摘要 :
A wide variety of volatile organic chemicals (VOC) have been applied to agricultural land or buried in chemical waste sites. The fate of these chemicals depends upon several mechanisms such as sorption, degradation, and transport ...
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A wide variety of volatile organic chemicals (VOC) have been applied to agricultural land or buried in chemical waste sites. The fate of these chemicals depends upon several mechanisms such as sorption, degradation, and transport in liquid and gaseous phases. Understanding the transport mechanisms affecting the volatile chemicals can lead to better management strategies. A theory describing inorganic solute transport, water and heat transfer, and the fate and transport of VOC in porous media has been developed. This theory includes matric water pressure head, solution osmotic pressure head, gravity pressure head, temperature, inorganic solute concentration, and VOC concentration gradients as driving forces for heat and mass transfer. The effect of surface tension, as a function of VOC concentration and temperature, on the matric water pressure head is included. The VOC can be associated with gas, liquid, and solid phases of the porous media. The gas and liquid phases are mobile, but the solid phase is immobile. The transfer of VOC across the gas/liquid, liquid/solid, and gas/solid interfaces is included using sorption-equilibrium assumptions at the interfaces. The VOC can degrade. This degradation is described by a first-order decay rate. The theory can be used to predict spatial and temporal variations of water content, temperature, inorganic concentration and the total concentration of VOC within a porous medium. The concentration of VOC in each phase can be predicted also.
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摘要 :
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 ...
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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.
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