Simulated Soil Temperature Research Articles

Evaluation of the North American Land Data Assimilation System over the southern Great Plains during the warm season

North American Land Data Assimilation System (NLDAS) land surface models have been run for a retrospective period forced by atmospheric observations from the Eta analysis and actual precipitation and downward solar radiation to calculate land hydrology. We evaluated these simulations using in situ observations over the southern Great Plains for the periods of May–September of 1998 and 1999 by comparing the model outputs with surface latent, sensible, and ground heat fluxes at 24 Atmospheric Radiation Measurement/Cloud and Radiation Testbed stations and with soil temperature and soil moisture observations at 72 Oklahoma Mesonet stations. The standard NLDAS models do a fairly good job but with differences in the surface energy partition and in soil moisture between models and observations and among models during the summer, while they agree quite well on the soil temperature simulations. To investigate why, we performed a series of experiments accounting for differences between model‐specified soil types and vegetation and those observed at the stations, and differences in model treatment of different soil types, vegetation properties, canopy resistance, soil column depth, rooting depth, root density, snow‐free albedo, infiltration, aerodynamic resistance, and soil thermal diffusivity. The diagnosis and model enhancements demonstrate how the models can be improved so that they can be used in actual data assimilation mode.

Validation of the North American Land Data Assimilation System (NLDAS) retrospective forcing over the southern Great Plains

Atmospheric forcing used by land surface models is a critical component of the North American Land Data Assimilation System (NLDAS) and its quality crucially affects the final product of NLDAS and our work on model improvement. A three‐year (September 1996–September 1999) retrospective forcing data set was created from the Eta Data Assimilation System and observations and used to run the NLDAS land surface models for this period. We compared gridded NLDAS forcing with station observations obtained from networks including the Oklahoma Mesonet and Atmospheric Radiation Measurement/Cloud and Radiation Testbed at the southern Great Plains. Differences in all forcing variables except precipitation between the NLDAS forcing data set and station observations are small at all timescales. While precipitation data do not agree very well at an hourly timescale, they do agree better at longer timescales because of the way NLDAS precipitation forcing is generated. A small high bias in downward solar radiation and a low bias in downward longwave radiation exist in the retrospective forcing. To investigate the impact of these differences on land surface modeling we compared two sets of model simulations, one forced by the standard NLDAS product and one with station‐observed meteorology. The differences in the resulting simulations of soil moisture and soil temperature for each model were small, much smaller than the differences between the models and between the models and observations. This indicates that NLDAS retrospective forcing provides an excellent state‐of‐the‐art data set for land surface modeling, at least over the southern Great Plains region.

Effects of Frozen Soil on Soil Temperature, Spring Infiltration, and Runoff: Results from the PILPS 2(d) Experiment at Valdai, Russia

The Project for Intercomparison of Land-Surface Parameterization Schemes phase 2(d) experiment at Valdai, Russia, offers a unique opportunity to evaluate land surface schemes, especially snow and frozen soil parameterizations. Here, the ability of the 21 schemes that participated in the experiment to correctly simulate the thermal and hydrological properties of the soil on several different timescales was examined. Using observed vertical profiles of soil temperature and soil moisture, the impact of frozen soil schemes in the land surface models on the soil temperature and soil moisture simulations was evaluated. It was found that when soil-water freezing is explicitly included in a model, it improves the simulation of soil temperature and its variability at seasonal and interannual scales. Although change of thermal conductivity of the soil also affects soil temperature simulation, this effect is rather weak. The impact of frozen soil on soil moisture is inconclusive in this experiment due to the particular climate at Valdai, where the top 1 m of soil is very close to saturation during winter and the range for soil moisture changes at the time of snowmelt is very limited. The results also imply that inclusion of explicit snow processes in the models would contribute to substantially improved simulations. More sophisticated snow models based on snow physics tend to produce better snow simulations, especially of snow ablation. Hysteresis of snow-cover fraction as a function of snow depth is observed at the catchment but not in any of the models.

