Effect of crop sequence,soil sample location and depth on soil water holding capacity under center pivot irrigation

This study was carried out to investigate the changes that may occur to the soil water holding capacity under center pivot irrigation systems when grown with different crop patterns over a long period of time. The changes of water holding capacity were checked as affected by crop location and depth. The study was carried out in a dominantly sandy loam soil irrigation scheme, north of Saudi Arabia in 1999. The field capacity (FC), permanent wilting point (PWP) were determined by the pressure membrane method. The general trend of the results showed that crop sequences that were fallow or had cereal crops in their rotation before sampling period considerably affected FC and PWP. This is represented by crop sequences 6, 5 and 2 which produced the highest means of FC at 14.75, 12.79 and 12.68%, respectively. Moreover, the lowest means of FC were produced with alfalfa dominating the crop rotation prior to the sampling period. This is represented by crop sequences 7, 3 and 4 at FCs of 9.56, 9.74 and 10.28%, respectively. Crop sequences 1,4,5 and 6 gave the highest values of PWP, while the lowest one was in crop sequence 7 (4.79%). The highest means of available water (AW) were found in crop sequences 6, 2, 5 at 8.65, 6.87 and 6.35%, respectively. While the lowest value of AW was found in crop sequence 4 at 3.69%. The results showed that the soil samples collected from inside center pivots, for all crop sequences, produced higher means of FC at 12.87%, PWP at 6.53 and 6.34% compared with soil samples collected from outside the center pivot. The relative decrease of FC, PWP and AW due to increasing the soil sample depth from 0–15 to 60–90 cm was 21.55, 22.52 and 20.53%, respectively. The measured values of FC, PWP and AW showed that the highest values of standard deviation (S.D.) and coefficient of variation (CV), for FC, PWP, and AW were found in soil sample depth followed by soil sample location and crop sequence respectively. The interaction effect of crop sequences and soil sample depths on PWP and AW was significant.     

Modeling water uptake by roots

Summary Most current models of the water uptake by plant roots from the soil profile solve the equation for flow of water in unsaturated soils. The boundary condition at the root-soil interface is represented, whether explicitly or implicitly by some kind of root distribution function. Such models have sufficient number of parameters so that they can be fitted to data reasonably well. Most water uptake patterns, when normalized with respect to root zone depth and plant extractable water reveal, remarkable similarities regardless of soil texture, plant species, or root distribution. This similarity is not predictable with current models. A model based upon non-linear behavior of the root membranes and described by a distributed sink moving downward through the soil profile adequately represents the uptake process. The shape of the sink function is not critical and only two parameters, a root depth parameter, and an extractable water parameter are needed.     

Transpirational response to water availability for winter wheat as affected by soil textures

Soil texture and evaporative demand have been reported to be the main factors which influence the transpirational response to soil water deficits. However, experimental evidences are not enough. The objective of this study was to investigate the transpirational response to soil water availability in soils of different textures under different evaporative demand levels. The three main soils of the Loess Plateau of China (loamy clay, clay loam and sandy loam) were selected and six constant soil water treatments were applied for winter wheat (Triticum aestivum L.) grown in pots. In order to reduce the influence of environmental conditions and plant factors, a normalized daily transpiration rate was used to develop the relationships with volumetric soil water content and soil water suction. Results showed that, under various levels of evaporative demand, a linear-plateau function with a critical value could be used to describe the dynamic change of the normalized transpiration rate with soil drying. Soil texture significantly influenced both the critical and the slope values of the linear-plateau equations, however, evaporative demand significantly affected the critical values of volumetric soil water content and soil suction for the loamy clay and clay loam only. Therefore, for saving water, different strategies are needed for these three soils.     

