Simulated Soil Water Content Research Articles

Parameter Optimization for Predicting Soil Water Movement under Crop Residue Cover

Plant residue on the soil surface is considered useful for reducing the evaporation component of crop evapotranspiration. In contrast to soil, the upward movement of water through the plant residue layer is predominantly in the vapor phase rather than the liquid phase. Because of this difference in the mechanism of water movement, physically based numerical models that simulate liquid-dominated water movement in the soil profile have not been tested for water movement through residue. In this article, a new methodology is presented in which the crop residue layer is replaced with a hydraulically equivalent soil layer (ESL), thereby allowing the use of a numerical model, Hydrus-1D, to simulate the changes in soil moisture in a residue-covered production system. Parameter optimization software, PEST, was used to characterize the unsaturated hydraulic function of the ESL. The data for calibrating and validating the model were collected from two different studies in 2010 at the University of California West Side Research and Extension Center in Five Points, California. The simulated soil water content in the profile under the ESL matched the measured soil water content under crop residue cover with RMSE values of 0.004 to 0.013 cm3 cm-3 for calibration and 0.001 to 0.019 cm3 cm-3 for validation. Parameter optimization of the ESL provides a new tool to allow the use of a physically based model such as Hydrus-1D to simulate the many complex interactions between the soil, crop residue, and atmosphere. The methodology may need further validation in different soil, mulch, and climatic conditions. In future research, the effect of crop residue on evaporation for a crop system will be quantified for different growth periods, and efficient irrigation management protocols will be designed to reduce the evaporation component of crop evapotranspiration.

Modelling for maize irrigation scheduling using long term experimental data from Plovdiv region, Bulgaria

Abstract Independent historic datasets on irrigated maize, collected over seven years (1984–1990), were used to parameterize the irrigation scheduling model ISAREG. Experimental data were obtained under rainfed, deficit, and full irrigation conditions in an alluvial soil at Tsalapitsa, Plovdiv region, in the Thracian plain, Bulgaria. Crop coefficients and depletion fractions for no-stress were calibrated by minimizing the differences between observed and simulated soil water content. The calibration was performed using data from full irrigation and rainfed treatments while deficit irrigation treatments were used for validation. The modelling efficiency was high, 0.91 for the calibration and 0.89 for the validation. The resulting average absolute errors of the estimate for the soil water content were smaller than 0.01 cm3 cm−3. The model was also tested by comparing computed versus observed seasonal evapotranspiration. Results for dry years show a modelling efficiency of 0.96 but the model slightly underestimated evapotranspiration for other years. The yield response factor was derived from observed yield data of the hybrid variety H708 when relative evapotranspiration deficits were smaller than 0.5. The value Ky = 1.32 was obtained. The relative yield decreases predicted with this Ky value compared well with observed data. Results support the use of the ISAREG model for developing water saving irrigation schedules for the Thracian plain.

Optimizing Soil Hydraulic Parameters in RZWQM2 under Fallow Conditions

Robust estimation of soil hydraulic parameters is essential for predicting soil water dynamics and related biogeochemical processes; however, uncertainties in estimated parameter values limit a model's ability for prediction and application. In this study, methods of global analysis (Latin hypercube sampling, LHS) and gradient‐based optimization (PEST, parameter estimation software) were explored to calibrate soil hydraulic parameters in the Root Zone Water Quality Model (RZWQM2). Six methods of estimating Brooks–Corey parameters of the soil water retention curve and saturated hydraulic conductivity were evaluated to simulate daily soil water dynamics under fallow conditions in eastern Colorado. The calibrated soil hydraulic parameters showed similar trends with soil depth for the different estimation methods in RZWQM2 but resulted in large differences between simulated and observed soil water contents. The PEST optimization based on soil type values as initial estimates gave reasonable soil water responses but with some unrealistic soil hydraulic parameters and soil evaporation. Overall, errors in simulated soil water contents were reduced by using LHS to initialize and constrain the PEST parameter space, which also stabilized the cross‐validation results. Calibration results using water content measurements at four depths (30, 60, 90, and 150 cm) were similar to results using 10 depths (30, 40, 50, 60, 70, 80, 90, 120, 150, and 170 cm). Calibrating soil hydraulic parameters remains challenging, but the combined calibration procedures (LHS + PEST) with cross‐validation can reduce parameter uncertainties and improve model performance.

