Soil-atmosphere Model Research Articles

On the Physics of High CAPE

Abstract Large values of convective available potential energy (CAPE) are an important ingredient for many severe convective storms, yet there has been comparatively little research on how, physically, such large values arise or why they take on the observed values and climatology. Here we build on recently published observational and theoretical work to construct a simple, one-dimensional coupled soil–atmosphere model of preconvective boundary layer growth, driven by a single diurnal cycle of prescribed net surface radiation. Based on this model and previously published research, we suggest that high CAPE (>∼1000 J kg−1) results when air masses that have been significantly modified by passage over dry, lightly vegetated soils are advected over moist and/or moderately vegetated soils and then exposed to surface solar heating. Several diurnal cycles may be needed to raise the moist static energy of the boundary layer to levels consistent with high CAPE. The production of CAPE and erosion of convective inhibition (CIN) are strongly affected by the potential temperature of the desert-modified air mass, the level of near-surface soil moisture (and root-zone soil moisture if significant vegetation is present), the type of soil, and the characteristics of the vegetation. Consequently, CAPE production and severe convective weather may be significantly affected by regional-scale land-use changes and by climate change. Significance Statement The energy available for severe convective storms depends strongly on the properties of the underlying soil and vegetation and the temperature of air masses formed over dry terrain upstream. This implies that the severity of convective storms can be strongly affected by changes in land use and by climate change.

Prediction of soil suction using measured climatic data

This paper presents calibration and validation of a one-dimensional soil–atmosphere model created using the SVFlux software package for predicting soil suction changes based on the measured climate data at two Oklahoma Mesonet sites. The parameters for the soil water characteristic curves and the hydraulic conductivity function were obtained from published calibration studies conducted using laboratory test results on soil samples extracted from these sites. The plant cover quality, the root depth and the root uptake distribution function were first calibrated using 1-year data at one site. While a rectangular root uptake distribution function overpredicted suction at deeper layers, the triangular uptake distribution function overpredicted suction at shallower depths. In addition, reducing the root depth to 1 m improved the predictions at surface layers and led to overestimation of the suction at deeper layers. Based on the root mean squares of the differences between the simulated and the measured values and weighting the shallower depths more, a rectangular root uptake distribution function and a root depth of 1 m were selected to predict suction values at the calibration site and the second site for another year. Reasonable predictions of soil suction values at shallower depths were obtained at both sites.

VINESYM: an integrated vine and grapevine mathematical model for vegetative development and production quality forecast

The present work deal with the development of a mathematical model able to predict, using time dependent meteorological data, soil and vine characteristics, the growing of a vine and grapevine in terms of leaf area, shoot length, fruit and vegetative mass and finally sugar and acid content of the berry. The model is based upon a source-sink relationship approach, integrated with a soil-atmosphere model, where water accumulation in soil, sap flow across vine are coupled with potential carbon demand functions to directly consider possible water and temperature stresses. The model includes also a N2 sink-source approach, limiting growth rate following N2 availability. Finally, a mechanistic model to evaluate sugar accumulation and a correlation-based model for acid concentration evaluation in the berry is coupled with vegetative growth, to provide the information required to manage vineyard operations and evaluate the impact to the potential wine quality. The primary distinctive trait of this model is then the integration and feedback among prediction of grapevine quality model (sugar an acid content) and vegetative growth model, using a common initial ad boundary conditions data set.

Improvements to the calculation of actual evaporation from bare soil surfaces

Evaporation of water from a saturated soil surface with ample free water is known as potential evaporation, PE, and the associated physical processes are quite well understood. However, evaporation of water from an unsaturated soil surface is known as actual evaporation, AE, and the associated physical processes are more complex and less understood. The calculation of actual evaporation is important for many geotechnical engineering applications. Soil suction and the corresponding water content at which the AE rate begins to depart from the PE rate during a drying process are re-assessed using a series of laboratory tests (i.e., thin soil section drying tests and soil column drying tests). Laboratory results show that the suction at which the actual rate of evaporation begins to depart from the PE rate for soil columns (or thick soil layers) may be different than for thin soil layers. Suction at the “evaporation-rate reduction point” (ERRP) appears to be approximately 3000 kPa for thin soil layers, but is between the air-entry value and residual soil suction for thick soil layers or soil columns. The analyses presented in this paper have resulted in the development of a methodology for the estimation of suction corresponding to the ERRP in soil columns. Equations are also proposed to calculate the coefficient of surface moisture availability, vapour pressure, and “surface resistance” at the ground surface. The paper also presents an equation (i.e., new soil–atmosphere moisture flux equation) for predicting evaporation rate from a soil surface using “surface resistance” to vapour water diffusion from the soil to the atmosphere. The proposed soil–atmosphere model is verified using evaporation rate data collected from various drying tests on thin soil layers and soil columns. Reasonably good agreement was found between the computed and measured rates of evaporation. The findings and recommendations in this paper contribute to an improved understanding of the prediction of AE from unsaturated soil surfaces.