Models for estimating capillary rise in a heavy clay soil with a saline shallow water table

Summary Shallow saline water tables underlie large areas of the clay soils in the Murray basin of Australia. Accurate estimation of capillary rise is important in formulating management strategies to avoid degradation of such soils. Measured capillary rise from a saline water table was compared with capillary rise estimated by three mathematical models of varying complexity and input requirement. A quasi steady state analytical model (QS-SAM), a transient state analytical model (TSAM) and a numerical model (NM) were used. An undisturbed heavy clay soil core of 0.75 m diameter and 1.4m deep was subjected to a static saline water table at 1.2 m from the surface. A wheat crop was grown on the core and the weekly capillary rise from the water table was measured. The electrical conductivity of a 1:2 soil: water extract was determined at 0.15 m depth intervals before and 21 weeks after the introduction of the saline water table. The QSSAM did not satisfactorily estimate the initial wetting of the subsoil and the estimated capillary rise was considerably lower than the measured values. Capillary rise estimated by the TSAM was reasonably close to the measured values, but the weekly rates fluctuated considerably. The NM estimated capillary rise quite satisfactorily throughout the experiment. Except near the soil surface, the electrical conductivity values estimated by the NM were close to the measured values. For estimating total capillary rise over large areas, the TSAM is preferred over the NM because of its fewer input requirements and shorter execution time.     

Grouping soils with similar properties for areal water budgeting and moisture mapping

Infiltration, field capacity and wilting point are the most important parameters used in water budgeting. Even for a small watershed of uniform weather characteristics, water budgeting must be performed for sub-areas of distinct soil properties. As the number of these sub-areas increases, the number of calculations involved in water budgeting also becomes large. For a large area including many different weather zones, the total number of water budget calculations, proportional to the product of weather zones and the number of sub-areas of uniform soil properties, can reach a magnitude which easily exceeds the capability of the most powerful computer available. Therefore, it is important to group soils with similar water movement and storage properties (the same can also be said about weather) to reduce water budgeting calculations. The magnitide of dispersion of soil properties in each sub-area needs to be estimated. The US Soil Taxonomy, a general soil classification scheme, was found to be useful to this grouping. The soil grouping technique based on the Soil Taxonomy was used in producing soil hydraulic properties maps for the Island of Oahu, Hawaii.     

Drainage models to predict soil water regimes in drained soils: a UK perspective

Drainage is an intervention in the natural hydrology of the soil to alter the duration of adverse (waterlogged) soil conditions. The effects of drainage can be investigated by models that predict the position of the water table at a site in the presence of drainage. An inter-related series of models, which include the van Schilfgaarde non-steady state model, that have been used in the UK for the evaluation of drainage design options, are described. A simplified form of the van Schilfgaarde equation is presented, equivalent to a standard time series model, allowing both the efficient implementation of the model, and the inverse use of the model to derive performance parameters from observational data using statistical methods. A sensitivity analysis is used to investigate the relative importance of the two soil parameters, drainable porosity and soil hydraulic conductivity, on the performance of the model. This shows a far greater effect due to the variation of hydraulic conductivity.The use of a similar model to predict water tables in non-homogeneous soils has also been explored, including the investigation of a two-phase model to describe water movement in soils which are dominated by macropores. More useful, however, is the prediction of water table fluctuations in soils in which the soil hydraulic conductivity is a continuous function of soil depth, using the drainage theory of Youngs (1965). Solutions are presented for the logarithm of the hydraulic conductivity varying linearly with depth. The improvement in model performance is however gained at the expense of an additional parameter that describes the variation of hydraulic conductivity with depth. Some methods for deriving this parameter are discussed. Results from the use of this model are compared with those derived from the simple uniform conductivity model, showing superior performance.Lastly, the issue of soil lateral heterogeneity and the replicability of measurements is discussed. A detailed study of the variation of water table levels from a replicated drainage experiment indicates that in a practical situation very real limits exist on the accurate measurement of water tables, and that these present limits on our ability to verify models.     

Comparative evaluation of three-crop growth models for the simulation of soil water balance in oilseed Brassica

Performance of three-crop growth models for dynamic simulation of soil water balance in the sandyloam soils cropped to oilseed Brassica was evaluated. The model parameters were subjected to sensitivity analysis, modified and calibrated for local environment and verified with experimental field values. Simulated root zone (0–120 cm) moisture from Campbell–Diaz model was more sensitive to stepwise changes in input parameters as compared to the O'Leary and SWASIM models. While calibrating these models during post-rainy season of 1992–1993, simulated profile moisture from the Campbell–Diaz and SWASIM models, on an average, did not deviate by more than ± 5% from measurements except on one or two occasions whereas the O'Leary model gave slight overestimates up to seed filling stage and underestimates of the order of −6% in the post-seed filling stage. Campbell–Diaz model requiring least number of inputs yielded the lowest error estimates (6.01–11.06 mm) followed by the SWASIM (6.46–18.88 mm) and O'Leary (8.3–20.6 mm) models. The Campbell–Diaz and SWASIM models can also be successfully used with common coefficients and also to simulate layerwise soil moisture contents, respectively.     