Effects of crop residue cover and architecture on heat and water transfer at the soil surface

Different residue types and standing stubble versus distributed flat residues affect heat and water transfer at the soil surface to varying degrees. Understanding the effects of various residue configurations can assist in better residue management decisions, but this is complex due to various interacting influences. Therefore, modeling the effects of crop residues on heat and water movement can be an effective tool to assess the benefits of differing residues types and architectures for various climates. The purpose of this study was to test the ability of the Simultaneous Heat And Water (SHAW) model for simulating the effects of residue type and architecture on heat and water transfer at the surface and to evaluate the impacts of differing residue types and architectures on heat and water transfer in significantly different climates. The model was tested on bare tilled soils and corn, wheat and millet residues having varying amounts of standing and distributed flat residues for three separate locations: Ames, IA, Akron, CO and Pullman, WA. Modifications to the model were necessary to correctly simulate the effect of wind on convective transfer through a flat corn residue layer. Model efficiencies for simulated soil temperature approached or exceeded 0.90 for nearly all residue treatments and locations. The root mean square deviation for simulated water content compared to measured values was typically around 0.04 m 3 m −3. Satisfied that the model could reasonably simulate the effect of residue type and architecture, the model was applied to simulate the effects of differing residue architectures to 30 years of generated weather conditions for four diverse climate stations: Boise, ID; Spokane, WA; Des Moines, IA; Minneapolis, MN. Simulated frost depths for bare and standing residues were typically deeper than for flat residues. Bare soil had the highest evaporation at all sites, and flat wheat residue generally had the lowest evaporation. The wetter climates (Des Moines and Minneapolis) tended to favor flat residues for reducing evaporation more so than the drier climates. Near-surface soil temperature under standing residues warmed to 5 °C in the spring by as much as 5–9 days earlier compared to bare and flat residue cover depending on location, which can have important ramifications for early seedling germination and plant establishment.

Boreal Forest Surface Parameterization in the ECMWF Model—1D Test with NOPEX Long-Term Data

The objective of the present study was to assess the performance and recent improvements of the land surface scheme used operationally in the European Centre for Medium-Range Weather Forecasts (ECMWF) in a Scandinavian boreal forest climate/ecosystem. The previous (the 1999 scheme of P. Viterbo and A. K. Betts) and the new (Tiled ECMWF Surface Scheme for Exchange Processes over Land, TESSEL) surface schemes were validated by single-column runs against data from NOPEX (Northern Hemisphere Climate-Processes Land-Surface Experiment). Driving and validation datasets were prepared for a 3-yr period (1994-96). The new surface scheme, with separate surface energy balances for subgrid fractions (tiling), improved predictions of seasonal as well as diurnal variation in surface energy fluxes in comparison with the old scheme. Simulated wintertime evaporation improved significantly as a consequence of the introduced additional aerodynamic resistance for evaporation from snow lying under high vegetation. Simulated springtime evaporation also improved because the limitation of transpiration in frozen soils was now accounted for. However, downward sensible heat flux was still underestimated during winter, especially at nighttime, whereas soil temperatures were underestimated in winter and overestimated in summer. The new scheme also underestimated evaporation during dry periods in summer, whereas soil moisture was overestimated. Sensitivity tests showed that further improvements of simulated surface heat fluxes and soil temperatures could be obtained by calibration of parameters governing the coupling between the surface and the atmosphere and the ground heat flux, and parameters governing the water uptake by the vegetation. Model performance also improved when the seasonal variation in vegetation properties was included.

Parameterisation, evaluation and comparison of pesticide leaching models to data from a Bologna field site, Italy.