Development and evaluation of an efficient soil-atmosphere model (FHAVeT) based on the Ross fast solution of the Richards equation for bare soil conditions

Abstract. In agricultural management, a good timing in operations, such as irrigation or sowing, is essential to enhance both economical and environmental performance. To improve such timing, predictive software are of particular interest. Optimal decision-software would require process modules which provide robust, efficient and accurate predictions while being based on a minimal amount of parameters easily available. The objective of this study is to assess the accuracy of a physically based model with high efficiency. To this aim, this paper develops a coupled model with climatic forcing based on the Ross fast solution for Richards' equation, heat transfer and detailed surface energy balance. The present study is limited to bare soil, but the impact of vegetation can be easily included. The developed model, FHAVeT (Fast Hydro Atmosphere Vegetation Temperature), is evaluated against the coupled model based on the Philip and De Vries (1957) description, TEC. The two models were compared for different climatic and soil conditions. Moreover, the model allows using various pedotransfer functions. The FHAVeT model showed better performance in regards to mass balance, mostly below 0.002 m, and generally improved computation time. In order to allow for a more precise comparison, six time windows were selected. The study demonstrated that the FHAVeT behaviour is quite similar to the TEC behaviour except under some dry conditions. The ability of the models to detect the occurrence of soil intermediate water content thresholds with a 1 day tolerance was also evaluated. Both models agreed in more than 90% of the cases.

Coupled Soil-Atmosphere Modeling for Expansive Regina Clay

Alternate deformations in the expansive clay have crippled civil infrastructure systems in and around the city of Regina that lies in a semi-arid zone. The main objective of this paper was to develop a soil-atmosphere model for predicting the net water flux and the corresponding volume change in the local expansive soil. A one-dimensional hydrologic model was developed, for a homogeneous soil and no ground water table, by coupling material properties with atmospheric parameters. The use of site coordinates ensured material continuity in a strain-independent framework and soil volume changes were calculated using model results in conjunction with laboratory data. Results showed high water absorption and retention capacities for the investigated soil deposit. Conducive atmospheric conditions during summer gradually desatuarted the top 2.5 m layer of the clay that imbibed sporadic rainfall water thereby resulting in volume increases. Cyclic variations in the degree of saturation and the corresponding swelling potential were highest at and near the ground surface and gradually decreased with depth. The highest swelling potential was predicted for late summer and equaled 37%. The model reasonably estimated the soil-atmosphere interactions for the investigated expansive clay and was found to depend on an effective capture of site conditions and material properties. An increased modeling duration can ensure steady state with respect to antecedent moisture.

Modelling of the long-term fate of pesticide residues in agricultural soils and their surface exchange with the atmosphere: Part II. Projected long-term fate of pesticide residues

In the first part of this paper, a simple coupled dynamic soil-atmosphere model for studying the gaseous exchange of pesticide soil residues with the atmosphere is described and evaluated by comparing model results with published measurements of pesticide concentrations in air and soil. In Part II, the model is used to study the concentration profiles of pesticide residues in both undisturbed and annually tilled agricultural soils. Future trends are estimated for the measured air and soil concentrations of lindane and six highly persistent pesticides (toxaphene, p,p'-DDE, dieldrin, cis- and trans-chlordane and trans-nonachlor) over a twenty-year period due to volatilization and leaching into the deeper soil. Wet deposition and particle associated pesticide deposition (that increase soil residue concentrations) and soil erosion, degradation in the soil (other than for lindane) and run-off in precipitation are not considered in this study. Estimates of the rain deposition fluxes are reported that show that, other than for lindane, net volatilization fluxes greatly exceed rain deposition fluxes. The model shows that the persistent pesticides studied are highly immobile in soil and that loss of these highly persistent residues from the soil is by volatilization rather than leaching into the deeper soil. The soil residue levels of these six pesticides are currently sources of net volatilization to the atmosphere and will remain so for many years. The maximum rate of volatilization from the soil was simulated by setting the atmospheric background concentration to zero; these simulations show that the rates of volatilization will not be significantly increased since soil resistance rather than the atmospheric concentration controls the volatilization rates. Annual tilling of the soils increases the volatilization loss to the atmosphere. Nonetheless, the model predicts that, if only air-soil exchange is considered, more than 76% of current persistent pesticide residues will remain after 20 years in the top 7 cm of annually tilled soils. In contrast, lindane is relatively mobile in soil due to weaker binding to soil carbon and leaching of lindane into soil is the main removal route for current lindane residues near the soil surface. The model predicts that the soil is a sink for lindane in the atmosphere and that soil residue levels of lindane in the surface soil are determined by a balance between dry gaseous deposition to the soil from the atmosphere and leaching from the surface soil into the deeper soil where degradation is the dominant loss route. The model suggests that deposition of lindane from the atmosphere will sustain residues in the soil and, in the absence of fresh applications of lindane to the soil, eliminating lindane from the atmosphere would lead to a rapid decline of lindane residues in agricultural soils of the southern U.S.