Estimating plant root water uptake using a neural network approach

Water uptake by plant roots is an important process in the hydrological cycle, not only for plant growth but also for the role it plays in shaping microbial community and bringing in physical and biochemical changes to soils. The ability of roots to extract water is determined by combined soil and plant characteristics, and how to model it has been of interest for many years. Most macroscopic models for water uptake operate at soil profile scale under the assumption that the uptake rate depends on root density and soil moisture. Whilst proved appropriate, these models need spatio-temporal root density distributions, which is tedious to measure in situ and prone to uncertainty because of the complexity of root architecture hidden in the opaque soils. As a result, developing alternative methods that do not explicitly need the root density to estimate the root water uptake is practically useful but has not yet been addressed. This paper presents and tests such an approach. The method is based on a neural network model, estimating the water uptake using different types of data that are easy to measure in the field. Sunflower grown in a sandy loam subjected to water stress and salinity was taken as a demonstrating example. The inputs to the neural network model included soil moisture, electrical conductivity of the soil solution, height and diameter of plant shoot, potential evapotranspiration, atmospheric humidity and air temperature. The outputs were the root water uptake rate at different depths in the soil profile. To train and test the model, the root water uptake rate was directly measured based on mass balance and Darcy's law assessed from the measured soil moisture content and soil water matric potential in profiles from the soil surface to a depth of 100 cm. The ‘measured’ root water uptake agreed well with that predicted by the neural network model. The successful performance of the model provides an alternative and more practical way to estimate the root water uptake at field scale.     

Evaluation of pedotransfer functions in predicting the soil water contents at field capacity and wilting point

Thirteen pedotransfer functions (PTFs), namely Rosetta PTF, Brakensiek, Rawls, British Soil Survey Topsoil, British Soil Survey Subsoil, Mayr-Jarvis, Campbell, EPIC, Manrique, Baumer, Rawls–Brakensiek, Vereecken, and Hutson were evaluated for accuracy in predicting the soil moisture contents at field capacity (FC) and wilting point (WP), of fine-textured soils of the Zagros mountain region of Iran. PTFs were developed using the laboratory measurements made on soil moisture at FC and WP, particle-size distribution, bulk density, and organic matter content. PTFs were evaluated on the basis of mean-squared deviation (MSD) between the observed and predicted values. Results agreed with the concept that the PTFs developed on soils of similar properties to the ones under study generally perform better than the others. In the case of the Zagros mountain soils, the “British Soil Survey” and “Brakensiek” PTFs were found to be the best methods. Since the soils under study had a wide range of organic matter contents (0.2–5.5%), the better performance of these PTFs may also be explained by the fact that they happen to be the only ones that require organic matter content as input. Rosetta, a software package that involves an artificial neural network approach, was of intermediate value in estimating soil moistures of the soils in question. This was attributed to the fact that the texture and the bulk density of the Zagros soils were not in the range of those used to develop Rosetta.     

Comparison of a modified statistical-dynamic water balance model with the numerical model WAVES and field measurements

The hydrology of the Earth’s surface is quite dynamic. Attempts to model the hydrology have been only partially successful. Many of the existing detailed numerical models require so many input parameters that they are not practical for use at specific locations, and the simplified models do not well describe the dynamic surface hydrology. Here, we present a modified statistical-dynamic model that is simple to use. We evaluate how well the modified statistical-dynamic model describes surface hydrology by comparing it to a more advanced numerical model and to field measurements. Our model is developed by making specific modifications to the Eagleson statistical-dynamic water balance model. Specific modifications to the earlier model include: the addition of precipitation periods that can account for seasonal variations in precipitation and water balance, a change in how soil water properties and flow are computed, and how a limited water supply influences plant transpiration so that transpiration rates can be less than the potential transpiration rates. Mass conservation and a step by step prediction-correction algorithm are used to calculate the mean water balance and its partitioning as well as the average soil moisture in the precipitation periods. All of these modifications improve the statistical-dynamic model and make it more flexible and potentially useful. Comparisons of the modified model are made with numerical simulations of the WAVES model and with 10-year field measurements from an eco-hydrological system on the Loess Plateau. The data from a long-term fertility experiment of winter wheat at Changwu Agro-ecological Station on the Loess Plateau are used to test the modified statistical-dynamic water balance model. In both comparisons the correspondence is remarkably good. The modified statistical-dynamic water balance model accurately predicts the mean water balance components and the dynamic processes of the mean soil moisture for specific wheat-fertility-productivity conditions. The statistical-dynamic water balance model is simple to use, fast and efficient, requires less input than complex numerical models, and is shown to be quite accurate in predicting dynamic soil moisture storage.     

