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Soil mapping for large or small areas done rapidly. Technique requires simple radiometric measurements of L-band (15 to 30 cm) and thermal infrared emissions from ground within 2 days after saturation of surface. Technique based on observation that correlation exists between L-band emissivity and hydraulic conductivity of soil.
Experiments are reported which show that measuring metabolic activity in soil solutions by means of dynamic changes in electrical conductivity, water-soluble Ca, or water-soluble Mg is a feasible life detection method. The addition of 0.5% glucose solutions to 12 different air-dried soils always resulted in increases in all three of these parameters. The kinetics and magnitude of these changes for at least two and usually all three of the parameters over a 14-day period were clearly distinguishable from the changes in heat-sterilized controls or unsterilized controls without added glucose. In general, maximal values were achieved more rapidly under aerobic than under anaerobic incubation.
We will present laboratory data and model results which show that a Mars Microprobe-type thermal conductivity experiment can be useful on future planetary missions.
We present a model of heat conduction for mono-sized spherical particulate media under stagnant gases based on the kinetic theory of gases, numerical modeling of Fourier s law of heat conduction, theoretical constraints on the gas thermal conductivity at various Knudsen regimes, and laboratory measurements. Incorporating the effect of the temperature allows for the derivation of the pore-filling gas conductivity and bulk thermal conductivity of samples using additional parameters (pressure, gas composition, grain size, and porosity). The radiative and solid-to-solid conductivities are also accounted for. Our thermal model reproduces the well-established bulk thermal conductivity dependency of a sample with the grain size and pressure and also confirms laboratory measurements finding that higher porosities generally lead to lower conductivities. It predicts the existence of the plateau conductivity at high pressure, where the bulk conductivity does not depend on the grain size. The good agreement between the model predictions and published laboratory measurements under a variety of pressures, temperatures, gas compositions, and grain sizes provides additional confidence in our results. On Venus, Earth, and Titan, the pressure and temperature combinations are too high to observe a soil thermal conductivity dependency on the grain size, but each planet has a unique thermal inertia due to their different surface temperatures. On Mars, the temperature and pressure combination is ideal to observe the soil thermal conductivity dependency on the average grain size. Thermal conductivity models that do not take the temperature and the pore-filling gas composition into account may yield significant errors.
A numerical model of heat conduction through particulate media made of spherical grains cemented by various bonding agents is presented. The pore-filling gas conductivity, volume fraction, and thermal conductivity of the cementing phase are tunable parameters. Cement fractions <0.001-0.01% in volume have small effects on the soil bulk thermal conductivity. A significant conductivity increase (factor 3-8) is observed for bond fractions of 0.01 to 1% in volume. In the 1 to 15% bond fraction domain, the conductivity increases continuously but less intensely (25-100% conductivity increase compared to a 1% bond system). Beyond 15% of cements, the conductivity increases vigorously and the bulk conductivity rapidly approaches that of bedrock. The composition of the cements (i.e. conductivity) has little influence on the bulk thermal inertia of the soil, especially if the volume of bond <10%. These results indicate that temperature measurements are sufficient to detect cemented soils and quantify the amount of cementing phase, but the mineralogical nature of the bonds and the typical grain size are unlikely to be determined from orbit. On Mars, a widespread surface unit characterized by a medium albedo (0.19-0.26) and medium/high thermal inertia (200-600 J s(0.5)/sq m/K) has long been hypothesized to be associated with a duricrust. The fraction of cement required to fit the thermal data is less than approx.1-5% by volume. This small amount of material is consistent with orbital observations, confirming that soil cementation is an important factor controlling the thermal inertia of the Martian surface
A parameterization of land surfaces based on a statistical-dynamical approach is presented. With this approach, the most important characteristics of the soil-plant-atmosphere system that affect the partition of energy (e.g., plant stomatal conductance, soil humidity, and surface roughness) are represented by a pdf rather than by a single 'representative' value. A primary simplified version of this parameterization is used to estimate the land-surface energy fluxes that are produced at the grid scale by various distributions of stomatal conductance under a broad range of environmental conditions. To demonstrate the approach's potential, results are compared with the same fluxes calculated with a big leaf model using the mean stomatal conductance that corresponds to the distributions. Large absolute and relative differences are obtained between the two schemes for many combinations of stomatal conductance pdfs and environmental conditions.