Effective prediction of pesticide fate using mathematical models requires good process descriptions in the models and good choice of parameter values by the user. This paper examines the ability of seven pesticide leaching models (LEACHP, MACRO, PELMO, PESTLA, PLM, PRZM and VARLEACH) to describe an arable field environment where sunflowers are grown in the Po Valley, northern Italy. Two pesticides were considered, aclonifen and ethoprophos. The models were evaluated in terms of their ability to reproduce field data of soil water content and pesticide residues in the soil and ground water. The evaluation was based on a combination of calibrated and uncalibrated runs. The results from the models were compared with each other to explore the differences between the models. The models varied in their ability to predict soil water content in the summer: the capacity models PRZM, PELMO and VARLEACH predicted less drying than MACRO, PESTLA, PLM and LEACHP. The models varied in their ability to simulate the persistence of the pesticides in the soil. Differences in the simulated pesticide degradation rate were observed between the models, due to variations in the simulated soil water content and soil temperature, and also differences in the equation linking degradation rate to soil water content. There were large differences among the predictions of the models for the mean leaching depth of ethoprophos. PRZM, PELMO, PESTLA and LEACHP all showed similar mean leaching depth to each other, whereas VARLEACH predicted lower ethoprophos mobility and PLM and MACRO predicted greater mobility. All the models overpredicted dispersion of ethoprophos through the soil profile, as compared to the field data. None of the models was able to simulate the field data of rapid leaching of pesticide to ground water except PLM after calibration of the percentage of macropores in the mobile pore space. More work is required in the parameterisation of macropore flow for those models that include this process.

Numerical solution of a complete surface energy balance model for simulation of heat fluxes and surface temperature under bare soil environment

Surface energy balance model is an essential approach for heat flux and evaporation estimation in applied meteorology and hydrology. Due to the complexity of soil–air interface system, the model has been simplified for different purposes in many researches. A complete model with full description of its complex factor relationships and its numerical solution has not been yet implemented in practical use. This paper presents a complete surface energy balance model with its inner relations cited from different researches. The model couples soil temperature change simultaneously with soil moisture movement, which makes the solution of the model uneasy. A detailed methodology of numerical approximation to the complete model is presented in the study for practical use. Soil heat and latent heat fluxes in the model are determined according to both soil temperature change and soil moisture movement, which are described as two differential equations. Crank–Nicolson implicit method is used to expand the differential equations into two sets of simultaneous linear equations, which are then solved by applying Gauss's elimination method. Latent heat flux is determined at the balance when evaporation from the surface is equal to the soil water loss. And surface temperature is estimated as the heat fluxes of the surface reaching the status of balance. The iterative computation of Newton–Raphson method is used to approximate latent heat flux and surface temperature from the balances. Based on this complexity of the model's relationships, a detailed computation procedure of the model is proposed. The methodology has been validated through application to south Israeli desert for heat flux and surface temperature estimation. A good matching of the simulated soil temperature to the measured one proves the validity of the model and method used for its numerical solution.

Error analysis of soil temperature simulations using measured and estimated hourly weather data with 2DSOIL

Many crop simulation models use 1-h time steps for atmospheric, soil and plant processes but often meteorological data are only available as daily summaries. The objective of this study was to investigate how errors in estimation of hourly values of solar radiation and air temperature affect errors in simulation of soil temperature using the model 2DSOIL. 2DSOIL is a two-dimensional finite element model that simulates water flow, chemical, water and solute uptake by plant roots, chemical equilibria processes, and gas and heat transport in soil. The standard deviations of the differences between hourly estimated air temperatures were about 2°C and 85 W m −2 for solar radiation. The mean difference in simulated and measured soil temperatures using measured hourly weather data for all depths at both sites was less than 1°C and standard deviations were about 1–3°C indicating low bias. The range of errors was highest in the surface soils when the soil was wetted after rainfall. Relative to simulated soil temperatures using measured hourly data, simulated soil temperatures using estimated data were, on average over all depths, 2°C lower and standard deviations ranged from 2 to 3°C. The errors were similar over all depths. Use of estimated hourly air temperature and radiation generally resulted in underpredictions of soil temperature by 2–3°C and increased error. Also maximum daily soil temperatures were underestimated.

