Simultaneous Heat And Water Model Research Articles

Simulation of Soil Temperature under Plateau Zokor's (Eospalax baileyi) Disturbance in the Qinghai Lake Watershed, Northeast Qinghai-Tibet Plateau.

The soil temperature is a key factor affecting the fragile terrestrial ecosystems on the Qinghai-Tibet Plateau, and has been remarkably altered by the soil mammal's disturbance. This study first analyzed the soil temperature variation in grassland, mound, and bald patch under the disturbance of plateau zokor (Eospalax baileyi) from October 2018 to July 2020 in the Qinghai Lake watershed. Then, the SHAW (simultaneous heat and water) model was used to simulate the soil temperature change of three land surface types, and the sensitivity of soil temperature to environmental parameters before and after the disturbance was explored. The results showed the following: (1) The daily range of soil temperature was mound > bald patch > grassland, which became smaller as the depth increased, due to the co-influence of vegetation coverage and soil bulk density. There was an obvious hysteresis of soil heat transfer for grassland, as compared with mound and bald patch, especially at 5 and 15 cm depths. (2) The SHAW model was applicable for the simulation of soil temperature under the plateau zokor's disturbance, especially during the growing season, and had better simulation accuracy for deep soil. (3) Air-entry potential and pore-size distribution index obviously affected soil temperature change, because of the change in root system and soil pores under the plateau zokor's disturbance. With the evolution of disturbance process, the response of soil temperature to the leaf area index weakened gradually, owing to the different duration of disturbance and restoration. In general, the plateau zokor's disturbance alters the soil properties and vegetation characteristics, and further, distinctly affects heat transfer and soil temperature.

Convective heat transfer of spring meltwater accelerates active layer phase change in Tibet permafrost areas

Abstract. Convective heat transfer (CHT) is one of the important processes that control the near-ground surface heat transfer in permafrost areas. However, this process has often not been considered in most permafrost studies, and its influence on freezing–thawing processes in the active layer lacks quantitative investigation. The Simultaneous Heat and Water (SHAW) model, one of the few land surface models in which the CHT process is well incorporated into the soil heat–mass transport processes, was applied in this study to investigate the impacts of CHT on the thermal dynamics of the active layer at the Tanggula station, a typical permafrost site on the eastern Qinghai–Tibet Plateau with abundant meteorological and soil temperature and soil moisture observation data. A control experiment was carried out to quantify the changes in active layer temperature affected by vertical advection of liquid water. Three experimental setups were used: (1) the original SHAW model with full consideration of CHT, (2) a modified SHAW model that ignores CHT due to infiltration from the surface, and (3) a modified SHAW model that completely ignores CHT processes in the system. The results show that the CHT events occurred mainly during thaw periods in melted shallow (0–0.2 m) and intermediate (0.4–1.3 m) soil depths, and their impacts on soil temperature at shallow depths were significantly greater during spring melting periods than summer. The impact was minimal during freeze periods and in deep soil layers. During thaw periods, temperatures at the shallow and intermediate soil depths simulated under the scenario considering CHT were on average about 0.9 and 0.4 ∘C higher, respectively, than under the scenarios ignoring CHT. The ending dates of the zero-curtain effect were substantially advanced when CHT was considered due to its heating effect. However, the opposite cooling effect was also present but not as frequently as heating due to upward liquid fluxes and thermal differences between soil layers. In some periods, the advection flow from the cold layer reduced the shallow and intermediate depth temperatures by an average of about −1.0 and −0.4 ∘C, respectively. The overall annual effect of CHT due to liquid flux is to increase soil temperature in the active layer and favor thawing of frozen ground at the study site.