In traditional applications in soil physics it is convention to scale porous media properties, such as hydraulic conductivity, soil water diffusivity, and capillary head, with the gravitational acceleration. In addition, the Richards equation for water flux in partially saturated porous media also contains a gravity term. With the plans to develop plant habitats in space, such as in the International Space Station, it becomes necessary to evaluate these properties and this equation under conditions of microgravitational acceleration. This article develops models for microgravity steady state two-phase flow, as found in irrigation systems, that addresses critical design issues. Conventional dimensionless groups in two-phase mathematical models are scaled with gravity, which must be assigned a value of zero for microgravity modeling. The use of these conventional solutions in microgravity, therefore, is not possible. This article therefore introduces new dimensionless groups for two-phase models. The microgravity models introduced here determined that in addition to porous media properties, important design factors for microgravity systems include applied water potential and the ratio of inner to outer radii for cylindrical and spherical porous media systems.
The return to the Moon has ignited the need to characterize the lunar regolith using fast, reliable in-situ methods. Characterizing the physical properties of the rocks and soils can be very difficult because of the many complex parameters that influence the measurements. In particular, soil electrical property measurements are influenced by temperature, mineral type, grain size, porosity, and soil conductivity. Determining the dielectric constant of lunar materials may be very important in providing quick characterization of surface deposits, especially for the Moon. A close examination of the lunar regolith samples collected by the Apollo astronauts indicates that the rocks and soils on the Moon are dominated by silicates and oxides. In this presentation, we will show that determining the dielectric constant measurements can provide a simple, quick detection method for minerals that contain titanium, iron, and water. Their presence is manifest by an unusually large imaginary permittivity.
The return to the Moon has ignited the need to characterize the lunar regolith using in situ methods. An examination of the lunar regolith samples collected by the Apollo astronauts indicates that only a few minerals (silicates and oxides) need be considered for in situ resource utilization (ISRU). This simplifies the measurement requirements and allows a detailed analysis using simple methods. Characterizing the physical properties of the rocks and soils is difficult because of many complex parameters such as soil temperature, mineral type, grain size, porosity, and soil conductivity. In this presentation, we will show that the dielectric constant measurement can provide simple detection for oxides such as TiO2, FeO, and water. Their presence is manifest by an unusually large imaginary permittivity.
Pedotransfer functions (PTFs) provide point predictions of soil hydraulic properties from more readily measured soil characteristics, yet uncertainties and biases in measurement methods, sampling distributions, and boundary conditions can limit accuracy when estimating near-saturated hydraulic conductivity (K(n)). These limitations may be particularly problematic in understudied urban landscapes that often contain altered hydraulic properties. To better treat deficiencies in PTF performance, we addressed three objectives, which were to: 1) develop PTFs to predict urban K(n), 2) assess bulk density and coarse fragments as explanatory variables; and 3) evaluate the predictive capability of these PTFs by comparing their output to measured hydraulic conductivity values from three other studies of urban soil hydraulics. We used artificial neural networks (ANN) and random forest (RF) approaches to predict urban K(n), with the training dataset including 307 tension infiltrometer tests and other measurements drawn from urban soil assessments in 11 U.S. cities. The PTFs utilized a hierarchy of inputs, starting with percentage sand, silt, clay, and then adding percentage coarse fragments and bulk density. The ANN models performed similar to the RF models, and all models exhibited similar or better predictive performance as models results collected from published articles. The inclusion of bulk density or coarse fragments did not improve accuracy over soil texture alone. Possible reasons for this result include low correlation between K(n) and bulk density and the exclusion of large voids during flow measurements with tension infiltrometers. The models have been made available as an open-source software package to encourage adoption by users working in urban systems.
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The thermal conductivity and thermal diffusivity of lunar fines samples from the Apollo 11 and Apollo 12 missions, determined at low temperatures as a function of temperature and various densities, are reviewed. It is shown that the thermal conductivity of lunar soil is nearly the same as that of terrestrial basaltic rock under the same temperature and pressure conditions.
