the regressions. This work shows that soil loss and runoff could be predicted from bare soil surface provided the initial roughness and the energy of rainfall is known. However, field verifications of these relationships are needed under different tillage tools and under natural rainfall. Copyright © 2002 John Wiley & Sons, Ltd.     

Monitoring soil surface roughness under growing winter wheat with low-altitude UAV sensing: Potential and limitations

Soil surface roughness (SSR) is an important factor in controlling sediment and runoff generation, influencing directly a wide spectrum of erosion parameters. SSR is highly variable in time and space under natural conditions, and characterizing SSR to improve the parameterization of hydrological and erosion models has proved challenging. Our study uses recent technological and algorithmic developments in capturing and processing close aerial sensing data to evaluate how high-resolution imagery can assist the temporally and spatially explicit monitoring of SSR. We evaluated the evolution of SSR under natural rainfall and growing vegetation conditions on two arable fields in Denmark. Unmanned aerial vehicle (UAV) photogrammetry was used to monitor small field plots over 7 months after seeding of winter wheat following conventional and reduced tillage treatments. Field campaigns were conducted at least once a month from October until April, resulting in nine time steps of data acquisition. Structure from motion photogrammetry was used to derive high-resolution point clouds with an average ground sampling distance of 2.7 mm and a mean ground control point accuracy of 1.8 mm. A comprehensive workflow was developed to process the point clouds, including the detection of vegetation and the removal of vegetation-induced point cloud noise. Rasterized and filtered point clouds were then used to determine SSR geostatistically as the standard deviation of height, applying different kernel sizes and using semivariograms. The results showed an influence of kernel size on roughness, with a value range of 0.2–1 cm of average height deviation during the monitoring period. Semivariograms showed a measurable decrease in sill variance and an increase in range over time. This research demonstrated multiple challenges to measuring SSR with UAV under natural conditions with increasing vegetation cover. The proposed workflow represents a step forward in tackling those challenges and provides a knowledge base for future research. © 2020 John Wiley & Sons, Ltd.     

Mapping the spatial variation of soil water content at the field scale with different ground penetrating radar techniques

Two ground penetrating radar (GPR) techniques were used to estimate the shallow soil water content at the field scale. The first technique is based on the ground wave velocity measured with a bistatic impulse radar connected to 450 MHz ground-coupled antennas. The second technique is based on inverse modeling of an off-ground monostatic TEM horn antenna in the 0.8–1.6 GHz frequency range. Data were collected on a 8 by 9 m partially irrigated intensive research plot and along four 148.5 m transects. Time domain reflectometry, capacitance sensors, and volumetric soil samples were used as reference measurements. The aim of the study was to test the applicability of the ground wave method and the off-ground inverse modeling approach at the field scale for a soil with a silt loam texture. The results for the ground wave technique were difficult to interpret due to the strong attenuation of the GPR signal, which is related to the silt loam texture at the test site. The root mean square error of the ground wave technique was 0.076 m³ m⁻³ when compared to the TDR measurements and 0.102 m³ m⁻³ when compared with the volumetric soil samples. The off-ground monostatic GPR measured less within-field soil water content variability than the reference measurements, resulting in a root mean square error of 0.053 m³ m⁻³ when compared with the TDR measurements and an error of 0.051 m³ m⁻³ when compared with the volumetric soil samples. The variability between the two GPR measurements was even larger with a RSME of 0.115 m³ m⁻³. In summary, both GPR methods did not provide adequate spatial information on soil water content variation at the field scale. The main reason for the deviating results of the ground wave method was the poor data quality due to high silt and clay content at the test site. Additional reasons were shallow reflections and the dry upper soil layer that cannot be detected by the ground wave method. In the case of off-ground GPR, the high sensitivity to the dry surface layer is the most likely reason for the observed deviations. The off-ground GPR results might be improved by using a different antenna that allows data acquisition in a lower frequency range.     