Spatial representativity of the possible sites for measuring the water balance of apricot trees

The wide spatial variability of soil parameters together with the close relation between a soil’s texture and its hydrodynamic characteristics means that the sites where moisture is to be measured should be chosen carefully since the readings are often extrapolated to other sites where reading are not taken. Given that variations in texture behave as regionalized variables, a geostatistical analysis of soil texture is the most suitable and useful tool for identifying such sites. An isovalue map of d₅₀ obtained by kriging is described, which we propose can be used for locating soil moisture measurements sites for water balance studies in an apricot plantation.     

A simulation model of water dynamics in winter wheat field and its application in a semiarid region

Many models for water flow in cropped soil contain parameters such as rooting density, root permeability, and root water potential. Usually these parameters are chosen by trial-and-error method and direct measurements are difficult and impractical in some cases. This study presents a simulation model capable of analyzing water transport dynamics in a soil–plant–atmosphere continuum (SPAC). This model is developed by combining an existing mathematical model for soil water flow, a modified transpiration model taking into account of the air pressure and diurnal changes of the extinction coefficient of crop canopies, and a new simple model for root water uptake. Using data from lysimeters in a field experiment carried out on a wheat crop, we also developed two new empirical equations for the estimation of total canopy resistance and soil evaporation.We then applied the model for 2 years (1990–1991, 1991–1992) on winter wheat in a semiarid area of northwest China. Required parameters, particularly soil hydraulic and crop parameters, were determined by field and laboratory tests. Outputs from the simulation were in good agreement with the independent field measurements of seasonal changes in soil water content, canopy transpiration, surface evaporation, and root water uptake along the soil profile. In addition, this simulation agreed well with the actual measurements of seasonal crop water consumption and soil water balance among the treatments for different irrigation amounts.     

Sugarcane water use from shallow water tables: implications for improving irrigation water use efficiency

The resource potential of shallow water tables for cropping systems has been investigated using the Australian sugar industry as a case study. Literature concerning shallow water table contributions to sugarcane crops has been summarised, and an assessment of required irrigation for water tables to depths of 2 m investigated using the SWIMv2.1 soil water balance model for three different soils. The study was undertaken because water availability is a major limitation for sugarcane and other crop production systems in Australia and knowledge on how best to incorporate upflow from water tables in irrigation scheduling is limited. Our results showed that for the three soils studied (representing a range of permeabilities as defined by near-saturated hydraulic conductivities), no irrigation would be required for static water tables within 1 m of the soil surface. Irrigation requirements when static water tables exceeded 1 m depth were dependent on the soil type and rooting characteristics (root depth and density). Our results also show that the near-saturated hydraulic conductivities are a better indicator of the ability of water tables below 1 m to supply sufficient upflow as opposed to soil textural classifications. We conclude that there is potential for reductions in irrigation and hence improvements in irrigation water use efficiency in areas where shallow water tables are a low salinity risk: either fresh, or the local hydrology results in net recharge.     