Combining an ecological model with remote sensing and GIS techniques to monitor soil water content of croplands with a monsoon climate

Abstract Soil water is an important factor affecting photosynthesis, transpiration, growth, and yield of crops. Accurate information on soil water content (SWC) is crucial for practical agricultural water management at various scales. In this study, remotely sensed parameters (leaf area index, land cover type, and albedo) and spatial data manipulated using the geographic information system (GIS) technique were assimilated into the boreal ecosystem productivity simulator (BEPS) model to monitor SWC dynamics of croplands in Jiangsu Province, China. The monsoon climate here is characterized by large interannual and seasonal variability of rainfall causing periods of high and low SWC. Model validation was conducted by comparing simulated SWC with measurements by a gravimetric method in the years 2005 and 2006 at nine agro-meteorological stations. The model-to-measurement R 2 values ranged from 0.40 to 0.82. Nash-Sutcliffe efficiency values were in the range from 0.10 to 0.80. Root mean square error (RMSE) values ranged from 0.028 to 0.056 m 3 m −3 . Simulated evapotranspiration (ET) was consistent with ET estimated from pan evaporation measurements. The BEPS model successfully tracked the dynamics and extent of the serious soil water deficit that occurred during September–November 2006. These results demonstrate the applicability of combining process-based models with remote sensing and GIS techniques in monitoring SWC of croplands and improving agricultural water management at regional scales in a monsoon climate.

Parametric modeling of root length density and root water uptake in unsaturated soil

The problem of water movement through the root zone has attracted increasing interest during the last few decades. In this research, the spatial and temporal pattern of root water uptake in wetted soil was studied in the root zone of a 6-year-old apple tree. An important part of the root water uptake model is root length density, which was measured by sampling soil cores in one quarter of the root zone. The exponential model better described the observed apple root distribution. The measured data were compared against the outputs of the root density distribution model. A normalized root length density was used to simulate root water uptake and determine the effect of root distribution on the water content pattern. A 2-dimensional (2D) model of root water uptake was established, which includes root density distribution function, potential transpiration, and the soil water stress-modified factor. Root water uptake distribution was measured with an array of time domain reflectometry (TDR) probes. Root water uptake parameters were optimized by minimizing the residuals between measured and simulated soil water content values. Studies showed that the maximum root water uptake was at a depth of 10-50 cm. The results indicated an excellent agreement between the measured and the simulated values, proving that the developed root water uptake model is effective and feasible.

Simulation of nitrogen leaching from a fertigated crop rotation in a Mediterranean climate using the EU-Rotate_N and Hydrus-2D models

Abstract Two different modeling approaches were used to simulate the N leached during an intensively fertigated crop rotation: a recently developed crop-based simulation model (EU-Rotate_N) and a widely recognized solute transport model (Hydrus-2D). Model performance was evaluated using data from an experiment where four N fertigation levels were applied to a bell pepper–cauliflower–Swiss chard rotation in a sandy loam soil. All the input data were obtained from measurements, transfer functions or were included in the model databases. Model runs were without specific site calibration. The use of soil input parameters based on the same pedotransfer functions in both models resulted in a very similar simulation of soil water content in spite of the different nature of the approaches. Good correlations were found between the simulated water draining below 60 cm and that calculated by water balance. Accuracy of the predicted nitrate nitrogen (NO3-N) contents in the 0–90 cm soil profile was acceptable with both models, with values of the mean absolute error (MAE) below the average standard deviation of the observations. The uptake of nitrate was better simulated with EU-Rotate_N where specific crop N demand algorithms are involved. In the simulations with Hydrus-2D the evapotranspiration demand was a limiting factor for N uptake, resulting in an increasing underestimation of uptake with decreasing N fertilizer rates. Simulated N leaching below a depth of 60 cm was higher with Hydrus-2D due to a higher nitrate concentration in percolated water. Comparison of the observed and predicted yield response to N applications with EU-Rotate_N demonstrated that the best fertigation strategy could be identified and the risk of nitrate leaching quantified with this model. The results showed that for a successful solving of the problem studied, Hydrus-2D probably would need a more complex calibration, and that the EU-Rotate_N model can provide acceptable predictions by adjusting basic parameters for the growing conditions. Further research with other crops and soil types will allow up-scaling the quantification of N leaching from a field level to regional and national levels, identifying best management strategies in relation to N use from an environmental and economic perspective.

