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How Airflow Affects Soil Water Dynamics
Abstract and Figures
The concept of enhanced vapor transfer in unsaturated soils has been questioned for its reliance on soil temperature gradient, which leads to consideration of other mechanisms of vapor transfer, e.g. advective vapor transfer due to soil air pressure gradient. Although the advective flux is an important portion of evaporation, there is a lack of knowledge in its effect on evaporation. In order to assess the dependence of evaporation on the soil air pressure gradient, the vertical one-dimensional two-phase heat and mass flow model developed in Chap. 4 is used to investigate the advective effect in both low- and high-permeability soils. The advective effect is reflected by underestimating evaporation when the airflow is neglected and is more evident in the low-permeability soil. Neglecting airflow causes the underestimation error of 53.3 % on the day right after rainfall event in the low-permeability soil (7.9 × 10−4 cm s−1), and 33.3 % in the high-permeability soil (2 × 10−3 cm s−1). The comparisons of driving forces and conductivities show that the isothermal liquid flux, driven by the soil matric potential gradient, is the main reason for the underestimation error.
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The Tibetan Plateau is a key region of land-atmosphere interactions, as it provides an elevated heat source to the middle-troposphere. The Plateau surfaces are typically characterized by alpine meadows and grasslands in the central and eastern part while by alpine deserts in the western part. This study evaluates performance of three state-of-the-art land surface models (LSMs) for the Plateau typical land surfaces. The LSMs of interest are SiB2 (the Simple Biosphere), CoLM (Common Land Model), and Noah. They are run with default parameters at typical alpine meadow sites in the central Plateau and typical alpine desert sites in the western Plateau. The recognized key processes and modeling issues are as follows. First, soil stratification is a typical phenomenon beneath the alpine meadows, with dense roots and soil organic matters within the topsoil, and it controls the profile of soil moisture in the central and eastern Plateau; all models significantly under-estimate the soil moisture within the topsoil. Second, a soil surface resistance controls the surface evaporation from the alpine deserts but it has not been reasonably modeled in LSMs; a new scheme is proposed to determine this resistance from soil water content. Third, an excess resistance controls sensible heat fluxes from dry bare-soil or sparsely vegetated surfaces, and all LSMs significantly under-predict the ground-air temperature difference in the daytime. A parameterization scheme for this resistance has been shown effective to remove this bias.
The response of a bare soil surface to atmospheric forcing -- rain, wind, sunshine, etc. -- may be expressed in terms of the resultant evaporation rate and sensible and radiant heat losses. Examining the earth-atmosphere interface in an idealized one-dimensional framework, we evaluate a hierarchy of mathematical models in terms of their ability to predict this land surface response. The evaluation is based on simulation, using typical climatologic and soil parameters. The reference model, against which the other models are tested, is based on a numerical solution of a very detailed description of heat and moisture movement in porous media. The alternative models are, to a greater or less extent, simpler both conceptually and computationally than the reference model. They include the following: 1. A family of models obtained by introducing various sinplifying assumptions in the reference model. These corcern the roles of water vapor, of soil moisture retention hysteresis, and of a few other minor effects. 2. A set of models constructed by linking the forcerestore method of soil temperature prediction to each of three soil moisture parameterizations -- a two-node finite element model, a conceptualization used by climate modelers, and a nonlinear diffusion model. Using the nominal soil and climatologic parameters, we determine the critical physical mechanisms affecting the surface fluxes of water and heat. We find that an isothermal moisture equation, with the hydraulic conductivity augmented by a vapor conductivity, and accounting for hysteresis, is sufficient. The nonlinear diffusion parameterization, which includes these effects, is extended to account for redistribution. In conjunction with the force-restore method, it successfully predicts evaporation under various climatic and soil conditions.
