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Register a new userSoil and soil CO2 magnify greenhouse effect
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Soil has been recognized as an indirect driver of global warming by regulating atmospheric greenhouse gases. However, in view of the higher heat capacity and CO2 concentration in soil than those in atmosphere, the direct contributions of soil to greenhouse effect may be non-ignorable. Through field manipulation of CO2 concentration both in soil and atmosphere, we demonstrated that the soil-retained heat and its slow transmission process within soil may cause slower heat leaking from the earth. Furthermore, soil air temperature was non-linearly affected by soil CO2 concentration with the highest value under 7500 ppm CO2. This study indicates that the soil and soil CO2, together with atmospheric CO2, play indispensable roles in fueling the greenhouse effect. We proposed that anthropogenic changes in soils should be focused in understanding drivers of the globe warming.
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A minimalist stochastic model of primary soil salinity is proposed, in which the rate of soil salinization is determined by the balance between dry and wet salt deposition and the intermittent leaching events caused by rainfall events. The long term probability density functions of salt mass and concentration are found by reducing the coupled soil moisture and salt mass balance equation to a single stochastic differential equation driven by multiplicative Poisson noise. The novel analytical solutions provide insight on the interplay of the main soil, plant and climate parameters responsible for long-term soil salinization. In particular, they show the existence of two distinct regimes, one where the mean salt mass remains nearly constant (or decreases) with increasing rainfall frequency, and another where mean salt content increases markedly with increasing rainfall frequency. As a result, relatively small reductions of rainfall in drier climates may entail dramatic shifts in long-term soil salinization trends, with significant consequences e.g. for climate change impacts on rain-fed agriculture.
Proximal soil sensors are taking hold in the understanding of soil hydrogeological processes involved in precision agriculture. In this context, permanently installed gamma ray spectroscopy stations represent one of the best space-time trade off methods at field scale. This study proved the feasibility and reliability of soil water content monitoring through a seven-month continuous acquisition of terrestrial gamma radiation in a tomato test field. By employing a 1 L sodium iodide detector placed at a height of 2.25 m, we investigated the gamma signal coming from an area having a ~25 m radius and from a depth of approximately 30 cm. Experimental values, inferred after a calibration measurement and corrected for the presence of biomass, were corroborated with gravimetric data acquired under different soil moisture conditions, giving an average absolute discrepancy of about 2%. A quantitative comparison was carried out with data simulated by AquaCrop, CRITeRIA, and IRRINET soil-crop system models. The different goodness of fit obtained in bare soil condition and during the vegetated period highlighted that CRITeRIA showed the best agreement with the experimental data over the entire data-taking period while, in presence of the tomato crop, IRRINET provided the best results.
Carbon sequestration is the process of capture and long-term storage of atmospheric carbon dioxide (CO2) with the aim to avoid dangerous climate change. In this paper, we propose a simple mathematical model (a coupled system of nonlinear ODEs) to capture some of the dynamical effects produced by adding charcoal to fertile soils. The main goal is to understand to which extent charcoal is able to lock up carbon in soils. Our results are preliminary in the sense that we do not solve the CO2 sequestration problem. Instead, we do set up a flexible modeling framework in which the interaction between charcoal and soil can be tackled by means of mathematical tools. We show that our model is well-posed and has interesting large-time behaviour. Depending on the reference parameter range (e.g. type of soil) and chosen time scale, numerical simulations suggest that adding charcoal typically postpones the release of CO2.
Proximal gamma-ray spectroscopy supported by adequate calibration and correction for growing biomass is an effective field scale technique for a continuous monitoring of top soil water content dynamics to be potentially employed as a decision support tool for automatic irrigation scheduling. This study demonstrates that this approach has the potential to be one of the best space-time trade-off methods, representing a joining link between punctual and satellite fields of view. The inverse proportionality between soil moisture and gamma signal is theoretically derived taking into account a non-constant correction due to the presence of growing vegetation beneath the detector position. The gamma signal attenuation due to biomass is modelled with a Monte Carlo-based approach in terms of an equivalent water layer which thickness varies in time as the crop evolves during its life-cycle. The reliability and effectiveness of this approach is proved through a 7 months continuous acquisition of terrestrial gamma radiation in a 0.4 ha tomato (Solanum lycopersicum) test field. We demonstrate that a permanent gamma station installed at an agricultural field can reliably probe the water content of the top soil only if systematic effects due to the biomass shielding are properly accounted for. Biomass corrected experimental values of soil water content inferred from radiometric measurements are compared with gravimetric data acquired under different soil moisture levels, resulting in an average percentage relative discrepancy of about 3% in bare soil condition and of 4% during the vegetated period. The temporal evolution of corrected soil water content values exhibits a dynamic range coherent with the soil hydraulic properties in terms of wilting point, field capacity and saturation.
This article focuses on liquefaction of saturated granular soils, triggered by earthquakes. Liquefaction is definedhere as the transition from a rigid state, in which the granular soil layer supports structures placed on its surface, toa fluidlike state, in which structures placed initially on the surface sink to their isostatic depth within the granularlayer.We suggest a simple theoretical model for soil liquefaction and show that buoyancy caused by the presence ofwater inside a granular medium has a dramatic influence on the stability of an intruder resting at the surface of themedium.We confirm this hypothesis by comparison with laboratory experiments and discrete-element numericalsimulations. The external excitation representing ground motion during earthquakes is simulated via horizontalsinusoidal oscillations of controlled frequency and amplitude. In the experiments, we use particles only slightlydenser than water, which as predicted theoretically increases the effect of liquefaction and allows clear depth-of-sinkingmeasurements. In the simulations, a micromechanical model simulates grains using molecular dynamicswith friction between neighbors. The effect of the fluid is captured by taking into account buoyancy effects onthe grains when they are immersed. We show that the motion of an intruder inside a granular medium is mainlydependent on the peak acceleration of the ground motion and establish a phase diagram for the conditions underwhich liquefaction happens, depending on the soil bulk density, friction properties, presence of water, and peak acceleration of the imposed large-scale soil vibrations.We establish that in liquefaction conditions, most cases relaxtoward an equilibrium position following an exponential in time.We also show that the equilibrium position itself,for most liquefaction regimes, corresponds to the isostatic equilibrium of the intruder inside a medium of effectivedensity. The characteristic time to relaxation is shown to be essentially a function of the peak ground velocity.
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