Impact of climate change on soil moisture dynamics in Brandenburg with a focus on nature conservation areas

Global warming impacts the water cycle not only by changing regional precipitation levels and temporal variability, but also by affecting water flows and soil moisture dynamics. In Brandenburg, increasing average annual temperature and decreasing precipitation in summer have already been observed. For this study, past trends and future effects of climate change on soil moisture dynamics in Brandenburg were investigated, considering regional and specific spatial impacts. Special Areas of Conservation (SACs) were focused on in particular. A decreasing trend in soil water content was shown for the past by analyzing simulation results from 1951 to 2003 using the integrated ecohydrological model SWIM [Krysanova, V., Müller-Wohlfeil, D.-I., Becker, A., 1998. Development and test of a spatially distributed hydrological/water quality model for mesoscale watersheds. Ecol. Model. 106, 261–289]. The trend was statistically significant for some areas, but not for the entire region. Simulated soil water content was particularly low in the extremely dry year 2003. Comparisons of simulated trends in soil moisture dynamics with trends in the average annual Palmer Drought Severity Index for the region showed largely congruent patterns, though the modeled soil moisture trends are characterized by a much higher spatial resolution. Regionally downscaled climate change projections representing the range between wetter and drier realizations were used to evaluate future trends of available soil water. A further decrease of average available soil water ranging from −4% to −15% was projected for all climate realizations up to the middle of the 21st century. An average decrease of more than 25mm was simulated for 34% of the total area in the dry realization. Available soil water contents in SACs were generally higher and trends in soil moisture dynamics were lower mainly due to their favorable edaphic conditions. Stronger absolute and relative changes in the simulated trends for the past and future were shown for SACs within Brandenburg than for the state as a whole, indicating a high level of risk for many wetland areas. Nonetheless, soil water content in SACs is expected to remain higher than average under climate change conditions as well, and SACs therefore have an important buffer function under the projected climate change. They are thus essential for local climate and water regulation and their status as protected areas in Brandenburg should be preserved.

Extension of an Existing Model for Soil Water Evaporation and Redistribution under High Water Content Conditions

Most crop, hydrology, and water quality models require the simulation of evaporation from the soil surface. A model developed by J.T. Ritchie in 1972 provides useful algorithms for estimating soil evaporation, but it does not calculate the soil water redistribution resulting from evaporation. A physically‐based model using diffusion theory, described previously by Suleiman and Ritchie in 2003, provides efficient algorithms for soil water redistribution and soil evaporation. However, the model is appropriate only for second stage drying when the soil in the entire profile being simulated is below the drained upper limit (θDUL) and no more drainage occurs due to gravity. This paper extends the Suleiman–Ritchie model for soil water contents higher than θDUL where soil evaporation rates are usually higher than second stage drying. New algorithms were developed for these wetter conditions that are functions of soil depth and the wetness of the near‐surface soil. New model parameters were calibrated with data measured in laboratory soil column studies. The resulting model was integrated into DSSAT‐CSM (Decision Support System for Agrotechnology Transfer Cropping Systems Model). Simulated soil evaporation rates and soil water contents obtained using the Suleiman–Ritchie model with the developed extensions and the previous DSSAT soil evaporation model were compared and evaluated with field measurements of soil water content during several drying cycles for parts of 3 yr in North Central Florida. Computed soil water contents from the model agreed well with the measured soil water contents near the surface, and provided more accurate estimations than the original DSSAT soil evaporation model, especially for the 5‐cm surface layer.