Promise and pitfalls of modeling grassland soil moisture in a free-air CO2 enrichment experiment (BioCON) using the SHAW model

Free-air carbon dioxide (CO2) enrichment (FACE) experiments provide an opportunity to test models of heat and water flow under novel, controlled situations and eventually allow use of these models for hypothesis evaluation. This study assesses whether the United States Department of Agriculture SHAW (Simultaneous Heat and Water) numerical model of vertical one-dimensional soil water flow across the soil-plant-atmosphere continuum is able to adequately represent and explain the effects of increasing atmospheric CO2 on soil moisture dynamics in temperate grasslands. Observations in a FACE experiment, the BioCON (Biodiversity, CO2, and Nitrogen) experiment, in Minnesota, USA, were compared with results of vertical soil moisture distribution. Three scenarios represented by different plots were assessed: bare, vegetated with ambient CO2, and similarly vegetated with high CO2. From the simulations, the bare plot soil was generally the wettest, followed by a drier high-CO2 vegetated plot, and the ambient CO2 plot was the driest. The SHAW simulations adequately reproduced the expected behavior and showed that vegetation and atmospheric CO2 concentration significantly affected soil moisture dynamics. The differences in modeled soil moisture amongst the plots were largely due to transpiration, which was low with high CO2. However, the modeled soil moisture only modestly reproduced the observations. Thus, while SHAW is able to replicate and help broadly explain soil moisture dynamics in a FACE experiment, its application for point- and time-specific simulations of soil moisture needs further scrutiny. The typical design of a FACE experiment makes the experimental observations challenging to model with a one-dimensional distributed model. In addition, FACE instrumentation and monitoring will need improvement in order to be a useful platform for robust model testing. Only after this can we recommend that models such as SHAW are adequate for process interpretation of datasets from FACE experiments or for hypothesis testing.

Ecohydrological modelling in a deciduous boreal forest: Model evaluation for application in non‐stationary climates

AbstractSoil moisture is an important driver of growth in boreal Alaska, but estimating soil hydraulic parameters can be challenging in this data‐sparse region. Parameter estimation is further complicated in regions with rapidly warming climate, where there is a need to minimize model error dependence on interannual climate variations. To better identify soil hydraulic parameters and quantify energy and water balance and soil moisture dynamics, we applied the physically based, one‐dimensional ecohydrological Simultaneous Heat and Water (SHAW) model, loosely coupled with the Geophysical Institute of Permafrost Laboratory (GIPL) model, to an upland deciduous forest stand in interior Alaska over a 13‐year period. Using a Generalized Likelihood Uncertainty Estimation parameterisation, SHAW reproduced interannual and vertical spatial variability of soil moisture during a five‐year validation period quite well, with root mean squared error (RMSE) of volumetric water content at 0.5 m as low as 0.020 cm3/cm3. Many parameter sets reproduced reasonable soil moisture dynamics, suggesting considerable equifinality. Model performance generally declined in the eight‐year validation period, indicating some overfitting and demonstrating the importance of interannual variability in model evaluation. We compared the performance of parameter sets selected based on traditional performance measures such as the RMSE that minimize error in soil moisture simulation, with one that is designed to minimize the dependence of model error on interannual climate variability using a new diagnostic approach we call CSMP, which stands for Climate Sensitivity of Model Performance. Use of the CSMP approach moderately decreases traditional model performance but may be more suitable for climate change applications, for which it is important that model error is independent from climate variability. These findings illustrate (1) that the SHAW model, coupled with GIPL, can adequately simulate soil moisture dynamics in this boreal deciduous region, (2) the importance of interannual variability in model parameterisation, and (3) a novel objective function for parameter selection to improve applicability in non‐stationary climates.

Evaluation of 14 frozen soil thermal conductivity models with observations and SHAW model simulations