Multi‐scale assimilation of root zone soil water predictions

When hydrology model parameters are determined, a traditional data assimilation method (such as Kalman filter) and a hydrology model can estimate the root zone soil water with uncertain state variables (such as initial soil water content). The simulated result can be quite good. However, when a key soil hydraulic property, such as the saturated hydraulic conductivity, is overestimated or underestimated, the traditional soil water assimilation process will produce a persistent bias in its predictions. In this paper, we present and demonstrate a new multi‐scale assimilation method by combining the direct insertion assimilation method, particle swarm optimisation (PSO) algorithm and Richards equation. We study the possibility of estimating root zone soil water with a multi‐scale assimilation method by using observed in situ data from the Wudaogou experiment station, Huaihe River Basin, China. The results indicate there is a persistent bias between simulated and observed values when the direct insertion assimilation surface soil water content is used to estimate root zone soil water contents. Using a multi‐scale assimilation method (PSO algorithm and direct insertion assimilation) and an assumed bottom boundary condition, the results show some obvious improvement, but the root mean square error is still relatively large. When the bottom boundary condition is similar to the actual situation, the multi‐scale assimilation method can well represent the root zone soil water content. The results indicate that the method is useful in estimating root zone soil water when available soil water data are limited to the surface layer and the initial soil water content even when the soil hydraulic conductivities are uncertain. Copyright © 2011 John Wiley & Sons, Ltd.     

Using a H∞ filter assimilation procedure to estimate root zone soil water content

Root zone soil water content impacts plant water availability, land energy and water balances. Because of unknown hydrological model error, observation errors and the statistical characteristics of the errors, the widely used Kalman filter (KF) and its extensions are challenged to retrieve the root zone soil water content using the surface soil water content. If the soil hydraulic parameters are poorly estimated, the KF and its extensions fail to accurately estimate the root zone soil water. The H‐infinity filter (HF) represents a robust version of the KF. The HF is widely used in data assimilation and is superior to the KF, especially when the performance of the model is not well understood. The objective of this study is to study the impact of uncertain soil hydraulic parameters, initial soil moisture content and observation period on the ability of HF assimilation to predict in situ soil water content. In this article, we study seven cases. The results show that the soil hydraulic parameters hold a critical role in the course of assimilation. When the soil hydraulic parameters are poorly estimated, an accurate estimation of root soil water content cannot be retrieved by the HF assimilation approach. When the estimated soil hydraulic parameters are similar to actual values, the soil water content at various depths can be accurately retrieved by the HF assimilation. The HF assimilation is not very sensitive to the initial soil water content, and the impact of the initial soil water content on the assimilation scheme can be eliminated after about 5–7 days. The observation interval is important for soil water profile distribution retrieval with the HF, and the shorter the observation interval, the shorter the time required to achieve actual soil water content. However, the retrieval results are not very accurate at a depth of 100 cm. Also it is complex to determine the weighting coefficient and the error attenuation parameter in the HF assimilation. In this article, the trial‐and‐error method was used to determine the weighting coefficient and the error attenuation parameter. After the first establishment of limited range of the parameters, ‘the best parameter set’ was selected from the range of values. For the soil conditions investigated, the HF assimilation results are better than the open‐loop results. Copyright © 2010 John Wiley & Sons, Ltd.     

TDR measurement of stem and soil water content in two Mediterranean oak species

Abstract

Since 1990s, time domain reflectometry (TDR) has been applied to estimate the stem water content of living trees. Here, new calibration equations relating the apparent dielectric constant (K_a ) to the volumetric water content (θ) were developed for two Mediterranean oak species. Our calibration equations differ from those previously calculated for other species, suggesting that stem water contents could be monitored more accurately using species-specific curves. The stem water content in the trees of these species and the surrounding soil were monitored with TDR to examine the feasibility of this technology for recording changes in trunk water storage. The average stem water contents of the oaks reflect the soil water contents, and the temporal differences observed (17%) point to the importance of trunk water for coping with soil water deficit. Although it would be very useful to obtain a single function to estimate the stem water content of trees, it remains necessary to obtain the results in more species.     

The retrieval of two-dimensional distribution of the earth''''s surface aerodynamic roughness using SAR image and TM thermal infrared image

The research for the land surface fluxes has madea quiet great progress for its breakthroughs in the fieldof regional or global interactions between land surfaceand atmosphere. However, many remote sensing mod-els for estimating the land surface fluxes need the pa-rameters of surface momentum, heat, resistance ofwater vapor at a referenced height, which are the func-tion of aerodynamic surface roughness zad. It hasbeen validated that the retrieval of the land surfacefluxes is very sensitive to…     

Evaluation of Terrestrial Laser Scanner and Structure from Motion photogrammetry techniques for quantifying soil surface roughness parameters over agricultural soils

