Soil Moisture Flow Modeling with Water Uptake by Plants (Wheat) under Varying Soil and Moisture Conditions

A variably saturated soil moisture flow model is developed for planted soils with depth varying properties by incorporating a nonuniform macroscopic root water uptake function. The model includes spatial and temporal variation of the root density with dynamic root growth for simulating water uptake by plants along with the impact of soil moisture availability. The governing partial differential moisture flow equation integrated over the depth with a plant water uptake term is solved numerically by the implicit finite difference method using an iterative scheme. The model is first tested for barren soils for two profiles considering constant and depth varying soil characteristics under constant inflow condition. The results obtained are later tested with experimental data available in the literature. A nonuniform plant water uptake term is subsequently incorporated in the model and water uptake by wheat plants under different soil moisture availability conditions is studied. Finally, the moisture flow model is validated with field data of rain fed wheat (Triticum aestivum) using a dynamic root growth model for a layered root zone soil profile. The simulated soil moisture regime of the layered root zone shows a reasonably good agreement with the observed data.     

Modeling Water Uptake by Plant Roots

A mathematical model is developed that describes water uptake from soil by the roots of transpiring plants. Starting from a one-dimensional Richards equation with a root water extraction term, a partial differential equation predicting the moisture content in the soil profile is formulated. There are many expressions in literature that predict water extraction by plant roots, each one of them having its own merits and demerits. This study proposes a simple model with a linear root water extraction term that varies with time. The model also incorporates a sinusoidal root growth function that takes into account the root growth with time. The flow equation is subjected to a boundary condition that signifies the potential evaporation or the applied water (head) during the irrigation application time at the top boundary. The simulated model without the extraction function is validated by comparing the model results with experimental studies predicting soil moisture content for both a homogeneous and a layered medium. A linear root water extraction term is later adopted in the model, and a hypothetical case is simulated to compute the water uptake by plant roots. The comparison in all test cases was found to be reasonably good.     

Evaluation of a Nonlinear Root-Water Uptake Model

Soil-water movement due to root-water uptake, is a key process for plant growth and transport of water in the soil plant system. There are different root-water uptake models to determine the extraction rate of soil moisture by roots. The present study examines the performance of different root-water extraction models using available data as well as data generated under controlled conditions. Data pertaining to moisture uptake in respect to two crops: wheat (Triticum aestivum L.) and maize (Zea mays L.) along with soil-water characteristics have been monitored at the Indian Institute of Technology Roorkee, agricultural farm. For this purpose, a numerical model is also formulated by incorporating different moisture extraction terms as sink terms in the Richards equation. A nonlinear root-water uptake model selected as the base model was evaluated for its moisture uptake efficiency. The work establishes the merits of the base model over other extraction terms considered, particularly constant and linear extraction terms in predicting the soil moisture depletion in the root zone. The work stresses the nonlinearity parameter of the base model, which is capable of defining crop specific nonlinearity in the plant moisture uptake.     

Estimating Soil Moisture Under Low Frequency Surface Irrigation Using Crop Water Stress Index

The present study investigated the relationship between the crop water stress index (CWSI) and soil moisture for surface irrigated cotton (Gossypium hirsutum, Delta Pine 90b) at Maricopa, Arizona during the 1998 season. The CWSI was linked to soil moisture through the water stress coefficient Ks that accounts for reduced crop evapotranspiration when there is a shortage of soil water. A stress recovery coefficient Krec was introduced to account for reduced crop evapotranspiration as the crop recovered from water stress after irrigation events. A soil water stress index (SWSI) was derived in terms of Ks and Krec. The SWSI compared reasonably well to the CWSI, but atmospheric stability correction for the CWSI did not improve comparisons. When the CWSI was substituted into the SWSI formulation, it gave good prediction of soil moisture depletion (fDEP; when to irrigate) and depth of root zone depletion (Dr; how much to irrigate). Disagreement was greatest for fDEP<0.6 because cotton is less sensitive to water stress in this range.     

