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Research was conducted in northern Colorado in 2011 to estimate the crop water stress index (CWSI) and actual transpiration (T a) of maize under a range of irrigation regimes. The main goal was to obtain these parameters with minimum instrumentation and measurements. The results confirmed that empirical baselines required for CWSI calculation are transferable within regions with similar climatic conditions, eliminating the need to develop them for each irrigation scheme. This means that maize CWSI can be determined using only two instruments: an infrared thermometer and an air temperature/relative humidity sensor. Reference evapotranspiration data obtained from a modified atmometer were similar to those estimated at a standard weather station, suggesting that maize T a can be calculated based on CWSI and by adding one additional instrument: a modified atmometer. Estimated CWSI during four hourly periods centered on solar noon was largest during the 2 h after solar noon. Hence, this time window is recommended for once-a-day data acquisition if the goal is to capture maximum stress level. Maize T a based on CWSI during the first hourly period (10:00–11:00) was closest to T a estimates from a widely used crop coefficient model. Thus, this time window is recommended if the goal is to monitor maize water use. Average CWSI over the 2 h after solar noon and during the study period (early August to late September, 2011) was 0.19, 0.57, and 0.20 for plots under full, low-frequency deficit, and high-frequency deficit irrigation regimes, respectively. During the same period (50 days), total maize T a based on the 10:00–11:00 CWSI was 218, 141, and 208 mm for the same treatments, respectively. These values were within 3 % of the results of the crop coefficient approach.

In transferring crop coefficients (Kc) from one location to another, it has been assumed that basal Kc (minimal soil evaporation) and/or Kc during full-canopy cover will be universally valid if the variation in weather is accounted for by reference ET variations. The sensitivity of full-canopy-cover crop coefficients (Kc) to variations in solar radiation, air temperature, air vapor density and wind speed was investigated using an energy balance model. Interpretation of the sensitivity involved analyzing the components of the energy balance, which varied as a result of differences in aerodynamic and canopy resistance between the reference crop and the crop to be irrigated. Instability of crop coefficients was shown to increase with decreasing crop canopy resistance and with increasing crop height, indicating that the expectation of universal validity for basal or full-canopy-cover coefficients is not fulfilled. For crops taller and/or with lower canopy resistance than the short clipped grass (0.1 m) used as reference, the magnitude of Kc fluctuations with changes in weather elements suggests caution when using Kc values under environmental conditions different from those prevailing at the site where they were experimentally derived. Values of Kc derived for crops whose height and canopy resistance are not too different from the reference are more stable across environments. Thus, full-cover alfalfa (0.5-m height) would be a better reference crop choice than a short clipped grass (0.1 m) because its canopy resistance and roughness better approximate those of most crops. Research to develop operational methods for directly estimating crop ET, as an alternative to the two-step approach of calculating reference ET and determining site specific empirical crop coefficients, seems desirable.

Soil infiltration problems occur as a result of alternating irrigation with saline-sodic waters and monsoon rainfall. Hydraulic conductivity (K) and related soil properties of a non-calcareous (CaCO3 0.8%) and a calcareous soil (25.7%) having similar textural constituents were monitored. The soils were subjected to six consecutive cycles of irrigation with saline waters (SW) of sodium adsorption ratio (SAR), 10, 20 or 30 (mmol/l)1/2, but of similar electrolyte concentration (EC; 80 mEq/l), and each followed by simulated rain water (SRW) (electrical conductivity <0.02 dS/m). Results are presented in terms of relative K i.e. K r=K sw/K tw where K tw is steady state K measured separately under application with tap water (ECw 0.54 dS/m, SAR 0.9). For irrigation with SW alone, K r values were reduced to 0.95, 0.79 and 0.70 at SAR of 10, 20 and 30, respectively, in non-calcareous soil. The corresponding values of 0.95, 0.87 and 0.79 were slightly higher in calcareous soil. Severe reductions in K r were observed in both the soils when subjected to alternate use of SW and SRW (K r=0.22, 0.03 and 0.02 in non-calcareous, and 0.57, 0.17 and 0.07 in calcareous soil). About half of the reductions in K r were reversible when SW was subsequently applied. Depth distributions of salinity, pH, dispersible clay and hydraulic head indicate that disaggregation and dispersion of surface soil was the cause of reduced K with SRW, whereas “washed in” sub-soil became restrictive and controlled the K values with SW under alternations of SW and SRW. Salt release (<1 mEq/l) was insufficient to avoid dispersion and sustain K even in the calcareous soil. For evaluating the infiltration hazard of saline-sodic water, measurements of stabilized K values after consecutive cycles of SW and SRW should serve as a better diagnostic criteria under monsoonal climates than threshold EC–SAR combinations.