Modeling soil thermal and carbon dynamics of a fire chronosequence in interior Alaska

In this study, the dynamics of soil thermal, hydrologic, and ecosystem processes were coupled to project how the carbon budgets of boreal forests will respond to changes in atmospheric CO2, climate, and fire disturbance. The ability of the model to simulate gross primary production and ecosystem respiration was verified for a mature black spruce ecosystem in Canada, the age‐dependent pattern of the simulated vegetation carbon was verified with inventory data on aboveground growth of Alaskan black spruce forests, and the model was applied to a postfire chronosequence in interior Alaska. The comparison between the simulated soil temperature and field‐based estimates during the growing season (May to September) of 1997 revealed that the model was able to accurately simulate monthly temperatures at 10 cm (R> 0.93) for control and burned stands of the fire chronosequence. Similarly, the simulated and field‐based estimates of soil respiration for control and burned stands were correlated (R= 0.84 and 0.74 for control and burned stands, respectively). The simulated and observed decadal to century‐scale dynamics of soil temperature and carbon dynamics, which are represented by mean monthly values of these variables during the growing season, were correlated among stands (R= 0.93 and 0.71 for soil temperature at 20‐ and 10‐cm depths,R= 0.95 and 0.91 for soil respiration and soil carbon, respectively). Sensitivity analyses indicate that along with differences in fire and climate history a number of other factors influence the response of carbon dynamics to fire disturbance. These factors include nitrogen fixation, the growth of moss, changes in the depth of the organic layer, soil drainage, and fire severity.

Growth, carbohydrate and nutrient allocation of Scots pine seedlings after exposure to simulated low soil temperature in spring

The effects of sustained low soil temperature on growth and allocation of biomass and carbohydrates in Scots pine (Pinus sylvestris L.) were studied by exposing 1-year-old seedlings to soil temperatures of 5 °C for 0, 3, 6 or 9 weeks and subsequently for 9 weeks at 13 °C. Growth at 5 °C soil temperature at the beginning of the growing season reduced the height of new shoots but the length of the cold soil period did not affect the final height. Some new root tips emerged during the 5 °C soil temperature period. Prolific root growth did not start until the soil temperature was increased from 5 to 13 °C, but new root growth was scarce during the first 3 weeks even at 13 °C, a clearly more favourable soil temperature than 5 °C. Seedlings exposed to a temperature exceeding 5 °C over any 3-week period during the first 9 weeks had above- and below-ground biomasses that were equivalent, whereas continual exposure to 5 °C reduced shoot and root growth. The above-ground biomass of the seedlings did not increase any more after Week 12, nor did the below-ground biomass after Week 15. Biomass allocation among the different parts of the seedlings was not greatly affected by the length of the cold soil period. Our results indicate that the accumulation of above-ground biomass is mainly dependent on the air temperature and not soil temperature. Element allocation followed the pattern of biomass allocation, except for N, which increased in the above-ground parts throughout the experiment, and Fe, which had already accumulated during the first 3 weeks. The seedlings grown for a longer time at low soil temperatures contained lower amounts of starch but similar amounts of soluble sugars throughout the experiment.

Incorporation of a permafrost model into a large‐scale ecosystem model: Evaluation of temporal and spatial scaling issues in simulating soil thermal dynamics

This study evaluated whether a model of permafrost dynamics with a 0.5‐day resolution internal time step that is driven by monthly climate inputs is adequate for representing the soil thermal dynamics in a large‐scale ecosystem model. An extant version of the Goodrich model was modified to develop a soil thermal model (STM) with the capability to operate with either 0.5‐hour or 0.5‐day internal time steps and to be driven with either daily or monthly input data. The choice of internal time step had little effect on the simulation of soil thermal dynamics of a black spruce site in Alaska. The use of monthly climate inputs to drive the model resulted in an error of less than 1°C in the upper organic soil layer and in an accurate simulation of seasonal active layer dynamics. Uncertainty analyses of the STM driven with monthly climate inputs identified that soil temperature estimates of the upper organic layer were most sensitive to variability in parameters that described snow thermal conductivity, moss thickness, and moss thermal conductivity. The STM was coupled to the Terrestrial Ecosystem Model (TEM), and the performance of the coupled model was verified for the simulation of soil temperatures in applications to a black spruce site in Canada and to white spruce, aspen, and tundra sites in Alaska. A 1°C error in the temperature of the upper organic soil layer had little influence on the carbon dynamics simulated for the black spruce site in Canada. Application of the model across the range of black spruce ecosystems in North America demonstrated that the STM‐TEM has the capability to operate over temporal and spatial domains that consider substantial variation in surface climate given that spatial variability in key structural characteristics and physical properties of the soil thermal regime are described.