Regional Salinity Modeling for Conjunctive Water Use Planning in Kheri Command

A one-dimensional water and solute transport UNSATCHEM model is calibrated and validated with a saline water use experiment for wheat and cotton crops. The model is further employed for regional scale salinity modeling with distributed data on soil, irrigation water supply, and its quality from six representative locations from the Kheri command of the Bhakra irrigation system. The wheat–cotton crop rotation, the main rotation in the command, is considered during long-term simulations. The CROPWAT model is used to determine the evapotranspiration requirements of different wheat and cotton crops, while soil water retention parameters are estimated by the RETC model. Atmospheric water and solute boundary conditions are assumed at the top boundary, while free drainage is considered for the lower boundary, as the watertable in the command is sufficiently deep. Simulated salinity and yield values are compared with observed values for regional validation of the model. Critical areas in the command are identified using regional scale modeling results, and applying irrigation water availability and root zone salinity criteria. Guidelines for sustainable conjunctive water use planning are for the Kheri command to get optimum agricultural production despite the use of saline water for irrigation under prevailing scenarios of water availability and its quality.     

Assessment of Soil Moisture Dynamics of the Nebraska Sandhills Using Long-Term Measurements and a Hydrology Model

Soil moisture, evapotranspiration, and other major water balance components were investigated for six Nebraska Sandhills locations during a 6 year period (1998–2004) using a hydrological model. Annual precipitation in the study period ranged from 330 to 580?mm. Soil moisture was measured continuously at 10, 25, 50, and 100?cm depth at each site. Model estimates of surface (0–30?cm), subsurface (30–91?cm), and root zone (0–122?cm) soil moisture were generally well correlated with observed soil moisture. The correlations were poorest for the surface layer, where soil moisture values fluctuated sharply, and best for the root zone as a whole. Modeled annual estimates of evapotranspiration and drainage beneath the rooting zone showed large differences between sites and between years. Despite the Sandhills’ relatively homogeneous vegetation and soils, the high spatiotemporal variability of major water balance components suggest an active interaction among various hydrological processes in response to precipitation in this semiarid region.     

Soil Salinity Modeling over Shallow Water Tables. II: Application of LEACHC

Root zone salinity is one of the major factors adversely affecting crop production. A saline shallow water table can contribute significantly to salinity increases in the root zone. A soil salinity model (LEACHC) was used to simulate the effects of various management alternatives and initial conditions on root zone salinity, given a consistently high water table. The impact of water table salinity levels, irrigation management strategies, soil types, and crop types on the accumulation of salts in the root zone and on crop yields was evaluated. There were clear differences in soil salinity accumulations depending upon the depth and salinity of the water table. In general, increasing water table depth reduced average soil profile salinity, as did having lower salinity in the water table. Among the four irrigation strategies that were compared, the 14-day irrigation interval with replenishment of 75% of evapotranspiration (ET) resulted in the lowest soil salinity. With a 4-day interval and 50% ET replenishment, a wheat yield reduction of nearly 40% was predicted after three years of salt accumulation. Soil type and crop type had minimal or no impact on soil salinity accumulation. Under all conditions, soil water average electrical conductivity increased during the 3-year simulation period. This trend continued when the simulation period was extended to 6 years. Under the conditions shown to develop the highest average soil salinity (high water table, low irrigation), an annual presowing irrigation of 125 mm caused a nearly 50% reduction in soil salinity at the end of the 6-year simulation period, as compared with the soil salinity given no presowing irrigation.     

Surface Soil Moisture Simulation for a Typical Torrential Event with a Modified Noah LSM Coupling to the NWP Model

Surface soil moisture has great impact on both meso- and microscale atmospheric processes, especially on severe local convection processes and on the dynamics of short-lived torrential rains. To promote the performance of the land surface model (LSM) in surface soil moisture simulations, a hybrid hydrologic runoff parameterization scheme based upon the essential modeling theories of the Xin'anjiang model and Topography based hydrological Model (TOPMODEL) was developed in preference to the simple water balance model (SWB) in the Noah LSM. Using a strategy for coupling and integrating this modified Noah LSM to the Global/Regional Assimilation and Prediction System (GRAPES) analogous to that used with the standard Noah LSM, a simulation of atmosphere-land surface interactions for a torrential event during 2007 in Shandong was attempted. The results suggested that the surface, 10-cm depth soil moisture simulated by GRAPES using the modified hydrologic approach agrees well with the observations. Improvements from the simulated results were found, especially over eastern Shandong. The simulated results, compared with the products of the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) soil moisture datasets, indicated a consistent spatial pattern over all of China. The temporal variation of surface soil moisture was validated with the data at an observation station, also demonstrated that GRAPES with modified Noah LSM exhibits a more reasonable response to precipitation events, even though biases and systematic trends may still exist.     