The surface roughness of agricultural soils is mainly related to the type of tillage performed, typically consisting of oriented and random components. Traditionally, soil surface roughness (SSR) characterization has been difficult due to its high spatial variability and the sensitivity of roughness parameters to the characteristics of the instruments, including its measurement scale. Recent advances in surveying have greatly improved the spatial resolution, extent, and availability of surface elevation datasets. However, it is still unknown how new roughness measurements relates with the conventional roughness measurements such as 2D profiles acquired by laser profilometers. The objective of this study was to evaluate the suitability of Terrestrial Laser Scanner (TLS) and Structure from Motion (SfM) photogrammetry techniques for quantifying SSR over different agricultural soils. With this aim, an experiment was carried out in three plots (5 × 5 m) representing different roughness conditions, where TLS and SfM photogrammetry measurements were co-registered with 2D profiles obtained using a laser profilometer. Differences between new and conventional roughness measurement techniques were evaluated visually and quantitatively using regression analysis and comparing the values of six different roughness parameters. TLS and SfM photogrammetry measurements were further compared by evaluating multi-directional roughness parameters and analyzing corresponding Digital Elevation Models. The results obtained demonstrate the ability of both TLS and SfM photogrammetry techniques to measure 3D SSR over agricultural soils. However, profiles obtained with both techniques (especially SfM photogrammetry) showed a loss of high-frequency elevation information that affected the values of some parameters (e.g. initial slope of the autocorrelation function, peak frequency and tortuosity). Nevertheless, both TLS and SfM photogrammetry provide a massive amount of 3D information that enables a detailed analysis of surface roughness, which is relevant for multiple applications, such as those focused in hydrological and soil erosion processes and microwave scattering. © 2019 John Wiley & Sons, Ltd.     

Experimental study on the relation between the water content of surface soil and theacoustic wave

Introduction Earthquake is not an isolated event. The focal region is not a closed system either. It is able to exchange energy or material with the medium outside this region. These kinds of exchange may cause various physical and chemical effects, so it is possible to get precursory signals by using space remote sensing technology. Many scholars (QIANG, et al, 1990; GENG, et al, 1992; XU, et al, 1995) have carried out some preliminary researches and experiments on the mechanism of therm…     

Synergistic effect of vegetation and air temperature changes on soil water content in alpine frost meadow soil in the permafrost region of Qinghai‐Tibet

Seasonal changes over 2 years (2004–2006) in soil moisture content (θ_v) of frozen alpine frost meadow soils of the Qinghai‐Tibet plateau permafrost region under three different levels of vegetation cover were investigated. Vegetation cover and air temperature changes had significant effects (synergistic effect) on θ_v and its distribution in the soil profile. During periods of soil freezing or thawing, the less the vegetation cover, the quicker the temperature drop or rise of soil water, and the shorter the duration of the soil water freeze–thaw response in the active soil layer. Under 30% and 65% vegetation cover the amplitude of variation in θ_v during the freezing period was 20–26% greater than that under 93% cover, while during the thawing period, it was 1·5‐ to 40·5‐fold greater. The freezing temperature of the surface soil layer, ^fT_s, was 1·6 °C lower under 30% vegetation cover than under 93% vegetation cover. Changes in vegetation cover of the alpine frost meadow affected θ_v and its distribution, as well as the relationship between θ_v and soil temperature (T_s). As vegetation cover decreased, soil water circulation in the active layer increased, and the response to temperature of the water distribution across the soil profile was heightened. The quantity of transitional soil phase water at different depths significantly increased as vegetation cover decreased. The influence of vegetation cover and soil temperature distribution led to a relatively dry soil layer in the middle of the profile (0·70–0·80 m) under high vegetation cover. Alpine meadow θ_v and its pattern of distribution in the permafrost region were the result of the synergistic effect of air temperature and vegetation cover. Copyright © 2007 John Wiley & Sons, Ltd.     

探地雷达测定土壤含水量的研究进展

结合国内外关于探地雷达测定土壤含水量的最新研究成果,阐述了探地雷达测定土壤含水量的基本原理和计算方法,总结和评价了土壤含水量与土壤介电常数的不同计算模型,针对在实际应用中存在的不足,提出了相关改进措施,并展望发展方向.     

Long-term analysis of measured and simulated evapotranspiration and soil water content

In our study, we analysed a period from 2003 to 2012 with micrometeorological data measured at a boundary-layer field site operated by the Lindenberg Meteorological Observatory – Richard-Aßmann-Observatory of the German Meteorological Service (DWD). Amongst others, these data consist of real evapotranspiration (ETr) rates measured by eddy covariance and soil water contents determined by time domain reflectometry. Measured ETr and soil water contents were compared with those simulated by a simple soil–vegetation–atmosphere transfer (SVAT) scheme consisting of the FAO56 Penman-Monteith equation and the soil water flux model Hydrus-1D. We applied this SVAT scheme using uncompensatory and compensatory root water uptake (RWU). Soil water contents and ETr rates calculated using uncompensatory RWU showed an acceptable fit to the measured ones. In comparison, the use of compensatory RWU resulted in lower model performance due to higher deviations between measured and simulated soil moisture values and ETr rates during dry summer periods.     