Prediction of the water balance of two soil cover systems

Soil cover systems are widely used for containment of municipal solid waste, hazardous and mine waste, with the objective of limiting the ingress of precipitation and oxygen. The ability to predict their long-term performance is crucial, as their failure would result in the release of contaminants to the environment. However, monitoring covers over the long term to derive the information needed to aid in design is impractical and there are no large-scale covers that have been in use for a long enough period to generate the data needed. Numerical models have been particularly useful as design tools. To improve their reliability these models may be calibrated to field data and then used to make long-term predictions of cover performance. The field performance of two resistive test soil covers on a 20% sloping waste rock platform is predicted using the two-dimensional soil–atmosphere model Vadose/W. Input data for the model included soil, climate and vegetation data obtained either in the field or laboratory. Model results were compared to field data to assess the validity of the program. The model reasonably simulated field response patterns for soil water storage and suction. Divergence between field performance data and model predictions were significantly influenced by snowmelt, interflow and flow through preferential pathways.

DECOMP – a semi-mechanistic model of litter decomposition

The decomposition of organic matter in a forest ecosystem is simulated by DECOMP, a process-based, semi-mechanistic model built on system dynamic principles. The model divides a litter into four different substrate quality classes with different decomposition rates which are differently influenced by temperature, soil moisture content, pH and aluminum concentration in the soil solution. The model is presented with its core equations and parameter values, but also presented from a system dynamics perspective in its context as a cornerstone in a forest–soil–atmosphere model. DECOMP is aimed at simulating long-term dynamics of decomposition over several forest management rotations, and to function in concert with other model components used in forest modeling. The model is evaluated against empirical data and shows good resemblance when simulating decomposition of Scots pine needle litter with data from a four-year litter bag field experiment.

Regression equations for estimating throughfall nutrient fluxes using wet deposition data and their applicability for simulating the soil acid–base status using the dynamic forest soil–atmosphere model SAFE

Throughfall may contribute large amounts of nutrients to forest soils via the leaching of accumulated dry particulates on the canopy, and by altering incoming precipitation, it may have some control on the acid–base status of the soil. Unfortunately, information about throughfall in forests is sparse and thus, scientists must deal with this gap in knowledge before conducting regional applications of dynamic soil acidification models. The first objective of this paper was to test the possibility of developing regression equations that could allow modellers to estimate throughfall nutrient fluxes using wet deposition nutrient fluxes as input data. The second objective was to test the relative importance of this simplification on regional applications of the dynamic soil–atmosphere model Soil Acidification in Forested Ecosystems (SAFE) using one published application of this model as the base case. Annual throughfall nutrient fluxes were estimated successfully from annual wet deposition fluxes for individual ions. The success of these relationships were however inversely proportional to the intensity at which an ion was involved in exchange reactions: models generally performed better with more conservative ions. The simulation of the soil acid–base status with SAFE suggested that it was appropriate to use the throughfall estimates yielded using the regression equations. Also, testing of the SAFE output using different regression equations in throughfall showed that, in the case of base cations, the key for modelling the soil acid–base status was to produce accurate throughfall estimates of Ca and Mg, and that K had marginal effects. However, a small bias in solution pH was introduced as the balance between alkalinity and acidity in the different categories of deposition appeared to be diverging from the base case (measured) values. The use of our approach at other sites may indicate if there is a systematic bias or not in the regressions. Yet, results suggest that the regression equations are appropriate for the purpose of modelling the soil acid–base status at the scale of the landscape because it assures that the same set of assumptions in throughfall are used for each application.