Frozen soil thermal conductivity (FSTC, λeff) is a critical thermophysical property that is required for a variety of science and engineering applications. Measurements of λeff in frozen soils are prone to errors because the currently available thermal methods result in phase change (i.e., thawing and refreezing of ice) that affects the estimated λeff, especially near the freezing point of soil water (e.g., −4 to 0 °C) where rapid phase change occurs. In addition, measured λeff data are few compared to other physical properties. Therefore, many FSTC algorithms have been developed and a few of them have been incorporated in numerical simulation programs for calculating λeff. However, large discrepancies between simulated and observed soil thermal regimes have been reported. Previous studies either evaluated the performance of a few FSTC algorithms with limited λeff or simply compared the performance of the algorithms in numerical simulation programs. No study has been performed to systematically assess the performance of the FSTC algorithms included in numerical simulation programs with both observations and model simulations. In this study, 14 FSTC algorithms incorporated in various numerical simulation programs were evaluated with a compiled dataset consisting of 331 λeff measurements on 27 soils from seven studies made at temperatures on or below −4 °C. The Becker 1992 algorithm provided the best estimates of the λeff measurements, but the accuracy of the estimates was not good (i.e., RMSE = 0.46 W m−1 °C−1, Bias = -0.04 W m−1 °C−1 and NSE = 0.51). These FSTC algorithms were also incorporated in the Simultaneous Heat and Water (SHAW) model to compare their effects on the simulating soil temperature and water content at two field sites with contrasting soil textures in USA. The simulation results showed that the average bias of simulated and observed soil temperature for all depths ranged from −2.2 to 2.8 °C and the average differences of liquid water content ranged from −0.08 to 0.1 cm3 cm−3. Generally no FSTC algorithm combined with the SHAW model satisfactorily estimated the dynamic soil thermal regime. Perspectives on future studies are discussed.

Simulation of Soil Freezing and Thawing for Different Groundwater Table Depths

Core Ideas The SHAW model was used to simulate the freeze–thaw process during freeze–thaw periods. It revealed the effects of soil texture and groundwater table depth on soil freezing and thawing. The frost depth and accumulated negative soil surface temperature relationship was determined. During freeze–thaw periods, the transformation between phreatic water and soil water will change the soil hydrothermal properties and affect the soil freezing and thawing in shallow groundwater areas. The purpose of this study was to determine the effect of four different groundwater table depths (GTDs) and two soil textures on the process of soil freezing and thawing during two successive freeze–thaw periods using the Simultaneous Heat and Water (SHAW) model. The results show that the frost depth was the maximum when the GTD was 1.0 m, and the maximum frost depths of sandy loam and fine sand were 97.6 and 98.9 cm, respectively. When the GTD was larger than 1.5 m, the maximum frost depth decreased with an increase in GTD, and the maximum frost depth of the soil profile was more sensitive to changes in the air temperature. The frost depth of the soil profile was linear with the square root of the accumulated negative soil surface temperature (ANST) under different GTDs. The ANST was influenced by the phreatic evaporation, and the soil freezing rate increased with an increase in GTD under the same ANST. This research is significant for the rational development of soil water and heat resources and the study of soil water–heat transfer in shallow groundwater areas.

Land Surface Model and Particle Swarm Optimization Algorithm Based on the Model-Optimization Method for Improving Soil Moisture Simulation in a Semi-Arid Region.

Improving the capability of land-surface process models to simulate soil moisture assists in better understanding the atmosphere-land interaction. In semi-arid regions, due to limited near-surface observational data and large errors in large-scale parameters obtained by the remote sensing method, there exist uncertainties in land surface parameters, which can cause large offsets between the simulated results of land-surface process models and the observational data for the soil moisture. In this study, observational data from the Semi-Arid Climate Observatory and Laboratory (SACOL) station in the semi-arid loess plateau of China were divided into three datasets: summer, autumn, and summer-autumn. By combing the particle swarm optimization (PSO) algorithm and the land-surface process model SHAW (Simultaneous Heat and Water), the soil and vegetation parameters that are related to the soil moisture but difficult to obtain by observations are optimized using three datasets. On this basis, the SHAW model was run with the optimized parameters to simulate the characteristics of the land-surface process in the semi-arid loess plateau. Simultaneously, the default SHAW model was run with the same atmospheric forcing as a comparison test. Simulation results revealed the following: parameters optimized by the particle swarm optimization algorithm in all simulation tests improved simulations of the soil moisture and latent heat flux; differences between simulated results and observational data are clearly reduced, but simulation tests involving the adoption of optimized parameters cannot simultaneously improve the simulation results for the net radiation, sensible heat flux, and soil temperature. Optimized soil and vegetation parameters based on different datasets have the same order of magnitude but are not identical; soil parameters only vary to a small degree, but the variation range of vegetation parameters is large.