Spatio-temporal variability of surface soil water content and its influencing factors in a desert area,China

Abstract

Knowledge of the variability of soil water content (SWC) in space and time plays a key role in hydrological and climatic modelling. However, limited attention has been given to arid regions. The focus of this study was to investigate the spatio-temporal variability of surface soil (0–6 cm) water content and to identify its controlling factors in a region of the Gobi Desert (40 km²). The standard deviation of SWC decreased logarithmically as mean water content decreased, and the coefficient of variation of SWC exhibited a convex upward pattern. The spatial variability of SWC also increased with the size of the investigated area. The spatial dependence of SWC changed over time, with stronger patterns of spatial organization in drier and wetter conditions of soil wetness and stochastic patterns in moderate soil water conditions. The dominant factors regulating the variability of SWC changed from combinations of soil and topographical properties (bulk density, clay content and relative elevation) in wet conditions to combinations of soil and vegetation properties (bulk density, clay content and shrub coverage) in dry conditions. This study has important implications for the assessment of soil quality and the sustainability of land management in arid regions.     

Use of upscaled elevation and surface roughness data in two-dimensional surface water models

In this paper, we present an approach that uses a combination of cell-block- and cell-face-averaging of high-resolution cell elevation and roughness data to upscale hydraulic parameters and accurately simulate surface water flow in relatively low-resolution numerical models. The method developed allows channelized features that preferentially connect large-scale grid cells at cell interfaces to be represented in models where these features are significantly smaller than the selected grid size. The developed upscaling approach has been implemented in a two-dimensional finite difference model that solves a diffusive wave approximation of the depth-integrated shallow surface water equations using preconditioned Newton-Krylov methods. Computational results are presented to show the effectiveness of the mixed cell-block and cell-face averaging upscaling approach in maintaining model accuracy, reducing model run-times, and how decreased grid resolution affects errors. Application examples demonstrate that sub-grid roughness coefficient variations have a larger effect on simulated error than sub-grid elevation variations.     

The role of fire on soil mounds and surface roughness in the Mojave Desert

A fundamental question in arid land management centers on understanding the long‐term effects of fire on desert ecosystems. To assess the effects of fire on surface topography, soil roughness, and vegetation, we used terrestrial (ground‐based) LiDAR to quantify the differences between burned and unburned surfaces by creating a series of high‐resolution vegetation structure and bare‐earth surface models for six sample plots in the Grand Canyon‐Parashant National Monument, Arizona. We find that 11 years following prescribed burns, mound volumes, plant heights, and soil‐surface roughness were significantly lower on burned relative to unburned plots. Results also suggest a linkage between vegetation and soil mounds, either through accretion or erosion mechanisms such as wind and/or water erosion. The biogeomorphic implications of fire‐induced changes are significant. Reduced plant cover and altered soil surfaces from fire likely influence seed residence times, inhibit seed germination and plant establishment, and affect other ecohydrological processes. Published in 2012. This article is a US Government work and is in the public domain in the USA.     

Spatial variability of soil water content in the covered catchment at Gårdsjön,Sweden

The spatial variability of soil water content was investigated for a 6300 m² covered catchment on the Swedish west coast. The catchment podzol soil is developed in a sandy—silty till with a mean depth of 43 cm and the dominant vegetation is Norway spruce. The acid precipitation is removed by a plastic roof and replaced with lake water irrigated under the tree canopies. On two occasions, in April and May 1993, TDR measurements were made at 57–73 points in the catchment using 15 and 30 cm long vertically installed probes. The water content pattern at the two dates, which occurred during a relatively dry period, were similar. The range of water content was large, from 5 to 60%. In May 1993 measurements also were made in areas of 10 × 10 m, 1 × 1 m and 0·2 × 0·2 m. The range and standard deviation for the 10 × 10 m area, which apart from a small-scale variability in soil hydraulic properties and fine root distribution also had a heterogeneous micro- and macro-topography, was similar to the range and standard deviation for the catchment. The 1 × 1 m and 0·2 × 0·2 m areas had considerably lower variability. Semi-variogram models for the water content had a range of influence of about 20 m. If data were paired in the east-–west direction the semi-variance reflected the topography of the central valley and had a maximum for data pairs with internal distances of 20–40 m. The correlation between soil water content and topographic index, especially when averaged for the eight topographically homogeneous subareas, indicated the macro-topography as the cause of a large part of the water content variability.     