A Combined Soil-Atmosphere Model for Evaluating the Fate of Surface-Applied Pesticides. 1. Model Development and Verification

Volatilization of soil-applied pesticides to the atmosphere and their vapor transport in the air are principal processes leading to their widespread dispersion in the environment. A detailed one-dimensional nonisothermal model was developed to accommodate the impact of outdoors-dynamic behavior on the fate of surface-applied pesticides. The model includes the effects of temporal changes in weather conditions on the distribution of soil temperature and moisture in the soil profile and the latter two parameters' role on the volatilization and persistence of the applied pesticides. The model is solved numerically by the finite differences method. The performance of the numerical model was tested in two ways: by comparing its results with an analytic solution for a simplified case and by comparing predicted volatilization rates and soil residues of three pesticides (lindane, dieldrin, and trifluralin) with measured data. A good agreement was found between measured and simulated results. Hence, the model might be a useful tool for designing pesticide application and to explore their behavior under various soil and meteorological conditions. A sensitivity analysis of the model showed that volatilization of volatile pesticides such as lindane is most sensitive to the estimation of vapor pressure as a function of temperature, less sensible to adsorption coefficient, and insensitive to water solubility (within the range of published data) and decomposition coefficient.

A Combined Soil-Atmosphere Model for Evaluating the Fate of Surface-Applied Pesticides. 2. The Effect of Varying Environmental Conditions

Simulations using the one-dimensional nonisothermal model (Reichman et al. Environ Sci. Technol. 2000, 34, 1313−1320). this issue) for pesticides that have been applied to the soil surface revealed that diurnal variation of climatic factors, soil type (silty clay and sand), initial soil-moisture distribution, and pesticide type (parathion, dieldrin, and trifluralin) potentially have major influences on pesticide volatilization rates and persistence. The diurnal variation of water evaporation, which is closely related to the diurnal variation in solar radiation, has potentially significant effect on the diurnal variation of parathion volatility and mobility (low volatility and high mobility). However, the volatilization rates of low-water-soluble pesticides (e.g., trifluralin and dieldrin) are only slightly affected by water evaporation rate. Their migration downward via vapor-phase diffusion reduces their concentration in the soil surface layer and decreases their actual volatilization rates. The limiting...

Coupled soil-atmosphere modelling for soil evaporation

Traditional methods of evaluating evaporation provide an estimate of the maximum or potential rate of evaporation determined on the basis of climatic conditions. Methods such as these are appropriate for open water or fully saturated soil surfaces. Actual rates of evaporation from unsaturated soil surfaces are generally greatly reduced relative to the potential rate of evaporation. A theoretical model for predicting the rate of evaporation from soil surfaces is presented in this paper. The model is based on a system of equations for coupled heat and mass transfer in soil. Darcy's Law and Fick's Law are used to describe the flow of liquid water and water vapour, respectively. Heat flow is evaluated on the basis of conductive and latent heat fluxes. Dalton's Law is used to calculate the rate of soil evaporation to the atmosphere based on the suction at the soil surface. The soil–atmosphere model was used to predict soil evaporation rates, water-content profiles, and temperature profiles for a controlled column evaporation test over a 42 day period. The values computed by the soil–atmosphere model agreed well with the values measured for two columns of Beaver Creek sand in the evaporation test. Key words : modelling, evaporation, unsaturated, soil surfaces.

A One-Dimensional Interactive Soil-Atmosphere Model for Testing Formulations of Surface Hydrology

A model representing a soil-atmosphere column in a GCM is developed for off-line testing of GCM soil hydrology parameterizations. Repeating three representative GCM sensitivity experiments with this one-dimensional model demonstrates that, to first order, the model reproduces a GCM's sensitivity to imposed changes in parameterization and therefore captures the essential physics of the GCM. The experiments also show that by allowing feedback between the soil and atmosphere, the model improves on off-line tests that rely on prescribed precipitation, radiation, and other surface forcing.

Triggering of atmospheric circulations by moisture inhomogeneities of the earth's surface

A two-dimensional mesoscale soil-atmosphere model is used to simulate the triggering of atmospheric convection by horizontally varying soil water content. The variation is periodic with a wavelength λ between 4 and 40 km, which is considered a realistic scale for the variation of land surface characteristics. Three stages of convection can be clearly discerned: a short initial stage when convection sets in and where the size of the conective cells is determined by λ, a mature stage with well developed cells whose size is still determined by λ, and a decay/transformation stage, characterized by the formation of narrow regions of strong updrafts and wide regions of moderate downdrafts, independent of λ. Parameters relevant for the transition are given, and the importance of the feedback between soil and atmosphere is demonstrated. The dependence of convective parameters, e.g., height of the convective layer, vertical velocity and fluxes of heat and moisture on λ is investigated. The calculations of the mature stage are compared with the predictions of a linear model.