An easily implemented agro-hydrological procedure with dynamic root simulation for water transfer in the crop–soil system: Validation and application

Models for water transfer in the crop–soil system are key components of agro-hydrological models for irrigation, fertilizer and pesticide practices. Many of the hydrological models for water transfer in the crop–soil system are either too approximate due to oversimplified algorithms or employ complex numerical schemes. In this paper we developed a simple and sufficiently accurate algorithm which can be easily adopted in agro-hydrological models for the simulation of water dynamics. We used a dual crop coefficient approach proposed by the FAO for estimating potential evaporation and transpiration, and a dynamic model for calculating relative root length distribution on a daily basis. In a small time step of 0.001 d, we implemented algorithms separately for actual evaporation, root water uptake and soil water content redistribution by decoupling these processes. The Richards equation describing soil water movement was solved using an integration strategy over the soil layers instead of complex numerical schemes. This drastically simplified the procedures of modeling soil water and led to much shorter computer codes. The validity of the proposed model was tested against data from field experiments on two contrasting soils cropped with wheat. Good agreement was achieved between measurement and simulation of soil water content in various depths collected at intervals during crop growth. This indicates that the model is satisfactory in simulating water transfer in the crop–soil system, and therefore can reliably be adopted in agro-hydrological models. Finally we demonstrated how the developed model could be used to study the effect of changes in the environment such as lowering the groundwater table caused by the construction of a motorway on crop transpiration.

Statistical spring wheat yield forecasting for the Canadian prairie provinces

A study to forecast regional spring wheat ( Triticum aestivum L.) yields on the Canadian Prairies was conducted, based on simulated daily water use and soil water contents derived from the National Drought Model. Empirical linear regression models were calibrated from 1976 to 2006 spring wheat yield data for this purpose. Potential predictors assessed were mainly those indicators related to water stress conditions at different crop growth stages. Stepwise regression and cross-validation were employed for the selection of the predictors in multivariate linear regression models used for forecasting spring wheat yields from seeding to harvest. The cross-validated “forecasts” for 1976–2006, using data up to harvest, explained 77%, 64%, 63% and 70% of yield variances, respectively, for Alberta, Saskatchewan, Manitoba and the entire Prairie region. Root mean squared error of the “forecasts” ranged from 8% to 11% of the average yields. The prediction accuracy earlier in the season was often lower than later in the season. Usable prediction accuracy was found by the middle of the growing season (around heading or anthesis), but only marginally effective at seeding time, especially so for Saskatchewan.

Simulating Canopy Transpiration and Photosynthesis of Corn Plants under Contrasting Water Regimes Using a Coupled Model

A process-based corn simulation model (MaizSim) was coupled with a two-dimensional soil simulator (2DSOIL) to simulate transpiration and photosynthesis of corn under contrasting water regimes. To improve the simulation of stomatal reaction to drought stress, a hydraulic stomatal control algorithm was implemented in the coupled photosynthesis-stomatal conductance module. Corn plants were grown in sunlit growth chambers and irrigated at three different frequencies. Simulated soil water content, transpiration, and photosynthesis rates were compared with those measured in the chambers. Comparison among simulations and measurements indicated that the coupled model was able to simulate the changes in soil water contents as well as the changes in transpiration and photosynthesis rates of corn plants under varying water status over the growing season. It was also found that the simulated photosynthesis rates were not as sensitive to reduction in stomatal conductance as the simulated transpiration rates. Reasons for this difference are discussed from the modeling viewpoint. This result agreed with the differences in sensitivity of photosynthesis and transpiration to changes in stomatal closure that have been reported in the literature. These results suggest that the coupled model not only is a valuable tool in studying corn transpiration and photosynthesis under drought stress, but it also provides a platform to implement and evaluate algorithms in studies of corn crop water dynamics and CO2 assimilation.

Comparison of measured and simulated water storage in dryland terraces of the Loess Plateau, China

In the hilly regions of China, developing sustainable agriculture requires implementing conservation management practices that prevent soil erosion and conserve soil and water resources. In the semiarid northwest Loess Plateau, the primary conservation management practice is terracing. Numerical simulation of soil water dynamics in terraces is potentially an efficient means of investigating the effects of terrace design on moisture retention, but little information is available on the accuracy of such simulations. In this work, we evaluated the accuracy of HYDRUS-2D simulations of water infiltration and redistribution in fallow, level, dryland terraces located in the Loess Plateau. The simulated soil water content distributions were in good agreement with experimental data. Modeling analyses showed that about one-third of the evaporative water losses occurred from the terrace riser surface. To prevent such losses, it is advisable to mulch the riser and minimize the riser surface area. The simulations also demonstrated that with other dimensions equal, wide terraces retain more water on a percentage basis than narrow ones due to a lower evaporating surface area are per unit volume of water storage. With other design considerations being equal, wide beds and minimal riser surface areas will likely enhance water capture and retention. Future analyses of terrace moisture dynamics may additionally include simulations of root water uptake, surface ponding, and runoff.