Relationship between Evapotranspiration and Land Surface Temperature under Energy- and Water-Limited Conditions in Dry and Cold Climates

Remotely sensed land surface temperature- (LST-) dependent evapotranspiration (ET) models and vegetation index- (VI-) LST methods may not be suitable for ET estimation in energy-limited cold areas. In this study, the relationship of ET to LST was simulated using the process-based Simultaneous Heat and Water (SHAW) model for energy- and water-limited conditions in Mongolia, to understand the differences in ET processes under these two limiting conditions in dry and cold climates. Simulation results from the SHAW model along with ground observational data showed that ET and LST have a positive relationship when air temperature (Ta) is less than or equal to the temperature (Ttra) above which plants transpire and have a negative relationship whenTais greater thanTtraunder the energy-limited condition. However, ET and LST maintain a negative relationship with changes inTaunder the water-limited condition. The differences in the relationship between ET and LST under the energy-limited and water-limited conditions could be attributed to plant transpiration and energy storage in moist/watered soil and plants. This study suggests that different strategies should be used to estimate ET under the energy-limited condition in dry and cold climates.

Comparison of Methods for Estimating Evapotranspiration in a Small Rangeland Catchment

Evapotranspiration (ET) was quantified for two rangeland vegetation types, aspen and sagebrush‐grassland, over an 8‐yr study period by comparing the following approaches for estimating ET: eddy covariance systems (EC, available for only 6 yr); soil water storage loss measured by time domain reflectometry (TDR) and neutron probe; and model simulation. The research site, the Upper Sheep Creek catchment in the Reynolds Creek Experimental Watershed, is part of a study on the effects of prescribed fire and vegetation removal. Estimates of seasonal ET for the aspen using EC with the turbulent fluxes adjusted to force energy balance closure, a 180‐cm TDR soil profile, two 225‐cm neutron access tubes, and the Simultaneous Heat and Water (SHAW) model agreed well with each other. If the two neutron probes were averaged, the RMSD of all approaches over the 6 yr was within 8% of the average. For the sagebrush‐grassland, a 120‐cm TDR profile underestimated seasonal ET for all years except the year immediately following the prescribed fire, when rooting depth likely had not recovered. A 195‐cm neutron probe access tube located within 30 m of the stream underestimated ET for every year except when there was no streamflow, suggesting that lateral flow may have biased the results for this tube. A comparison of the other methods (EC flux adjusted to force energy balance closure, soil water loss measured from a 225‐cm neutron access tube, and SHAW model simulation) agreed within 3% during the 6 yr with EC measurements at that site.

Numerical Evaluation of a Sensible Heat Balance Method to Determine Rates of Soil Freezing and Thawing

In situ determination of soil freezing and thawing is difficult despite its importance for many environmental processes. A sensible heat balance (SHB) method using a sequence of heat pulse probes has been shown to accurately measure water evaporation in subsurface soil, and it has the potential to measure soil freezing and thawing. Determination of soil freezing and thawing may be more challenging than evaporation, however, because the latent heat of fusion is smaller than the latent heat of vaporization. Furthermore, convective heat flow associated with liquid water flow and occurrence of evaporation or condensation during freezing and thawing may cause inaccurate estimation of freezing and thawing with the SHB method. The objective of this study was to examine the applicability of the SHB concept to soil freezing and thawing. Soil freezing and thawing events were simulated with the simultaneous heat and water (SHAW) model. Ice contents were estimated by applying the SHB concept to numerical data produced by the SHAW model. Close agreement between the SHB‐estimated and the SHAW‐simulated ice contents were observed at depths below 24 mm. The main cause of inaccuracies with the SHB method was poor estimation of heat conduction at the 12‐mm depth, possibly due to simplifications of temporal or vertical distributions of temperature and thermal conductivity. The effects of convective heat flow and concurrent evaporation or condensation and freezing or thawing on the SHB method were small. The results indicate that the SHB method is conceptually suitable for estimating soil freezing and thawing. Independent, accurate estimates of thermal properties must be available to effectively use the SHB method to determine in situ soil freezing and thawing.