Effects of Crop Growth and Development on Land Surface Fluxes

In this study,the Crop Estimation through Resource and Environment Synthesis model (CERES3.0) was coupled into the Biosphere-Atmosphere Transfer Scheme (BATS),which is called BATS_CERES,to represent interactions between the land surface and crop growth processes.The effects of crop growth and development on land surface processes were then studied based on numerical simulations using the land surface models.Six sensitivity experiments by BATS show that the land surface fluxes underwent substantial changes when the leaf area index was changed from 0 to 6 m2 m-2.Numerical experiments for Yucheng and Taoyuan stations reveal that the coupled model could capture not only the responses of crop growth and development to environmental conditions,but also the feedbacks to land surface processes.For quantitative evaluation of the effects of crop growth and development on surface fluxes in China,two numerical experiments were conducted over continental China:one by BATS_CERES and one by the original BATS.Comparison of the two runs shows decreases of leaf area index and fractional vegetation cover when incorporating dynamic crops in land surface simulation,which lead to less canopy interception,vegetation transpiration,total evapotranspiration,top soil moisture,and more soil evaporation,surface runoff,and root zone soil moisture.These changes are accompanied by decreasing latent heat flux and increasing sensible heat flux in the cropland region.In addition,the comparison between the simulations and observations proved that incorporating the crop growth and development process into the land surface model could reduce the systematic biases of the simulated leaf area index and top soil moisture,hence improve the simulation of land surface fluxes.     

Mapping Root Zone Soil Moisture Using Remotely Sensed Optical Imagery

Field-based soil moisture measurements are cumbersome. Remote sensing techniques based on active or passive microwave data have limitations. This paper presents and validates a new method based on land surface energy balances using remotely sensed optical data (including thermal infrared), which allows field and landscape-scale mapping of soil moisture depth-averaged through the root zone of existing vegetation. Root zone depth can be variable when crops are emerging. The pixel-wise “evaporative fraction” (ratio of latent heat flux to net available energy) is related to volumetric soil moisture through a standard regression curve that is independent of soil and vegetation type. Validation with measured root zone soil moisture in cropped soils in Mexico and Pakistan has a root mean square error of 0.05?cm3?cm?3; the error is less than 0.07?cm3?cm?3 in 90% of cases. Consequently, soil moisture data should be presented in class intervals of 0.05?cm3?cm?3. The utility of this method is demonstrated at the field scale using multitemporal thematic mapper imagery for irrigated areas near Cortazar in Mexico, and for river basin-scale water resources distribution in Pakistan. The potential limitation is the presence of clouds and the time lag between consecutive images with field-scale resolution. With the falling price of optical satellite imagery, this technique should gain wider acceptance with river basin planners, watershed managers, and irrigation and drainage engineers.     

Wetting Pattern Models for Drip Irrigation: New Empirical Model

Reliable information about the wetted dimensions of soil under drip irrigation helps designers to determine optimal emitter flow rates and spacings to reduce system equipment costs and provide better soil water conditions for the most efficient and effective use of water. This study presents a new empirical formula that predicts soil wetted dimensions around a drip emitter. The coefficients were obtained by using regression analysis on the results of field experiments done on the Pardis Agricultural Farm of Tehran University in Karaj, Iran. These data were also used to evaluate the semiempirical model of Zur and Schwartzman, the empirical model of Amin and Ekhmaj, and the analytical model WetUp. Statistical comparisons (mean error, root mean square error, and model efficiency) are made of the simulated data with the observed data. To evaluate the models, published experimental data by Risse et?al. and Li et?al. were also used. The results demonstrate that the suggested equations can be used for a wide range of discharge rates and soil types. The best result was obtained from the new empirical model proposed in this investigation. The lowest mean error for the wetted radius and wetted depth was 8.21 and 8.62?cm, respectively.     

Modeling of Cadmium Removal from Domestic Wastewater in Constructed Wetlands Using STELLA Simulation Program

A mathematical model was developed to simulate cadmium removal from wastewater in free water surface (FWS) and subsurface flow (SF) constructed wetlands using STELLA simulation program. The model simulated the accumulation of cadmium in soil (Cds), uptake by plants (Cdp), and residual concentration in effluent (Cdww_eff). The model was calibrated using one-half of the experimental data for the adjustment of the coefficients and the remaining data for model verification. The comparison of simulated and experimental values of Cds, Cdp, and Cdww_eff showed good agreement. The results indicated that the developed mathematical model could be useful for predicting the fate of cadmium when treating domestic effluents in constructed wetlands.     