Coupling of heat, water vapor, and liquid water fluxes to compute evaporation in bare soils

The quantification of soil evaporation and of soil water content dynamics near the soil surface are critical in the physics of land-surface processes on regional and global scales, in particular in relation to mass and energy fluxes between the ground and the atmosphere. Although it is widely recognized that both liquid and gaseous water movement are fundamental factors in the quantification of soil heat flux and surface evaporation, their computation is still rarely considered in most models or practical applications. Moreover, questions remain about the correct computation of key factors such as the soil surface resistance or the soil surface temperature. This study was conducted to: (a) implement a fully coupled numerical model to solve the governing equations for liquid water, water vapor, and heat transport in bare soils, (b) test the numerical model with detailed measurements of soil temperature, heat flux, water content, and evaporation from the surface, and (c) test different formulations for the soil surface resistance parameter and test their effect on soil evaporation. The code implements a non-isothermal solution of the vapor flux equation that accounts for the thermally driven water vapor transport and phase changes. Simulated soil temperature, heat flux, and water content were in good agreement with measured values. The model showed that vapor transport plays a key role in soil mass and energy transfer and that vapor flow may induce sinusoidal variations in soil water content near the surface. Different results were obtained for evaporation calculations, depending on the choice of the soil surface resistance equation, which was shown to be a fundamental term in the soil-atmosphere interactions. The results also demonstrated that soil water dynamics are strongly linked to temperature variations and that it is important to consider coupled transport of heat, vapor and liquid water when assessing energy dynamics in soils.

Cotton irrigation scheduling in central Asia: model calibration and validation with consideration of groundwater contribution

AbstractThe calibration and validation of the irrigation scheduling simulation model ISAREG for Central Asian conditions were performed using cotton field observations in the Hunger Steppe over the period 1983–87, and in the Fergana Valley for 2001–03. The calibration referred to the crop coefficients and the soil water depletion factor for no stress. Groundwater contribution was considered in computations adopting a set of parametric equations used in ISAREG. Calibration and validation were performed by comparing the observed and simulated soil water content during each crop season. Various indicators of goodness of fit were used to assess model validation. For the Hunger Steppe, the validation also included the comparison of model‐computed and field‐measured crop evapotranspiration, which was performed with the energy balance method. Results obtained show a good agreement between field observations and model predictions, thus allowing use of the ISAREG model to generate and assess alternative irrigation schedules aimed at improved water use in Central Asia. Copyright © 2008 John Wiley & Sons, Ltd.

Comparison of dynamic and static APRI-models to simulate soil water dynamics in a vineyard over the growing season under alternate partial root-zone drip irrigation

In this paper, a two-dimensional (2D) dynamic model of root water uptake was proposed based on soil water dynamic and root dynamic distribution of grapevine, and a function of soil evaporation related to soil water content was defined under alternate partial root-zone drip irrigation (APDI). Then the soil water dynamic model of APDI (dynamic APRI-model) was developed on the basis of the 2D dynamic model of root water uptake and soil evaporation function over the growing season. Soil water dynamic in APDI was respectively simulated by dynamic and static APRI-models. The simulated soil water contents by two models were compared with the measured value. Results showed that values of root-mean-square-error (RMSE) for dynamic APRI-model were less than that of the static APRI-model either in the east side or the west side of grapevine. The average relative error between the simulated and measured value was less than 5% for dynamic APRI-model, indicating that the dynamic APRI-model is better than the static APRI-model in simulating the soil moisture dynamic throughout the growing season under the APDI.