Effects of Permafrost Degradation on Soil Hydrological Processes in Alpine Steppe on the Qinghai-Tibet Plateau

Abstract Permafrost degradation is prevalent on the Qinghai-Tibet Plateau. This may lead to changes in water and heat transition in soils and thus affect the structure and function of ecosystems. In this paper, using the measured data of alpine steppe in Wudaoliang assessed the model performance in simulating soil freezing and thawing processes. Comparison of the simulated results by simultaneous heat and water (SHAW) model to the measured data showed that SHAW model performed satisfactorily. Based on analyzing the simulated and predicted results, two points were obtained: (1) freezing and thawing of the active layer proceeded both from the soil surface downward. Compared with the freezing process, the thawing process was slower. The freezing period persisted in the surface layer (4 cm depth) for about 5 months; (2) in the next 50 years, frozen period would be shorten about 20 days in the top 100 cm depth while the thawing would start earlier 40 days than present. Soil water storage in the 0–60 cm would decrease by 22% averagely, especially from June to August when the vegetation is at the dominating water consumed stage. Therefore, this kind of permafrost degradation as active layer freezing and thawing processes changes will reduce soil water content and thus influence those ecosystems above it.

Simulation of freezing and thawing soils in Inner Mongolia Hetao Irrigation District, China

Inner Mongolia Hetao Irrigation District, in north of China, is typical of seasonal frozen soil areas in the region. Irrigation in autumn is required to leach soil salt and to provide a reserve of soil water for the next year's crop. However, improper autumn irrigation results in the secondary salinization of soil. The objective of this study is to simulate soil water and heat dynamics during winter period with the one-dimensional Simultaneous Heat and Water (SHAW) model to assess its capability for simulating overwinter water storage. SHAW model soil parameters were calibrated by data of 1995–1996 and 2002–2004 and validated by data of 1996–2001 and 2005–2006 using field measured soil water contents and temperatures during freezing and thawing periods. Using calibrated and validated soil parameters, the paper simulates the process of soil freezing–thawing, and the dynamic variation of moisture–heat transfer, including soil water content, temperature, frost depth, soil evaporation, and water flux in the seasonal freezing–thawing period. These are useful to determine proper autumn irrigation management, and can be used in future research to address overwinter solute migration to reduce soil secondary salinization.

Technical Note: Simulating the Surface Energy Balance in a Soybean Canopy with the SHAW and RZ-SHAW Models

Correct simulation of surface energy balance in a crop canopy is critical for better understanding of soil water balance, canopy and soil temperature, plant water stress, and plant growth. One existing effort is to incorporate the surface energy balance in the Simultaneous Heat and Water (SHAW) model into the Root Zone Water Quality Model (RZWQM). In this study, an improved version of the RZ-SHAW (RZWQM-SHAW) hybrid model was tested for energy balance components, canopy and soil temperature, evapotranspiration (ET), and soil water content against eddy covariance data measured in a soybean canopy and against predictions of the original SHAW and RZWQM models. The experiment was first used previously to test the SHAW model for radiation energy fluxes within the canopy without examining the energy balance components, soil water balance, and soil temperature. The same parameters from that study were used in both the SHAW model and RZ-SHAW hybrid model without any modification in this study. In terms of root mean squared error (RMSE), both RZ-SHAW and SHAW simulated net radiation, sensible heat, and latent heat well. However, the ground heat flux simulated by RZ-SHAW was less accurate, with RMSE of 28.9 W m-2 compared to 22.6 W m-2 with SHAW, which could be due to differences in simulated soil evaporation. Simulated soil temperature at both 1.5 cm and 4.5 cm depths with RZ-SHAW was comparable to that of SHAW, with RMSE of 2.18C and 2.23C, respectively, compared to 2.13C and 2.20C with SHAW. Similarly, simulated canopy temperature was essentially the same, with RMSE values of 1.77C with RZ-SHAW and 1.69C with SHAW. Simulated surface soil water content was reasonable for both models. Simulated ET had an RMSE of 0.069 cm d-1 with RZ-SHAW and 0.074 cm d-1 with SHAW. The new RZ-SHAW model was an improvement over the original RZWQM model in simulating soil temperature and moisture, in addition to its ability to provide complete energy balance and canopy temperature.