Temporal stability of soil water content as affected by climate and soil hydraulic properties: a simulation study

Temporal stability of soil water content (TS SWC) is an often‐observed phenomenon, which characterization finds multiple applications. Climate and variability in soil properties are usually mentioned as factors of TS SWC, but their effects are far from clear. The objective of this work was to use SWC modeling to evaluate the effects of climate and soil hydraulic properties on the TS of soil water at different measurement schedules. We selected four representative climates found in USA and simulated the multiyear SWC dynamics for sandy loam, loam, and silty clay loam soils, all having the lognormal spatial distribution of the saturated hydraulic conductivity. The CLIMGEN and the HYDRUS6 codes were used to generate weather patterns and to simulate SWC, respectively. Four different methods were applied to select the representative location (RL). The low probability of having the same variability of mean relative differences of soil water under different climates was found in most of the cases. The probability that the variance of mean relative differences depended on sampling frequency was generally higher than 91% for the three soils. The interannual difference in mean relative differences variation from short and intensive summer campaigns was highly probable for all climates and soils. The RLs changed as climate and measurement scheduling changed, and they were less pronounced for coarse‐textured soils. The RL selection methods based solely on bias provided more consistency as compared with other methods. The TS appears to be the result of the interplay between climate, soil properties, and survey protocols. One implication of this factor interaction effect on TS SWC is that a simulation study can be useful to decide on the feasibility of including a search for TS‐based RLs for a specific site. Copyright © 2013 John Wiley & Sons, Ltd.     

Vegetation impacts soil water content patterns by shaping canopy water fluxes and soil properties

Soil water content is a key variable for biogeochemical and atmospheric coupled processes. Its small‐scale heterogeneity impacts the partitioning of precipitation (e.g., deep percolation or transpiration) by triggering threshold processes and connecting flow paths. Forest hydrologists frequently hypothesized that throughfall and stemflow patterns induce soil water content heterogeneity, yet experimental validation is limited. Here, we pursued a pattern‐oriented approach to explore the relationship between net precipitation and soil water content. Both were measured in independent high‐resolution stratified random designs on a 1‐ha temperate mixed beech forest plot in Germany. We recorded throughfall (350 locations) and stemflow (65 trees) for 16 precipitation events in 2015. Soil water content was measured continuously in topsoil and subsoil (210 profiles). Soil wetting was only weakly related to net precipitation patterns. The precipitation‐induced pattern quickly dissipates and returns to a basic pattern, which is temporally stable. Instead, soil hydraulic properties (by the proxy of field capacity) were significantly correlated with this stable soil water content pattern, indicating that soil structure more than net precipitation drives soil water content heterogeneity. Also, both field capacity and soil water content were lower in the immediate vicinity of tree stems compared to further away at all times, including winter, despite stemflow occurrence. Thus, soil structure varies systematically according to vegetation in our site. We conclude that enhanced macroporosity increases gravity‐driven flow in stem proximal areas. Therefore, although soil water content patterns are little affected by net precipitation, the resulting soil water fluxes may strongly be affected. Specifically, this may further enhance the channelling of stemflow to greater depth and beyond the rooting zone.     

Estimation of surface roughness (z0) over a stabilizing coastal dune field based on vegetation and topography

Accurate knowledge of the surface roughness and the resultant wind speed are important for many applications, such as climatic models, wind power meteorology, agriculture and erosion hazards, especially on sand dunes in arid and semi‐arid environments, where vegetation cover is scarce. In this study we aimed at quantifying the effects of vegetation cover and topography on surface roughness over a stabilizing dune field on the southern coast of Israel. Forty‐six wind measurements were made at various distances from the coastline, ranging from 10 to 2800 m, and z₀ values were calculated from the wind measurements based on the ratio between the wind gust and the average wind speed. We estimated vegetation cover using the soil adjusted vegetation index (SAVI) from Landsat satellite images for the upwind sector at various lengths, ranging from 15 to 400 m, and based on digital elevation models and differential GPS field measurements we calculated the topographic variable of the relative heights of the stations. z₀ values were positively correlated with the winter SAVI values (r = 0·87 at an upwind length of 200 m) and negatively correlated with the relative height (r = ?0·68 at an upwind length of 200–400 m for the inland dune stations). Using these variables we were able to create a map of estimated z₀ values having an accuracy of over 64%. Such maps provide a better understanding of the spatial variability in both wind speed and sand movement over coastal dune areas. Copyright © 2007 John Wiley & Sons, Ltd.