The thermal conductivity of a simulated Apollo 12 soil sample is measured as a function of interstitial gas density, and implications for the thermal properties of lunar and Martian regolith are discussed. Measurements were performed for samples consisting of a mixture of Knippa and Berkely basalt powders with a grain size distribution identical to that of Apollo 12 lunar soil samples by the needle probe technique at interstitial pressures of He, N2, Ar and CO2 from 133,000 to 0.0133 Pa. It is shown that sample thermal conductivity decreases with decreasing interstitial gas pressure down to 1.0 Pa, due to the decreasing effective thermal conductivity of interstitial gas with decreasing gas pressure. Constant thermal conductivity values of 8.8 mW/m per K and 10.9 mW/m per K are obtained for sample densities of 1.70 and 1.85 g/cu cm, respectively, in agreement with in situ lunar regolith measurements. The results, which are greater than those obtained in previous soil studies, are explained by the dense packing of soil particles and enhanced intergranular thermal contact in the present experimental configuration, rather than the influence of interstitial gas pressure. The differences in conductivity between loose soils and packed regolith may also be used to account for the two peaks observed in Martian surface thermal inertia data.
Predictive procedures for developing soil hydrologic properties (i.e., relationships of soil water pressure and hydraulic conductivity to soil water content) are presented. Three models of the soil water pressure-water content relationship and one model of the hydraulic conductivity-water content relationship are discussed. Input requirements for the models are indicated, and computational procedures are outlined. Computed hydrologic properties for Keith silt loam, a soil typer near Colby, Kansas, on which the 1978 Agricultural Soil Moisture Experiment was conducted, are presented. A comparison of computed results with experimental data in the dry range shows that analytical models utilizing a few basic hydrophysical parameters can produce satisfactory data for large-scale applications.
The term "satellite-derived management zones" (SAMZ) denotes agricultural management zones that are subdivisions of large fields and that are derived from images of the fields acquired by instruments aboard Earth orbiting satellites during approximately the past 15 years. "SAMZ" also denotes the methodology and the software that implements the methodology for creating such zones. The SAMZ approach is one of several products of continuing efforts to realize a concept of precision agriculture, which involves optimal variations in seeding, in application of chemicals, and in irrigation, plus decisions to farm or not to farm certain portions of fields, all in an effort to maximize profitability in view of spatial and temporal variations in the growth and health of crops and in the chemical and physical conditions of soils. As used here, "management zone" signifies, more precisely, a subdivision of a field within which the crop production behavior is regarded as homogeneous. From the perspective of precision agriculture, management zones are the smallest subdivisions between which the seeding, application of chemicals, and other management parameters are to be varied. In the SAMZ approach, the main sources of data are the archives of satellite imagery that have been collected over the years for diverse purposes. One of the main advantages afforded by the SAMZ approach is that the data in these archives can be reused for purposes of precision agriculture at low cost. De facto, these archives contain information on all sources of variability within a field, including weather, crop types, crop management, soil types, and water drainage patterns. The SAMZ methodology involves the establishment of a Web-based interface based on an algorithm that generates management zones automatically and quickly from archival satellite image data in response to requests from farmers. A farmer can make a request by either uploading data describing a field boundary to the Web site or else drawing the boundary on a reference image. Hence, a farmer can start to engage in precision farming shortly after gaining access to the Web site, without need for incurring the high costs of conventional precision-agriculture data-collection practices that include collecting soil samples, mapping electrical conductivity of soil, and compiling multi-year crop-yield data. Given the boundary of a field, a SAMZ server computes the zones within the field in a three-stage process. In the first stage, a vector-valued image of the field is constructed by assembling, from the archives, the equivalent of a stack of the available images of the field (see figure). In the second stage, the vector-valued image is analyzed by use of a wavelet transform that detects spatial variations considered significant for precision farming while suppressing small-scale heterogeneities that are regarded as insignificant. In the third stage, a segmentation algorithm assembles the zones from smaller regions that have been identified in the wavelet analysis.