Field experiments were conducted in a deep Vertisol at the Indian Institute of Soil Science, Bhopal during the years 2001–2005 to assess the effect of five different irrigation strategies through combinations of sprinkler and flood irrigation and two N application methods on yield and water use efficiency of wheat (cv WH 147). The amount of irrigation applied each year differed according to the availability of water in the water harvesting pond to simulate the actual water crisis faced by the farmers in this region during these years due to monsoon failure. Results indicated that when wheat was grown only with 8-cm irrigation at sowing or 14 cm up to the crown root initiation stage, dry sowing of wheat immediately followed by sprinkler and subsequent irrigation through flooding produced the highest yield and water and nitrogen use efficiencies. However, when 20-cm irrigation was supplied up to the flowering stage or 14-cm irrigation was supplied up to tillering stage through sprinkler in 4 and 3 splits, respectively, at critical growth stages, maximized the grain yield and water and nitrogen use efficiencies. Across the years, the crop yield and water and nitrogen use efficiencies increased with increase in water supply.

The HYDRUS-2D model was experimentally verified for water and salinity distribution during the profile establishment stage (33 days) of almond under pulsed and continuous drip irrigation. The model simulated values of water content obtained at different lateral distances (0, 20, 40, 60, 100 cm) from a dripper at 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 120, 140 and 160 cm soil depths at different times (5, 12, 19, 26 and 33 days of profile establishment) were compared with neutron probe measured values under both irrigation scenarios. The model closely predicted water content distribution at all distances, times and soil depths as RMSE values ranged between 0.017 and 0.049. The measured mean soil water salinity (ECsw) at 25 cm from the dripper at 30, 60, 90 and 150 cm soil depth also matched well with the predicted values. A correlation of 0.97 in pulsed and 0.98 in continuous drip systems with measured values indicated the model closely predicted total salts in the root zone. Thus, HYDRUS-2D successfully simulated the change in soil water content and soil water salinity in both the wetting pattern and in the flow domain. The initial mean ECsw below the dripper in pulsed (5.25 dSm−1) and continuous (6.07 dSm−1) irrigations decreased to 1.31 and 1.36 dSm−1, respectively, showing a respective 75.1 and 77.6% decrease in the initial salinity. The power function [y = ax −b ] best described the mathematical relationship between salt removal from the soil profile as a function of irrigation time under both irrigation scenarios. Contrary to other studies, higher leaching fraction (6.4–43.1%) was recorded in pulsed than continuous (1.1–35.1%) irrigation with the same amount of applied water which was brought about by the variation in initial soil water content and time of irrigation application. It was pertinent to note that a small (0.012) increase in mean antecedent water content (θ i ) brought about 8.25–9.06% increase in the leaching fraction during the profile establishment irrespective of the emitter geometry, discharge rate, and irrigation scenario. Under similar θ i , water applied at a higher discharge rate (3.876 Lh−1) has resulted in slightly higher leaching fraction than at a low discharge rate (1.91 Lh−1) under pulsing only owing to the variation in time of irrigation application. The influence of pulsing on soil water content, salinity distribution, and drainage flux vanished completely when irrigation was applied daily on the basis of crop evapotranspiration (ETc) with a suitable leaching fraction. Therefore, antecedent soil water content and scheduling or duration of water application play a significant role in the design of drip irrigation systems for light textured soils. These factors are the major driving force to move water and solutes within the soil profile and may influence the off-site impacts such as drainage flux and pollution of the groundwater.

In a global scenario of climate change, water scarcity and population growth, it is imperative to optimize crop water management. One way is by calibrating a physically based crop evapotranspiration (ET) model, in the so-called one-step approach; as opposed to the two-step approach that uses reference evapotranspiration and crop coefficients. The Penman–Monteith (Symposium of the society for experimental biology, the state and movement of water in living organisms, Academic Press, Inc., New York; Monteith, Symposium of the society for experimental biology, the state and movement of water in living organisms, Academic Press, Inc., New York, 1965) ET model uses a bulk surface resistance (rs) term. This variable describes the resistance (stomatal, leaf, and canopy) to crop water transpiration and water evaporation from the soil surface. If the crop is not transpiring at a potential rate the rs resistance depends on the water status of the soil and vegetation. The stomatal resistance is influenced by climate and by water availability. However, this influence is different from crop to crop. The resistance increases when the crop is stressed and when the soil water availability limits ET. In this study, surface resistance was parameterized for grain maize considering a number of plant and environmental variables for water stressed and non-stressed conditions. The independent explanatory variables that facilitated a good calibration of rs, on a half-hourly basis, were: net radiation, photosynthetic active radiation, aerodynamic resistance, crop height, and leaf area index. The application of the obtained “rs” model (based on the variables mentioned above) resulted in maize ET (mm 30-min−1) estimation error of less than 1 ± 10% when evaluated with eddy covariance based ET data. This result is evidence that it is possible to calculate maize ET with a small associated error at very small time scales, for water deprived and advective conditions, using the one-step ET approach.