Modelling plant canopy effects on annual variability of evapotranspiration and heat fluxes for a semi‐arid grassland on the southern periphery of the Eurasian cryosphere in Mongolia

AbstractThe ability to predict vegetation cover effects on thermal/water regimes can enhance our understanding of canopy controls on evapotranspiration. The Simultaneous Heat and Water (SHAW) model is a detailed process model of heat and water movement in a snow–residue–soil system. This paper describes provisions added to the SHAW model for vegetation cover and simulation of heat and water transfer through the soil–plant–air continuum. The model was applied to four full years (May 2003–April 2007) of data collected on sparse grassland at Nalaikh in north‐eastern Mongolia. Simulated soil temperature and radiation components agreed reasonably well with measured values. The absolute differences between simulated and measured soil temperatures were larger at both the surface layer and deeper layer, but relatively smaller in the layer from 0·8 to 2·4 m. Radiation components were mimicked by the SHAW model with model efficiency (ME) reaching 0·93–0·72. Latent and sensible heat fluxes were simulated well with MEs of 0·93 and 0·87, respectively. The vegetation control on evapotranspiration was investigated by sensitivity experiments of model performance with changing leaf area index (LAI) values but constant of other variables. The results suggest that annual evapotranspiration ranged from 16 to − 22% in response to extremes of doubled and zero LAI. Copyright © 2010 John Wiley & Sons, Ltd.

Improving SHAW long-term soil moisture prediction for continuous wheat rotations, Alberta, Canada

The Decision Support System for Agrotechnology Transfer-Cropping System Model (DSSAT-CSM) is a widely used modeling package that often simulates wheat yield and biomass well. However, some previous studies reported that its simulation on soil moisture was not always satisfactory. On the other hand, the Simultaneous Heat and Water (SHAW) model, a more sophisticated, hourly time step soil microclimate model, needs inputs of plant canopy development over time, which are difficult to measure in the field especially for a long-term period (longer than a year). The SHAW model also needs information on surface residue, but treats them as constants. In reality, however, surface residue changes continuously under the effect of tillage, rotation and environment. We therefore proposed to use DSSAT-CSM to simulate dynamics of plant growth and soil surface residue for input into SHAW, so as to predict soil water dynamics. This approach was tested using three conventionally tilled wheat rotations (continuous wheat, wheat-fallow and wheat-wheat-fallow) of a long-term cropping systems study located on a Thin Black Chernozemic clay loam near Three Hills, Alberta, Canada. Results showed that DSSAT-CSM often overestimated the drying of the surface layers in wheat rotations, but consistently overestimated soil moisture in the deep soil. This is likely due to the underestimation of root water extraction despite model predictions that the root system reached 80 cm. Among the eight growth/residue parameters simulated by DSSAT-CSM, root depth, leaf area index and residue thickness are the most influential characteristics on the simulation of soil moisture by SHAW. The SHAW model using DSSAT-CSM-simulated information significantly improved prediction of soil moisture at different depths and total soil water at 0-120 cm in all rotations with different phases compared with that simulated by DSSAT-CSM. Key words: Soil moisture, modeling, Decision Support System for Agrotechnology Transfer-Cropping System Model, Simultaneous Heat and Water Model