Simulation of yield decline as a result of water stress with a robust soil water balance model

The relative yield decline that is expected under specific levels of water stress at different moments in the growing period is estimated by integrating the FAO K_y approach [Doorenbos, J., Kassam, A.H., 1979. Yield response to water. FAO Irrigation and Drainage Paper No. 33. Rome, Italy] in the soil water balance model BUDGET. The water stored in the root zone is determined in the soil water balance model on a daily basis by keeping track of incoming and outgoing water fluxes at its boundary. Given the simulated soil water content in the root zone, the corresponding crop water stress is determined. Subsequently, the yield decline is estimated with the K_y approach. In the K_y approach the relation between water stress in a particular growth stage and the corresponding expected yield is described by a linear function. To account for the effect of water stresses in the various growth stages, the multiplicative, seasonal and minimal approach are integrated in the model. To evaluate the model, the simulated yields for two crops under various levels of water stress in two different environments were compared with observed yields: winter wheat under three different water application levels in the North of Tunisia, and maize in three different farmers’ fields in different years in the South West of Burkina Faso. Simulated crop yields agreed well with observed yields for both locations using the multiplicative approach. The correlation value (R²) between observed and simulated yields ranged from 0.87 to 0.94 with very high modeling efficiencies. The root mean square error values are relatively small and ranged between 7 and 9%. The minimal and seasonal approaches performed significantly less accurately in both of the study areas. Estimation of yields on basis of relative transpiration performed significantly better than estimations on basis of relative evapotranspiration in Burkina Faso. A sensitivity analysis showed that the model is robust and that good estimates can be obtained in both regions even by using indicative values for the required crop and soil parameters. The minimal input requirement, the robustness of the model and its ability to describe the effect on seasonal yield of water stress occurring at particular moments in the growing period, make the model very useful for the design of deficit irrigation strategies. BUDGET is public domain software and hence freely available. An installation disk and manual can be downloaded from the web.     

Modeling shallow water table evaporation in irrigated regions

Groundwater discharge through evaporation due to a shallow water table can be an important component of a regional scale water balance. Modeling this phenomenon in irrigated regions where soil moisture varies on short time scales is most accurately accomplished using variably saturated modeling codes. However, the computational demands of these models limit their application to field scale problems. The MODFLOW groundwater modeling code is applicable to regional scale problems and it has an evapotranspiration package that can be used to estimate this form of discharge, however, the use of time-invariant parameters in this module result in evaporation rates that are a function of water table depth only. This paper presents a calibration and validation of the previously developed MOD-HMS model code using lysimeter data. The model is then used to illustrate the dependence of bare soil evaporation rates on water table depth and soil moisture conditions. Finally, an approach for estimating the time varying parameters for the MODFLOW evapotranspiration package using a 1-D variably saturated MOD-HMS model is presented.     

斥水土壤的水力参数及水平吸渗规律

为了对不同斥水程度土壤的水力性质进行分析,对比了van Genuchten和Brooks-Corey模型对于不同斥水程度下的塿土、砂姜黑土、盐碱土和砂土的适用性;进行了一维水平吸渗试验,分别运用Philip模型和Kostiakov公式对入渗规律进行了模拟,并分析了吸渗率和斥水持续时间的关系;采用水平吸渗法推求了土壤非饱和扩散率,并用指数函数拟合了非饱和扩散率和体积含水率的关系.结果表明:van Genuchten和Brooks-Corey模型对亲水和斥水土壤均具有较好的适用性;斥水性土壤的累积入渗量随时间变化曲线在一定时刻发生转折,未转折前Kostiakov公式的模拟结果比Philip模型好;当斥水时间大于40 s时,吸渗率的变化趋于稳定并在0~0.1 cm/min0.5内变化;非饱和扩散率和体积含水率关系的模拟可采用指数关系,且其对亲水性土壤的模拟效果优于斥水性土壤.斥水土壤的水力参数与亲水土壤的有明显差别,且表现出特殊性.     

基于黏粒量的土壤水分特征曲线预测模型

[目的]建立基于黏粒量的土壤水分特征曲线预测模型.[方法]设计12种不同黏粒量的质量混合比处理,获得一系列合成土样,通过测定合成土样的土壤水分特征曲线,研究了在体积质量一致的条件下,黏粒量对土壤水分特征曲线参数和孔隙分布的影响.[结果]在体积质量为1.55 g/cm3条件下,黏粒量增加1.9倍,土壤中传导孔隙(0.03...     