The effect of irrigation on tillering and tiller mortality in varieties of wheat (Triticum aestivum and T. durum), triticale and barley was studied under field conditions. Low temperature in the early stages of growth promoted production of tillers whereas increase in temperature during extension growth phase increased tiller mortality. More than 1000 tillers m−2 were produced with five irrigations but 40% or more died. With limited water availability tiller production was reduced but so was their mortality. Grain yield in wheat and triticale was positively correlated with productive tillers and negatively correlated with the maximum number of tillers produced in wheat and barley grown under limited irrigation conditions. Varieties with a capacity to produce fewer tillers were identified. Some of them proved more stable in yield. No correlation was found between tiller number and grain yield in the frequently irrigated treatment.

Water retention θ(h) and hydraulic conductivity K(h) are mandatory soil hydraulic properties (SHP) for consistent hydrological modeling and for an efficient irrigation management. Most commonly, SHP are determined by conventional methods (CM), based on hydrostatic equilibrium and the independent measurement of saturated hydraulic conductivity, which is used as a matching point for K(h) function. Alternatively, inverse-modeling experiments allow simultaneous parameter estimation using data from transient water flow conditions. This study aims to investigate the implications of these two protocols on simulations of soil water content (θ) and crop evapotranspiration (ET), and how they affect irrigation management and scheduling for different irrigation systems and crops. The SHP obtained from CM and IM were used in simulations with the Richards equation-based SWAP hydrological model. ET and θ were simulated for passion fruit under high-frequency drip irrigation and for pasture under conventional sprinkler irrigation. The simulation performance was evaluated using measured θ and ET obtained with passion fruit under drip irrigation. Both methods (CM and IM) gave similar results in the wetter range, while in the drier soil, CM estimated higher θ than IM. These differences affected the simulated ET and irrigation scheduling. Regarding the ET and θ simulations, for the drip irrigation scenario, in which the water content in the root zone remains near saturation, both SHP determination methods produced similar results. On the other hand, for scenarios with larger irrigation intervals such as sprinkler irrigation, simulations were affected significantly, with CM likely biasing irrigation frequency and depth.

Control engineering approaches may be applied to irrigation management to make better use of available irrigation water. These methods of irrigation decision-making are being developed to deal with spatial and temporal variability in field properties, data availability and hardware constraints. One type of control system is advanced process control which, in an irrigation context, refers to the incorporation of multiple aspects of optimisation and control. Hence, advanced process control is particularly suited to the management of site-specific irrigation. This paper reviews applications of advanced process control in irrigation: mathematical programming, linear quadratic control, artificial intelligence, iterative learning control and model predictive control. From the literature review, it is argued that model-based control strategies are more realistic in the soil–plant–atmosphere system using process simulation models rather than using ‘black-box’ crop production models. It is also argued that model-based control strategies can aim for specific end of season characteristics and hence may achieve optimality. Three control systems are identified that are robust to data gaps and deficiencies and account for spatial and temporal variability in field characteristics, namely iterative learning control, iterative hill climbing control and model predictive control: from consideration of these three systems it is concluded that the most appropriate control strategy depends on factors including sensor data availability and grower’s specific performance requirements. It is further argued that control strategy development will be driven by the available sensor technology and irrigation hardware, but also that control strategy options should also drive future plant and soil moisture sensor development.

The spatial and temporal variations commonly found in the infiltration characteristic for surface-irrigated fields are a major physical constraint to achieve higher irrigation application efficiencies. Substantial work has been directed towards developing methods to estimate the infiltration characteristics of soil from irrigation advance data. However, none of the existing methods are entirely suitable for use in real-time control. The greatest limitation is that they are data intensive. A new method that uses a model infiltration curve (MIC) is proposed. In this method a scaling process is used to reduce the amount of data required to predict the infiltration characteristics for each furrow and each irrigation event for a whole field. Data from 44 furrow irrigation events from two different fields were used to evaluate the proposed method. Infiltration characteristics calculated using the proposed method were compared to values calculated from the full advance data using the INFILT computer model. The infiltration curves calculated by the proposed method were of similar shape to the INFILT curves and gave similar values for cumulative infiltration up to the irrigation advance time for each furrow. More importantly the statistical properties of the two sets of infiltration characteristics were similar. This suggests that they would return equivalent estimates of irrigation performance for the two fields and that the proposed method could be suitable for use in real-time control.