Simulation of within-canopy radiation exchange

Radiation exchange at the surface plays a critical role in the surface energy balance, plant microclimate, and plant growth. The ability to simulate the surface energy balance and the microclimate within the plant canopy is contingent upon simulation of the surface radiation exchange. A validation and modification exercise of the Simultaneous Heat and Water (SHAW) model was conducted for simulating the surface short-wave and long-wave radiation exchange over and within wheat, maize and soya bean plant canopies using data collected at Yucheng in the North China Plain and near Ames, Iowa. Whereas model testing was limited to monocultures and mixed canopies of green and senesced leaves, methodologies were developed for simulating short-wave and long-wave radiation fluxes applicable to a multi-species, multi-layer plant canopy. Although the original SHAW model slightly underpredicted reflected solar radiation with a mean bias error (MBE) of −5 to −10 W m −2, one would conclude that the simulations were quite reasonable if within-canopy measurements were not available. However, within-canopy short-wave radiation was considerably underestimated (MBE of approximately −20 W m −2) by the original SHAW model. Additionally, leaf temperatures tended to be overpredicted (MBE = +0.76 °C) near the top of the canopy and underpredicted near the bottom (MBE = −1.12 °C). Modification to the SHAW model reduced MBE of above canopy reflected radiation to −1 to −6 W m −2 and within-canopy radiation simulations to approximately −6 W m −2; bias in leaf temperature was reduced to less than 0.4 °C. Model modifications resulted in essentially no change in simulated evapotranspiration for wheat, 4.5% lower for maize and 1% higher for soya bean. Alternative approaches for simulating canopy transmissivity to diffuse radiation were tested in the modified version and had a minor influence on simulated short-wave radiation, but made almost no difference in simulated long-wave radiation or evapotranspiration. Modifications to the model should lead to more accurate plant microclimate simulation; further work is needed to evaluate their influence.

Modeling Soil Temperature, Frost Depth, and Soil Moisture Redistribution in Seasonally Frozen Agricultural Soils

Soil freezing and thawing processes and soil moisture redistribution play a critical role in the hydrology and microclimate of seasonally frozen agricultural soils. Accurate simulations of the depth and timing of frost and the redistribution of soil water are important for planning farm operations and choosing rotational crops. The Simultaneous Heat and Water (SHAW) model was used to predict soil temperature, frost depth, and soil moisture in agricultural soils near Carman, Manitoba. The model simulations were compared with three years of field data collected from summer 2005 to the summer 2007 in four cropping system treatments (oats with berseem clover cover crop, oats alone, canola, and fallow). The simulated soil temperatures compared well with the measured data in all the seasons (R2=0.96-0.99). The soil moisture simulations were better during the summer (RMSE=9.1-12.0% of the mean) compared to the winter seasons (RMSE=17.5-19.7% of the mean). During the winter, SHAW over-predicted by 0.02 to 0.10 m3 m-3 the amount of total soil moisture below the freeze front and under-predicted by 0.02 to 0.05 m3 m-3 the soil moisture in the upper frozen layers. The model was revised to account for the reduction in effective pore space resulting from frozen water to improve the winter soil moisture predictions. After this revision, the model performed well during the winter (RMSE=14.4% vs. 17.5%; R2=0.74 vs. 0.67 in vegetated treatments, and RMSE=12.9% vs. 19.7%; R2=0.73 vs. 0.52 in fallow treatments). The modified SHAW model is an enhanced tool for predicting the soil moisture status as a function of depth during spring thawing, and for assessing the availability of soil moisture at the beginning of the subsequent growing season.

Energy Balance Simulation of a Wheat Canopy Using the RZ-SHAW (RZWQM-SHAW) Model

RZ-SHAW is a new hybrid model coupling the Root Zone Water Quality Model (RZWQM) and the Simultaneous Heat and Water (SHAW) model to extend RZWQM applications to conditions of frozen soil and crop residue cover. RZ-SHAW offers the comprehensive land management options of RZWQM with the additional capability to simulate diurnal changes in energy balance needed for simulating the near-surface microclimate and leaf temperature. The objective of this study was to evaluate RZ-SHAW for simulations of radiation balance and sensible and latent heat fluxes over plant canopies. Canopy energy balance data were collected at various growing stages of winter wheat in the North China Plain (36 57' N, 116 6' E, 28 m above sea level). RZ-SHAW and SHAW simulations using hourly meteorological data were compared with measured net radiation, latent heat flux, sensible heat flux, and soil heat flux. RZ-SHAW provided similar goodness-of-prediction statistics as the original SHAW model for all the energy balance components when using observed plant growth input data. The root mean square error (RMSE) for simulated net radiation, latent heat, sensible heat, and soil heat fluxes was 29.7, 30.7, 29.9, and 25.9 W m-2 for SHAW and 30.6, 32.9, 34.2, and 30.6 W m-2 for RZ-SHAW, respectively. Nash-Sutcliffe R2 ranged from 0.67 for sensible heat flux to 0.98 for net radiation. Subsequently, an analysis was performed using the plant growth component of RZ-SHAW instead of inputting LAI and plant height. The model simulation results agreed with measured plant height, yield, and LAI very well. As a result, RMSE for the energy balance components were very similar to the original RZ-SHAW simulation, and latent, sensible, and soil heat fluxes were actually simulated slightly better. RMSE for simulated net radiation, latent heat, sensible heat, and soil heat fluxes was 31.5, 30.4, 30.2, and 27.6 W m-2, respectively. Overall, the results demonstrated a successful coupling of RZWQM and SHAW in terms of canopy energy balance simulation, which has important implications for prediction of crop growth, crop water stress, and irrigation scheduling.