Plant-Enhanced Subsurface Bioremediation of Nonvolatile Hydrocarbons

In recent years, phytoremediation, i.e., the use of plants to clean up soils contaminated with organics, has become a promising new area of research, particularly for in-situ cleanup of large volumes of slightly contaminated soils. A model that can be used as a predictive tool in phytoremediation operations was developed to simulate the transport and fate of a residual hydrocarbon contaminant interacting with plant roots in a partially saturated soil. Time-specific distribution of root quantity through soil, as well as root uptake of soil water and hydrocarbon, was incorporated into the model. In addition, the microbial activity in the soil rhizosphere was modeled with a biofilm theory. A sandy loam, which is dominant in soils of agricultural importance, was selected for simulations. Cotton, which has well-documented plant properties, was used as the model plant. Model parameters involving root growth and root distribution were obtained from the actual field data reported in the literature and ranges of reported literature values were used to obtain a realistic simulation of a phytoremediation operation. Following the verification of the root growth model with published experimental data, it has been demonstrated that plant characteristics such as the root radius are more dominant than contaminant properties in the overall rate of phytoremediation operation. The simulation results showed enhanced biodegradation of a hydrocarbon contaminant mostly because of increased biofilm metabolism of organic contaminants in a growing root system of cotton. Simulations also show that a high mean daily root-water uptake rate increases the contaminant retardation factors because of the resulting low water content. The ability to simulate the fate of a hydrocarbon contaminant is essential in designing technically efficient and cost-effective, plant-aided remedial strategies and in evaluating the effectiveness of a proposed phytoremediation scheme. The model presented can provide an insight into the selection and optimization of a specific strategy.     

Modeling BMPs to Optimize Municipal Wastewater Land Treatment System

Nutrient simulations of a municipal wastewater land treatment system were performed using the ground-water loading effects of agricultural management systems model. A total of 33 best management practices (BMPs) were simulated and compared to a baseline simulation of the current reed canary grass management practice. BMPs consisted of various combinations of crop types and cropping practices. Effectiveness of BMPs was compared based on the amount of nitrogen leached through the root zone and the harvested market value of each crop. Based on the model predictions and local market conditions, recommendations for the facility were given as the following: reed canary grass cut four times per year, orchard grass cut three or four times per year, or silage corn with a winter cover crop under low wastewater loading. Overloading the reed canary grass and orchard grass, especially for short periods of time, was simulated to have no adverse effects on the ground water. The ground-water loading effects of agricultural management systems model was demonstrated as a useful tool for the optimization of a municipal wastewater land treatment facility.     

内蒙古锡林河流域羊草草原植物生长旺季呼吸的影响因素分析和区分

Based on the static opaque chamber method, the respiration rates of soil microbial respiration, soil respiration, and ecosystem respiration were measured through continuous in-situ experiments during rapid growth season in semiarid Leymus chinensis steppe in the Xilin River Basin of lnner Mongolia, China. Soil temperature and moisture were the main factor affecting respiration rates. Soil temperature can explain most CO2 efflux variations (R2=0.376-0.655) excluding data of low soil water conditions. Soil moisture can also effectively explain most of the variations of soil and ecosystem respiration (R2=0.314-0.583), but it can not explain much of the variation of microbial respiration (R2=0.063). Low soil water content (≤5%) inhibited CO2 efflux though the soil temperature was high. Rewetting the soil after a long drought resulted in substantial increases in CO2 flux at high temperature. Bivariable models based on soil temperature at 5 cm depth and soil moisture at O-10 cm depth can explain about 70% of the variations of CO2 effluxes. The contribution of soil respiration to ecosystem respiration averaged 59.4%, ranging from 47.3% to 72.4%; the contribution of root respiration to soil respiration averaged 20.5%, ranging from 11.7% to 51.7%. The contribution of soil to ecosystem respiration was a little overestimated and root to soil respiration little underestimated because of the increased soil water content that occurred as a result of plant removal.     