Test of a simple two-layer parameterisation to simulate the energy balance and temperature of a snow pack

Reasonably simple yet realistic modelling schemes simulating the heat and mass balance within a snow pack are required to provide the necessary boundary conditions for meteorological and hydrological models. An improvement to a one-layer snow energy balance model (UEB, Tarboton etal., 1995) is proposed to better simulate snow surface and snow pack temperatures and, as a result, snowmelt. The modified scheme is assessed against measured snow data from the WINTEX field campaign during spring 1997 in northern Finland, and compared with results from a complex multi-layer snow energy balance scheme. The results show that separation of a one-layer representation into two snow layers and a soil layer enables a more realistic simulation of soil and snow temperatures as well as of the snow surface temperature. The two-layer and the multi-layer snow schemes yielded comparable results for internal processes in the snow whenever the simulation was carried out under similar boundary forcing. The modified scheme is proposed for use as a sub-scheme in meteorological or hydrological models, or as a tool for simulating spatially-variable snowmelt and the surface energy balance during seasonal snow cover.

Treatment of frozen soil and snow cover in the land surface model SEWAB

The land surface model SEWAB (Surface Energy and Water Balance) is designed to be coupled to both, atmospheric and hydrological models. Its application in mid and high latitudes requires the inclusion of freezing and thawing processes within the soil and the accumulation and ablation of a snow cover. These winter processes are parameterised with a minimum number of empirical formulations in order to assure reasonable computation times for an application in climate and sensitivity studies yet accounting for all important processes. Meteorological forcing data and measurements of snow depth, soil temperature and liquid soil water content at two locations in the mid-west of North America are used to test the model. Generally the simulated snow depth matches the measurements, remaining differences in snow depth can be explained by uncertainties in snow density, blowing snow and errors in precipitation measurements. The simulated soil temperature and liquid soil water content compare well with the measurements, showing the isolating effect of the snow cover.

Simulation of Pesticide Persistence in the Field on the Basis of Laboratory Data—A Review

AbstractSimulations of pesticide fate in soils are often based on persistence models developed nearly 30 years ago. These models predict dissipation in the field on a daily basis by correcting laboratory degradation half‐lives for actual soil temperature and moisture content. They have been extensively applied, but to date no attempt has been made to evaluate existing studies in a consistent, quantitative way. This paper reviews 178 studies comparing pesticide soil residues measured in the field with those simulated by persistence models. The simulated percentage of initial pesticide concentration at the time of 50% measured loss was taken as a common criterion for model performance. The models showed an overall tendency to overestimate persistence. Simulated values ranged from 12 to 96% of initial pesticide concentrations with a median of 60%. Simulated soil residues overestimated the target value (50% of initial) by more than a factor of 1.25 in 44% of the cases. An underestimation by more than a factor of 1.25 was found in only 17% of the experiments. Discrepancies between simulated and observed data are attributed to difficulties in characterizing pesticide behavior under outdoor conditions using laboratory studies. These arise because of differences in soil conditions between the laboratory and the field and the spatial and temporal variability of degradation. Other possible causes include losses in the field by processes other than degradation, deviations of degradation from first‐order kinetics, discrepancies between simulated and actual soil temperature and moisture content, and the lack of soil‐specific degradation parameters. Implications for modeling of pesticide behavior within regulatory risk assessments are discussed.