Sensitivity of tile drainage flow and crop yield on measured and calibrated soil hydraulic properties

Process-based agricultural system models require detailed description of soil hydraulic properties that are usually not available. The objectives of this study were to evaluate the sensitivity of model simulation results to variability in measured soil hydraulic properties and to compare simulation results using measured and default soil parameters. To do so, we measured soil water retention curves and saturated soil hydraulic conductivity ( K sat) from intact soil cores taken from a long-term experimental field near Nashua, Iowa for the Kenyon–Clyde–Floyd–Readlyn soil association. The soil water retention curves could be well described using the pore size distribution index ( λ). Measured λ values from undisturbed soil cores ranged from 0.04 to 0.12 and the measured K sat values ranged from 1.8 to 14.5 cm/h. These hydraulic properties were then used to calibrate the Root Zone Water Quality Model (RZWQM) for simulating soil water content, water table, tile drain flow, and crop yield (corn and soybean) by optimizing the lateral K sat (L K sat) and hydraulic gradient (HG) for subsurface lateral flow. The measured soil parameters provided better simulations of soil water storage, water table, and N loss in tile flow than using the default soil parameters based on soil texture classes in RZWQM. Sensitivity analyses were conducted for λ, K sat, saturated soil water content ( θ s) or drainable porosity, L K sat, and HG using the Latin Hypercubic Sampling (LHS) and for L K sat and HG also using a single variable analysis. Results of sensitivity analyses showed that RZWQM-simulated yield and biomass were not sensitive to soil hydraulic properties. Simulated tile flow and N losses in tile flow were not sensitive to λ and K sat either, but they were sensitive to L K sat and HG. Further sensitivity analyses using a single variable showed that L K sat in the tile layer was a more sensitive parameter compared to L K sat in other soil layers, and HG was the most sensitive parameter for tile flow under the experimental soil and weather conditions.

A spatially referenced water and nitrogen management model (WNMM) for (irrigated) intensive cropping systems in the North China Plain

A spatially referenced biophysical model, the water and nitrogen management model (WNMM), was developed and shown to simulate dynamic soil water movement and soil–crop carbon (C) and nitrogen (N) cycling under a given agricultural management, for the purpose of identifying optimal strategies for managing water and fertiliser N under intensive cropping systems (mainly wheat–maize) in the North China Plain and other regions in the world. A uniform data structure, ARC GRID ASCII format, was used both in GIS and WNMM for achieving a close Model-GIS coupling. A significant part of WNMM adopts and modifies concepts and components from widely used models, with a focus on soil N transformations. WNMM simulates the key processes of water dynamics in the surface and subsurface of soils: including evapotranspiration, canopy interception, water movement and groundwater fluctuations; heat transfer and solute transport; crop growth; C and N cycling in the soil–crop system; and agricultural management practices (crop rotation, irrigation, fertiliser application, harvest and tillage). The model runs on a daily time step at any desired scale and is driven by lumped variables (meteorological and crop biological data) in text data format, and spatial variables (soil and agricultural management) in ARC GRID ASCII format. In particular, WNMM simulates all key N transformations in agricultural fields, including mineralisation of fresh crop residue N and soil organic N, formation of soil organic N, immobilisation in biomass, nitrification, ammonia (NH 3) volatilisation, denitrification and nitrous oxide (N 2O) emissions. WNMM has been successfully applied in Fengqiu County, Henan Province and Luancheng County, Hebei Province, China at site and regional scales. The key WNMM components were intensively calibrated and verified against comprehensive field measurements of soil water content, evapotranspiration, crop leaf area index and yield, NH 3 volatilisation, denitrification and N 2O emissions as well as nitrate (NO 3 −)–N concentrations in the soil solution. A sensitivity analysis showed that WNMM was sensitive to changes in meteorological variables, soil hydraulic properties, land use and agricultural management. At the site scale, WNMM simulated well soil water content, crop growth and yield, NH 3 volatilisation and soil NO 3 −–N concentration. There was uncertainty in simulating soil denitrification and N 2O emissions, when the predicted peaks of denitrification and N 2O emissions at very wet conditions could not be confirmed because of limitations in the acetylene-inhibition method for measuring denitrification. At county scale, WNMM simulation of crop yield in Fengqiu County explained 22% of the variation in observed crop yields, and 31% of crop yield variation in Luancheng County where soil variation was less. These results are considered acceptable because factors such as soil salinity and other nutrient deficiencies, which have not been considered in this version of WNMM, may play a role. The source code for the WNMM is available on request.