离心机法测定土壤水分特征曲线中的收缩特性

为了探明土壤在离心力作用下的收缩规律,开展了离心机法测定土壤水分特征曲线试验.砂壤土和黏壤土分别设定3个初始容重,以离心机法测定的数据为基础,研究了离心力变化下的土壤收缩规律,并通过van Genuchten-Mualem(VG-M)模型对2种情景模式(考虑容重变化和未考虑容重变化)下所测定的土壤水分特征曲线进行拟合,并以此估算所得的土壤水力特性参数对沟灌二维水分运动特性进行了数值模拟,同时结合室内试验对比分析了参数的合理性.结果表明,离心机转速增大,土壤含水率降低,容重随之增大,当吸力为7 000 cm时,砂壤土和黏壤土的容重分别近于1.81和1.79 g/cm³;基于土壤收缩特征曲线,供试土壤收缩过程可采用三直线模型进行表征,但各收缩段的吸力范围存在差异;与未考虑容重变化所得VG-M模型中的参数值相比,考虑土壤容重变化所得的滞留含水率θ_r和进气吸力值倒数a均增大,但形状系数n均减小;以考虑土壤容重变化所得VG-M参数为基础进行沟灌二维水分运动数值模拟,其入渗水量、湿润锋运移距离(垂直和水平)与实测值的误差绝对值均值分别为5.8%,3.0%和2.6%,较未考虑容重变化时精度分别提高了39.2%,57.2%和52.9%.因此离心机法测定土壤水分特征曲线的过程中需考虑土壤容重的变化,且以此获得的参数能够较为显著地提高数值模拟精度.     

Comparison between mechanistic and functional models for estimating soil water balance: deterministic and stochastic approaches

In many models used to simulate soil-water relationships, representations of the transport mechanisms in the soil-plant-atmosphere continuum, range from mechanistic to functional. The objective of this paper is to compare two functional models, FAO (Doorenbos and Pruitt, 1977) and Ritchie (1985)models, with a mechanistic model (Maraux and Lafolie, 1998) to simulate the soil water balance of maize and sorghum grown in sequence in Nicaragua. In the FAO model, the soil is described as a single reservoir which is characterized by its amount of water varying on a daily time scale, depending on the rain, drainage, and actual evapotranspiration. In the Ritchie model, the soil is regarded as a multilayered soil profile. The maximum evapotranspiration is divided between soil evaporation and plant transpiration, and drainage occurs if the amount of water arriving in the last layer corresponds to a water content greater than the field capacity. The mechanistic model is based on the Richards' equation. Comparison of the three models was first made according to a deterministic approach with parameters coming from the same database. We then considered a stochastic approach for which 800 hydraulic characteristics of the soil were generated, according to the spatial variability observed at the field scale and to the scaling theory applied to similar porous media. A distribution of the stochastic parameters used in the three models was thus derived. Results showed that the order of magnitude of the evapotranspiration was similar for the three models (902, 874, 842 mm cumulative evapotranspiration for a 203 day period for the MM, Ritchie, and FAO models, respectively). Adding a capillary rise mechanism in the functional models improved moderately the soil-water balance. Evapotranspiration and drainage showed moderate sensitivity to spatial variability in soil hydraulic properties (coefficients of variation less than 1.6%), whereas final water storage (after 203 days) showed a greater sensitivity (coefficients of variation from 7.9–15.7%, depending on the model).     

Use of soil physical characteristics from laboratory measurements or standard series for modelling unsaturated water flow

Soil physical characteristics are important input parameters for simulation modelling of unsaturated flow in soils and associated solute flow. The determination of soil water retention and hydraulic conductivity curves in the laboratory is laborious and expensive. For modelling studies that require characteristics for many soil horizons, such as regional studies or scenario studies, it may be impossible to measure all the necessary characteristics. An alternative would be to use characteristics inferred from readily available soil data by class-pedotransfer functions. In this study such a comparison was made for six sites on sandy soils in the Netherlands using the soil-water model SWACROP with soil physical characteristics from either laboratory measurements or from a standard series as input. For this the simulated pressure head values and moisture content values were compared with measured values at eight different depths using statistical criteria. Furthermore two functional criteria, i.e. the number of workable days and number of days with possible drought, were inferred from simulated pressure head values and again the different results were compared. It was found that simulation results were not significantly different, implying that standard series or class-pedotransfer functions could be used in studies like these for simulating the unsaturated water flow regime in sandy soils on field/farm level or regional level. Differences for specific criteria for individual sites were sometimes substantial and in such cases (at field level) it will make a difference which soil physical characteristics are used.