DEVELOPMENT OF THE ROOT ZONE WATER QUALITY MODEL (RZWQM) FOR OVER-WINTER CONDITIONS

Soil temperature and water conditions through the winter and early spring drive many important physical,chemical and biological processes. Impacts of management practices on these complex processes are often difficult topredict. The primary objective of this study was to incorporate routines for snow, soil heat, and soil freezing from theSimultaneous Heat and Water (SHAW) model into the process based RZWQM to extend its applicability to winterconditions. Routines from SHAW for simulating transfer through flat and standing residue layers were also included. TheRZWQMs solution of the Richards equation was retained, making it necessary to decouple the SHAW modelssimultaneous solution of the heat and water equations. The modified RZWQM was applied to varying tillage and residueconditions using data from Pullman, Washington, and Akron, Colorado, and compared to the original SHAW model.Statistical comparisons indicated that the two models simulated soil temperature similarly for most plots, showingsuccessful implementation of the SHAW routines. Differences in simulated soil temperatures and ice contents between thetwo models were related to differences in computing soil water transfer and solution of Richards equation. Modelefficiency for soil temperature simulated by the modified RZWQM, defined as the fraction of variability in measuredtemperature accounted for by the model, ranged from 0.71 to 0.92 within the top 25-cm at the Pullman site; simulatedsnow and soil frost depths were similar to previous simulations from the SHAW model. Model efficiency for simulatedtemperature at the Akron sites ranged from 0.87 to 0.98. Dynamic response of soil water potential was simulatedreasonably well, with model efficiencies ranging from 0.61 to 0.86 for the Akron site. This modified version of theRZWQM, that includes frozen soil and boundary conditions representative of varying surface conditions, makes the modelmore responsive to management of soil and water resources in northern latitudes.

A simple model for simulation of water content, soil frost, and soil temperatures in boreal mixed mires

In this paper we present a model that can reconstruct water table position and soil temperature profiles to 3 m depth in boreal mixed mire systems using the readily available climate data on air temperature and precipitation as driving variables. The model simulates complete, multiple annual cycles including winter conditions and freeze‐thaw processes. The major requisite for an accurate description of the soil heat flux in a mire is an accurate description of the water content of the profile because of the high porosity of the soil and the thermal properties of water. The soil moisture profile in this model is described as a function of water table position derived from empirical published data of soil moisture profile measurements at different water table positions. The parameters of the model were set and tested for a lawn community, one of the most dominant plant communities occurring in boreal mixed mires. The model is optimized for the period 1995–1997 at the mixed mire Degerö Stormyr and was validated for the period 1997–1998 at the same location and for 1991–1993 at Storåmyran, 60 km away. The mean deviation of simulated to measured soil temperature from 10 cm to 3 m depth in the validation data sets was <1.6°C with a maximal standard deviation of 1.8°C. A response analysis of the amount of winter precipitation showed the influence of snow cover depth on soil frost fluctuations. A simulated precipitation corresponding to 25% of the measured precipitation during winter 1995–1996, with all other factors unchanged, prolonged the period of frozen ground in the model from June 8 to August 1. With a doubling of the winter precipitation the modeled period of frozen ground lasted only until May 6.

Comparison of Different Models to Simulate Soil Temperature and Moisture Effects on Nitrogen Mineralization in the Soil

The rate of mineralization of organic nitrogen (N) in soils depends on environmental factors, specially temperature and water content. In this paper, different models that describe temperature and water content effects on mineralization are examined and the values of the factors used in the different models are compared. The results of mineralization simulations, using the different models at different levels of water content and temperature, are compared with experimental field data from the literature. The results show that the principal differences are found at temperatures greater than 25°C and at water content levels near saturation and near permanent wilting point. The different models were used for an estimation of net mineralized N under field conditions in a soil with ryegrass by using a deterministic model of water and N transport in the soil. The results confirm the differences of moisture and temperature effects on mineralization when the soil became very dry and wet during the rainy months. Vergleich verschiedener Modelle über den Einfluss der Temperatur und der Boden- feuchte auf die Stickstoff-Mineralisierung im Boden Die Stickstoff(N)-Mineralisierungsrate im Boden wird durch Umweltfaktoren wie Bodentemperatur und Bodenwassergehalt beeinflusst. In dieser Arbeit werden verschiedene Modelle überprüft und verglichen, die den Einfluss der Temperatur und der Bodenfeuchte auf die N-Mineralisierung beschreiben. Die Ergebnisse von Simulationen der N-Mineralisierung mit verschiedenen Modellen bei unterschiedlichen Bodenwassergehalten und Temperaturen werden mit Literaturdaten von Freilanduntersuchungen verglichen. Diese Vergleiche zeigen, dass die Simulationen bei Bodentemperaturen > 25°C sowie bei Wassergehalten nahe dem permanenten Welkepunkt bzw. der Sättigung zu deutlich unterschiedlichen Ergebnissen führen. Ausgehend von der deterministischen Model-lierung des Wasser- und N-Transports im Boden wurde mit verschiedenen Modellen die N-Nettomineralisierung unter Freilandbedingungen für einen Boden mit Weidelgrasanbau abgeschätzt. Die Ergebnisse bestätigen, dass die Modelle speziell bei starker Austrocknung sowie bei weitgehender Wassersättigung den Einfluss der Bodentemperatur sowie der Bodenfeuchte unterschiedlich bewerten.