Comparison of APRI and Hydrus-2D models to simulate soil water dynamics in a vineyard under alternate partial root zone drip irrigation

Alternate partial root zone irrigation (APRI) is a new water-saving irrigation technique. It can reduce irrigation water and transpiration without reduction in crop yield, thus increase water and nutrient use efficiency. Understanding of soil moisture distribution and dynamic under the alternate partial root zone drip irrigation (APDI) can help to develop the efficient irrigation schemes. In this paper, a two-dimensional (2D) root water uptake model was proposed based on soil water dynamic and root distribution of grape vine, and a function of soil evaporation related to soil water content was defined under the APDI. Then the soil water dynamic model of APDI (APRI-model) was developed based on the 2D root water uptake model and soil evaporation function combined with average measured soil moisture content at 0–10 cm soil layer. Soil water dynamic in APDI was respectively simulated by Hydrus-2D model and APRI-model. The simulated soil water contents by two models were compared with the measured value. The results showed that the values of root-mean-square-error (RMSE) range from 0.01 to 0.022 cm3/cm3 for APRI-model, and from 0.012 to 0.031 cm3/cm3 for Hydrus-2D model. The average relative error between the simulated and measured soil water content is about 10% for APRI-model, and from 11% to 29% for Hydrus-2D model, indicating that two models perform well in simulating soil moisture dynamic under the APDI, but the APRI-model is more suitable for modeling the soil water dynamic in the arid region with greater soil evaporation and uneven root distribution.

Development of Frozen Soil Model

In this paper,firstly, new version of frozen soil model is presented, in which the enthalpy and total volumetric water equivalent content in soil is used as predictive variables to replace the predictive variables of soil temperature and volumetric liquid water content in the current models respectively. It makes the required estimation of liquid-ice phase change rate in the current models unnecessary, and therefore avoids the introduction of the error in estimation of the phase change rate into the new model and in turn will improve the new version model in both speeding convergence of numerical iterative process and enhancing the model performance. At the same time, a numerical scheme is also developed for the diagnostic equations in the new version, which is very efficient for finding the true solution with a few iteration times. It's proved the numerical simulation results of the new version model are in good agreement with two field observed data. Besides, based on analyzing three schemes for soil freezing-thaw from theoretical view and comparing the numerical simulation results, it is found that the parameterization scheme, which takes the relation between moisture potential and temperature in soil derived from the equilibrium thermodynamics theory into consideration, can describe the freezing-thaw processes well. Numerical results have shown that different freezing-thaw parameterizations have greater influence on simulated soil temperature, water content, and latent and sensible heat fluxes at soil surface.

Comparisons of measured stream flow with drainage and runoff simulated by a soil-vegetation-atmosphere transport model parameterized with GLOBE student data

Summary Predicting runoff and drainage from landscapes and correlating these with stream flow can be a powerful watershed management tool. We examined the feasibility of using runoff and drainage output of a simple soil-vegetation-atmosphere (SVAT) model as a predictor of monthly and daily changes in measured stream flow. Six watersheds in the eastern US were analyzed, located from approximately 35°N to 43°N. They ranged in area from 23 to 2463 km 2 and were 35–65% forested. The SVAT model was parameterized with weather, soils and phenological data largely obtained from a secondary school in each watershed that is participating in the Global Learning and Observations to Benefit the Environment (GLOBE) program. This program is a United States government science education effort promoting scientific inquiry in grades K-12 by providing protocols for collecting environmental data. Monthly measured stream flow and simulated runoff + drainage over a one year period were normalized to the largest value in that period and were compared using linear regression. Simulated monthly runoff + drainage explained between 37% and 76% of the variability in monthly stream flow. Changes in daily simulated runoff + drainage and measured stream flow depended on the simulated volumetric soil water content ( θ v ). At low θ v , large precipitation events (>20 mm) did not result in increased daily simulated runoff + drainage or measured stream flow. At high or saturating θ v , large precipitation events resulted in increased daily simulated runoff + drainage followed by increased measured stream flow within two days.