The term "satellite-derived management zones" (SAMZ) denotes agricultural management zones that are subdivisions of large fields and that are derived from images of the fields acquired by instruments aboard Earth-orbiting satellites during approximately the past 15 years. "SAMZ" also denotes the methodology and the software that implements the methodology for creating such zones. The SAMZ approach is one of several products of continuing efforts to realize a concept of precision agriculture, which involves optimal variations in seeding, in application of chemicals, and in irrigation, plus decisions to farm or not to farm certain portions of fields, all in an effort to maximize profitability in view of spatial and temporal variations in the growth and health of crops, and in the chemical and physical conditions of soils. As used here, "management zone" signifies, more precisely, a subdivision of a field within which the crop-production behavior is regarded as homogeneous. From the perspective of precision agriculture, management zones are the smallest subdivisions between which the seeding, application of chemicals, and other management parameters are to be varied. In the SAMZ approach, the main sources of data are the archives of satellite imagery that have been collected over the years for diverse purposes. One of the main advantages afforded by the SAMZ approach is that the data in these archives can be reused for purposes of precision agriculture at low cost. De facto, these archives contain information on all sources of variability within a field, including weather, crop types, crop management, soil types, and water drainage patterns. The SAMZ methodology involves the establishment of a Web-based interface based on an algorithm that generates management zones automatically and quickly from archival satellite image data in response to requests from farmers. A farmer can make a request by either uploading data describing a field boundary to the Web site or else drawing the boundary on a reference image. Hence, a farmer can start to engage in precision farming shortly after gaining access to the Web site, without the need for incurring the high costs of conventional precision-agriculture data-collection practices that include collecting soil samples, mapping electrical conductivity of soil, and compiling multiyear crop-yield data. Given the boundary of a field, a SAMZ server computes the zones within the field in a three-stage process. In the first stage, a vector-valued image of the field is constructed by assembling, from the archives, the equivalent of a stack of the available images of the field (see figure). In the second stage, the vector-valued image is analyzed by use of a wavelet transform that detects spatial variations considered significant for precision farming while suppressing small-scale heterogeneities that are regarded as insignificant. In the third stage, a segmentation algorithm assembles the zones from smaller regions that have been identified in the wavelet analysis.
Water transport through a microporous tube-soil-plant system was investigated by measuring the response of soil and plant water status to step change reductions in the water pressure within the tubes. Soybeans were germinated and grown in a porous ceramic 'soil' at a porous tube water pressure of -0.5 kpa for 28 d. During this time, the soil matric potential was nearly in equilibrium with tube water pressure. Water pressure in the porous tubes was then reduced to either -1.0, -1.5 or -2.0 kPa. Sap flow rates, leaf conductance and soil, root and leaf water potentials were measured before and after this change. A reduction in porous tube water pressure from -0.5 to -1.0 or -1.5 kPa did not result in any significant change in soil or plant water status. A reduction in porous tube water pressure to -2.0 kPa resulted in significant reductions in sap flow, leaf conductance, and soil, root and leaf water potentials. Hydraulic conductance, calculated as the transpiration rate/delta psi between two points in the water transport pathway, was used to analyse water transport through the tube-soil-plant continuum. At porous tube water pressures of -0.5 to-1.5 kPa soil moisture was readily available and hydraulic conductance of the plant limited water transport. At -2.0 kPa, hydraulic conductance of the bulk soil was the dominant factor in water movement.
Infiltration is a time varying process of water entry into soil. Experiments were conducted here using truck based microwave radiometers to observe small plots during and following sprinkler irrigation. Experiments were conducted on a sandy loam soil in 1994 and a silt loam in 1995. Sandy loam soils typically have higher infiltration capabilities than clays. For the sandy loam the observed brightness temperature (TB) quickly reached a nominally constant value during irrigation. When the irrigation was stopped the TB began to increase as drainage took place. The irrigation rates in 1995 with the silt loam soil exceeded the saturated conductivity of the soil. During irrigation the TB values exhibited a pattern that suggests the occurrence of coherent reflection, a rarely observed phenomena under natural conditions. These results suggested the existence of a sharp dielectric boundary (wet over dry soil) that was increasing in depth with time.