A parameterization of snowpack and frozen ground intended for NCEP weather and climate models

Extensions to the land surface scheme (LSS) in the National Centers for Environmental Prediction, regional, coupled, land‐atmosphere weather prediction model, known as the mesoscale Eta model, are proposed and tested off‐line in uncoupled mode to account for seasonal freezing and thawing of soils and snow‐accumulation‐ablation processes. An original model assumption that there is no significant heat transfer during redistribution of liquid water was relaxed by including a source/sink term in the heat transfer equation to account for latent heat during phase transitions of soil moisture. The parameterization uses the layer‐integrated form of heat and water diffusion equations adopted by the original Eta‐LSS. Therefore it simulates the total ice content of each selected soil layer. Infiltration reduction under frozen ground conditions was estimated by probabilistic averaging of spatially variable ice content of the soil profile. Off‐line uncoupled tests of the new and original Eta‐LSS were performed using experimental data from Rosemount, Minnesota. Simulated soil temperature and unfrozen water content matched observed data reasonably well. Neglecting frozen ground processes leads to significant underestimation/overestimation of soil temperature during soil freezing/thawing periods and underestimates total soil moisture content after extensive periods of soil freezing.

Soil Warming and Carbon Loss from a Lake States Spodosol

AbstractElevated soil temperatures may increase C loss from soils by accelerating microbial respiration and dissolved organic C leaching. We evaluated the effect of elevated soil temperatures on C losses from a forest Spodosol by incubating soil cores from surface (Oa + A + E) and subsurface (Bhs) horizons at two seasonal temperature regimes. One regime simulated the normal course of soil temperatures in northern lower Michigan, and the other simulated soil temperatures representing an amount of warming that might occur under some global warming theory calculations. We measured the amounts of CO2‐C respired and dissolved organic C leached from the soil cores during a 33‐wk period. Microbial respiration rates, after adjustment for variation in initial rates, were significantly increased by soil warming and were greater in surface than in subsurface horizons. Warming significantly increased cumulative C respired, with greater losses from surface soils (≥50 mg C g‐1 C) as compared with subsurface soils (≤25 mg C g‐1 C). Mean quantities of dissolved organic C leached, ranging from 2.3 to 3.2 mg C g‐1 C, did not differ significantly by soil horizon or temperature regime. Increased microbial respiration in surface soil horizons was the process most responsive to soil warming in the Spodosol samples we examined. Whether this is a short‐term effect that would disappear once pools of labile C are exhausted, or represents a long‐term response to soil warming, remains uncertain.

Diurnal fluctuations of water and heat flows in a bare soil

The complexity of coupled transport of heat and moisture at the soil surface necessitates a combination of field and numerical experiments to evaluate the interactions between liquid and vapor phase flow. The near‐surface moisture and temperature conditions of a bare soil were investigated experimentally and by using the SOIL model to assess the importance of water vapor flow. During a 1‐month period in early fall, intensive measurements of water content, water tension, and temperature were made in a bare soil plot. Soil thermal conductivity, measured on soil cores extracted for laboratory analysis, was found to agree with estimates based on the Kersten equation. Simulated water content and soil temperature agreed well with observations. Modeled soil vapor flow was significant compared to liquid flow only during the initial dry days when the inclusion of vapor flow improved the predicted diurnal variation in water tension. Model predictions were sensitive to an accurate representation of the soil surface energy balance, including the consideration of steep gradients in tension near the soil surface, and to the enhancement of vapor flow.