Comparison of the Monod and Droop Methods for Dynamic Water Quality Simulations

The Monod method is widely used to model nutrient limitation and primary productivity in water bodies. It offers a straightforward approach to simulate the main processes governing eutrophication and it allows the proper representation of many aquatic systems. The Monod method is not able to represent the nutrient luxury uptake by algae, which consists of the excess nutrient uptake during times of high nutrient availability in the water column. The Droop method, which is also used to model nutrient limitation and primary productivity, takes into account the luxury uptake of nutrients. Because of the relative complexity of the Droop method, it has not been systematically adopted for the simulation of large stream networks. The Water Quality Analysis Simulation Program (WASP) version 7.1 was updated to include nutrient luxury uptake for periphyton growth. The objective of this paper is to present the new nutrient limitation processes simulated by WASP 7.1 and to compare the performance of the Droop and the Monod methods for a complex stream network where periphyton is the main organism responsible for primary productivity. Two applications of WASP 7.1 with the Droop and Monod methods were developed for the Raritan River Basin in New Jersey. Water quality parameters affecting the transport and fate of nutrients were calibrated based on observed data collected for the Raritan River total maximum daily load. The dissolved oxygen and nutrients simulated with WASP 7.1, obtained with the Droop and Monod methods, were compared at selected monitoring stations under different flows and nutrient availability conditions. The comparison of the WASP 7.1 applications showed the importance of using the Droop method when periphyton was the main organism responsible for primary productivity. The data simulated with the Droop method resulted in good agreement with the observed data for dissolved oxygen, ammonia-nitrogen, nitrate-nitrogen, and dissolved orthophosphate at the selected stations. The Monod method was not able to capture the diel dissolved oxygen variation when nutrients were scarce, and it resulted in unrealistic diel variations of nutrients at times of strong primary productivity at some locations.     

Soil Salinity Modeling over Shallow Water Tables. I:?Validation of LEACHC

Soil salinity is a very common problem in today's irrigated agriculture. High salinity levels adversely impact crop yields and reduce overall soil quality. The presence of a saline shallow water table can be a major contributor to this problem. The LEACHC version of LEACHM is one of the few numerical models that considers independent movement of individual ions along with their detailed chemistry. This model has apparently not previously been tested under saline shallow water table conditions. LEACHC was evaluated using both lysimeter and field data from the literature. The model performed reasonably well in simulating solute transport above a saline shallow water table. For both data sets used in model validation, less reactive ions (sodium and chloride) were predicted well while calcium concentrations were underpredicted. For the field data, the model predicted soil electrical conductivity (EC) profiles better than most of the individual ions. The water content profiles associated with the field data were also predicted quite well. Based on these results, LEACHC was selected as a simulation tool for evaluating the effects of management practices on salinity transport in crop root zones above a saline shallow water table.     

Water Stress Detection Under High Frequency Sprinkler Irrigation with Water Deficit Index

A remote sensing package called the agricultural irrigation imaging system (AgIIS) aboard a linear move irrigation system was developed to simultaneously monitor water status, nitrogen status, and canopy density at one-meter spatial resolution. The present study investigated the relationship between water status detected by AgIIS and soil moisture for the 1999 cotton (Gossypium hirsutum, Delta Pine 90b) season in Maricopa, Ariz. Water status was quantified by the water deficit index (WDI), an expansion of the crop water stress index where the influence of soil temperature is accounted for through a linear mixing model of soil and vegetation temperature. The WDI was best correlated to soil moisture through the FAO 56 water stress coefficient Ks model; stability correction of aerodynamic resistance did not improve correlation. The AgIIS did provide field images of the WDI that might aid irrigation scheduling and increase water use efficiency.     

Impact of Shallow Groundwater on Evapotranspiration Losses from Uncultivated Land in an Irrigated River Valley

In many agricultural regions of the West, decades of intensive irrigation have produced shallow water tables under not only cultivated fields but also the nearby uncultivated land. It is possible that the high water tables under the uncultivated lands are substantially increasing evapotranspiration (ET) rates, which would represent an unnatural and potentially nonbeneficial consumptive use. The objective of this paper is to quantify loss of water that occurs from uncultivated lands in a semiarid irrigated river valley (the Lower Arkansas River Valley in southeastern Colorado). A remote-sensing algorithm is used to estimate actual ET rates on 16 dates on the basis of Landsat satellite images. On the same dates, water table depths, soil moisture values, and soil water salinities are measured at up to 84 wells distributed across three study sites. On the basis of a water balance of the root zone, it is estimated that 78% of the ET is supplied by groundwater upflux at these sites. It is also observed that the ET and groundwater upflux decrease with increasing water table depth. A regression analysis indicates that the spatial variations in ET are most closely related to variations in vegetation-related attributes, whereas soil moisture and water table depths also explain substantial amounts of the variation. Valley-wide implications for reducing nonbeneficial ET through water table control also are discussed.