The purpose of this work is to develop a detailed, physically-based model of the response of the land surface to atmospheric forcing. The coupled, nonlinear partial differential equations governing mass and heat transport in the soil are derived. The theory of Philip and de Vries is re-cast in terms of the soil water matric potential, accounting for soil inhomogeneities and hysteresis of the moisture retention process. An existing model of hysteresis is modified to incorporate the effect of temperature and to facilitate numerical analysis. The Galerkin finite element method is applied in the development of a numerical algorithm for the solution of the governing equations. The numerical procedure is coded in FORTRAN for computer solution and several examples are run in order to test the method. The various modes of mass and heat transport are simulated accurately. A proposed procedure for the evaluation of non-linear storage coefficients in the numerical scheme yields excellent mass and energy balances.
The use of perturbed observations in the traditional ensemble Kalman filter (EnKF) results in a suboptimal filter behaviour, particularly for small ensembles. In this work, we propose a simple modification to the traditional EnKF that results in matching the analysed error covariance given by Kalman filter in cases when the correction is small; without perturbed observations. The proposed filter is based on the recognition that in the case of small corrections to the forecast the traditional EnKF without perturbed observations reduces the forecast error covariance by an amount that is nearly twice as large as that is needed to match Kalman filter. The analysis scheme works as follows: update the ensemble mean and the ensemble anomalies separately; update the mean using the standard analysis equation; update the anomalies with the same equation but half the Kalman gain. The proposed filter is shown to be a linear approximation to the ensemble square root filter (ESRF). Because of its deterministic character and its similarity to the traditional EnKF we call it the ‘deterministic EnKF’, or the DEnKF. A number of numerical experiments to compare the performance of the DEnKF with both the EnKF and an ESRF using three small models are conducted. We show that the DEnKF performs almost as well as the ESRF and is a significant improvement over the EnKF. Therefore, the DEnKF combines the numerical effectiveness, simplicity and versatility of the EnKF with the performance of the ESRFs. Importantly, the DEnKF readily permits the use of the traditional Schur product-based localization schemes.
An abridged, student-oriented edition of Hillel's earlier published Environmental Soil Physics, this is a more succinct elucidation of the physical principles and processes governing the behavior of soil and the vital role it plays in both natural and managed ecosystems. The textbook is self-contained and self-explanatory, with numerous illustrations and sample problems. Based on sound fundamental theory, the textbook leads to a practical consideration of soil as a living system in nature and illustrates the influences of human activity upon soil structure and function. Students, as well as other readers, will better understand the importance of soils and the pivotal possition they occupy with respect to careful and knowledgeable conservation.
Numerical simulation has become a widely practiced and accepted technique for studying flow and transport processes in the vadose zone and other subsurface flow systems. This article discusses a suite of codes, developed primarily at Lawrence Berkeley National Laboratory (LBNL), with the capability to model multiphase flows with phase change. We summarize history and goals in the development of the TOUGH codes, and present the governing equations for multiphase, multicomponent flow. Special emphasis is given to space discretization by means of integral finite differences (IFD). Issues of code implementation and architecture are addressed, as well as code applications, maintenance, and future developments.
The annual runoff rates generated by land surface models (LSMs) participating in the Global Soil Wetness Project (GSWP) are compared to observed rates in well-instrumented basins across the globe. Because such an offline evaluation can be clouded by an overwhelming influence of the atmospheric forcing itself (relative to the imposed land surface physics) on model output, we also estimate runoff rates with a decades-old climatological relation devised by M.I. Budyko, a relation that depends solely on annual precipitation and net radiation. The LSMs and the estimates derived with Budyko's relation are found to have standard errors of the same order (roughly 100 mm/yr). Thus, we conclude that the complexities inherent in these state-of-the-art LSMs did not lead to increased accuracy in the simulated energy and water balances at the annual time scale. Proper LSM formulations are nevertheless recognized as essential for realistic land surface behavior at shorter (e.g., monthly or hourly) time scales, for which a simple Budyko-type equation would be in much greater error.