Evaluation of SHAW Model in Simulating Energy Balance, Leaf Temperature, and Micrometeorological Variables within a Maize Canopy

Understanding and simulating plant canopy conditions can assist in better acknowledgment of plant microclimate characteristics, its effect on plant processes, and the influence of management and climate scenarios. The ability of the Simultaneous Heat and Water (SHAW) model to simulate the surface energy balance and profiles of leaf temperature and micrometeorological variables within a maize canopy and the underlying soil temperatures was tested using data collected during 1999 and 2003 at Yucheng, in the North China Plain. The SHAW model simulates the near‐surface heat and water movement driven by input meteorological variables and observed plant characteristic (leaf area index [LAI], height, and rooting depth). For 1999, the model accurately simulated air temperature and relative humidity in the upper one‐third of the canopy, but overpredicted midday temperature in the lower canopy. For 2003, although the surface energy balance was simulated quite well, radiometric canopy surface temperature and midday leaf temperature in the upper portion of the canopy were overpredicted, by approximately 5°C. Model efficiency (the fraction of variation in observed values explained by the model) for leaf temperature in the lower two‐thirds of the canopy ranged from 0.82 to 0.90, but fell to 0.38 for the uppermost canopy layer. Weaknesses in the model were identified and potentially include: the use of K‐theory to simulate turbulent transfer within the canopy; and simplifying assumptions with regard to long‐wave radiation transfer within the canopy. Model modifications are planned to address these weaknesses.

Evaluation of the SHAW Model in Simulating the Components of Net All-Wave Radiation

Radiation exchange at the surface plays a critical role in the surface energy balance, plant microclimate, and plant growth. The ability to simulate the surface energy balance and the microclimate within the plant canopy is contingent upon accurate simulation of the surface radiation exchange. A validation exercise was conducted of the Simultaneous Heat and Water (SHAW) model for simulating the surface radiation exchange (including downward long-wave and upward short- and long-wave radiation) over a maize canopy surface using data collected at Yucheng in the North China Plain. The model simulated upward short-wave and net all-wave radiation well with model efficiencies (ME) equaling 0.97 and 0.98, respectively. Downward and upward long-wave radiation were overestimated by 12.1 and 8.3 W m-2 with ME equaling 0.68 and 0.89, respectively. Two modifications to the model were implemented and tested to improve the simulated long-wave radiation exchange. In one modification, alternative schemes were tested to simulate cloudy sky long-wave radiation, and the best algorithm was employed in the model. With this modification, both downward and upward long-wave radiation were simulated better, with ME rising to 0.88 and 0.91, respectively. A second modification was implemented to use leaf temperature rather than canopy air temperature to compute emitted long-wave radiation. Although more theoretically correct, this modification did not improve simulations compared to the original model because upward long-wave radiation was already overpredicted and midday leaf temperatures at this site were typically higher than canopy air temperatures. Thus, the modification resulted in even higher overprediction of upward midday long-wave radiation. However, this modification removed some of the bias in nighttime emitted long-wave radiation. While the SHAW model simulates the radiation balance and transfer processes within the canopy reasonably well, results point to areas for model improvement.