A reexamination of the crop water stress index

Summary Hand-held infrared radiometers, developed during the past decade, have extended the measurement of plant canopy temperatures from individual leaves to entire plant canopies. Canopy temperatures are determined by the water status of the plants and by ambient meteorological conditions. The crop water stress index (CWSI) combines these factors and yields a measure of plant water stress. Two forms of the index have been proposed, an empirical approach as reported by Idso et al. (1981), and a theoretical approach reported by Jackson et al. (1981). Because it is simple and requires only three variables to be measured, the empirical approach has received much attention in the literature. It has, however received some criticism concerning its inability to account for temperature changes due to radiation and windspeed. The theoretical method is more complicated in that it requires these two additional variables to be measured, and the evaluation of an aerodynamic resistance, but it will account for differences in radiation and windspeed. This report reexamines the theoretical approach and proposes a method for estimating an aerodynamic resistance applicable to a plant canopy. A brief history of plant temperature measurements is given and the theoretical basis for the CWSI reviewed.     

Crop water stress index is a sensitive water stress indicator in pistachio trees

Regulated deficit irrigation (RDI) strategies, often applied in tree crops, require precise monitoring methods of water stress. Crop water stress index (CWSI), based on canopy temperature measurements, has shown to be a good indicator of water deficits in field crops but has seldom been used in trees. CWSI was measured on a continuous basis in a Central California mature pistachio orchard, under full and deficit irrigation. Two treatments—control, returning the full evapotranspiration (ET_c) and RDI—irrigated with 40% ET_c during stage 2 of fruit grow (shell hardening). During stage 2, the canopy temperature—measured continuously with infrared thermometers (IRT)—of the RDI treatment was consistently higher than the control during the hours of active transpiration; the difference decreasing after irrigation. The non-water-stressed baseline (NWSB), obtained from clear-sky days canopy–air temperature differential and vapour pressure deficit (VPD) in the control treatment, showed a marked diurnal variation in the intercept, mainly explained by the variation in solar radiation. In contrast, the NWSB slope remained practically constant along the day. Diurnal evolution of calculated CWSI was stable and near zero in the control, but showed a clear rising diurnal trend in the RDI treatment, increasing as water stress increased around midday. The seasonal evolution of the CWSI detected large treatment differences throughout the RDI stress period. While the CWSI in the well-irrigated treatment rarely exceeded 0.2 throughout the season, RDI reached values of 0.8–0.9 near the end of the stress period. The CWSI responded to irrigation events along the whole season, and clearly detected mild water stress, suggesting extreme sensitivity to variations in tree water status. It correlated well with midday leaf water potential (LWP), but was more sensitive than LWP at mild stress levels. We conclude that the CWSI, obtained from continuous nadir-view measurements with IRTs, is a good and very sensitive indicator of water stress in pistachio. We recommend the use of canopy temperature measurements taken from 1200 to 1500 h, together with the following equation for the NWSB: (T _c − T _a) = −1.33·VPD + 2.44. Measurements of canopy temperature with VPD < 2 kPa are likely to generate significant errors in the CWSI calculation and should be avoided.     

Evaluation of crop water stress index for LEPA irrigated corn

This study was designed to evaluate the crop water stress index (CWSI) for low-energy precision application (LEPA) irrigated corn (Zea mays L.) grown on slowly-permeable Pullman clay loam soil (fine, mixed, Torrertic Paleustoll) during the 1992 growing season at Bushland, Tex. The effects of six different irrigation levels (100%, 80%, 60%, 40%, 20%, and 0% replenishment of soil water depleted from the 1.5-m soil profile depth) on corn yields and the resulting CWSI were investigated. Irrigations were applied in 25 mm increments to maintain the soil water in the 100% treatment within 60–80% of the “plant extractable soil water” using LEPA technology, which wets alternate furrows only. The 1992 growing season was slightly wetter than normal. Thus, irrigation water use was less than normal, but the corn dry matter and grain yield were still significantly increased by irrigation. The yield, water use, and water use efficiency of fully irrigated corn were 1.246 kg/m², 786 mm, and 1.34 kg/m³, respectively. CWSI was calculated from measurements of infrared canopy temperatures, ambient air temperatures, and vapor pressure deficit values for the six irrigation levels. A “non-water-stressed baseline” equation for corn was developed using the diurnal infrared canopy temperature measurements as T _c–T _a = 1.06–2.56 VPD, where T _c was the canopy temperature (°C), Ta was the air temperature (°C) and VPD was the vapor pressure deficit (kPa). Trends in CWSI values were consistent with the soil water contents induced by the deficit irrigations. Both the dry matter and grain yields decreased with increased soil water deficit. Minimal yield reductions were observed at a threshold CWSI value of 0.33 or less for corn. The CWSI was useful for evaluating crop water stress in corn and should be a valuable tool to assist irrigation decision making together with soil water measurements and/or evapotranspiration models. Received: 19 May 1998     

Application of a new method to evaluate crop water stress index

Optimum water management and irrigation require timely detection of crop water condition. Usually crop water condition can be indicated by crop water stress index (CWSI), which can be estimated based on the measurements of either soil water or plant status. Estimation of CWSI by canopy temperature is one of them and has the potential to be widely applied because of its quick response and remotely measurable features. To calculate CWSI, the conventional canopy-temperature-based model (Jackson’s model) requires the measurement or estimation of the canopy temperature, the maximum canopy temperature (T _cu), and the minimum canopy temperature (T _cl). Because extensive measurements are necessary to estimate T _cu and T _cl, its application is limited. In this study, by introducing the temperature of an imitation leaf (a leaf without transpiration, T _p) and based on the principles of energy balance, we studied the possibility to replace T _cu by T _p and reduce the included parameters for CWSI calculation. Field experiments were carried out in a winter wheat (Triticum aestivum L.) field in Luancheng area, Hebei Province, the main production area of winter wheat in China. Six irrigation treatments were established and soil water content, leaf water potential, soil evaporation rate, plant transpiration rate, biomass, yield, and regular meteorological variables of each treatment were measured. Results indicate that the values of T _cu agree with the values of T _p with a regression coefficient r=0.988. While the values of CWSI estimated by the use of T _p are in agreement with CWSI by Jackson’s method, with a regression coefficient r=0.999. Furthermore, CWSI estimated by the use of T _p has good relations with soil water content and leaf water potential, showing that the estimated CWSI by T _p is a good indicator of soil water and plant status. Therefore, it is concluded that T _cu can be replaced by T _p and the included parameters for CWSI calculation can be significantly reduced by this replacement.     

Development of crop water stress index of wheat crop for scheduling irrigation using infrared thermometry

This study was conducted to develop the relationship between canopy-air temperature difference and vapour pressure deficit for no stress condition of wheat crop (baseline equations), which was used to quantify crop water stress index (CWSI) to schedule irrigation in winter wheat crop (Triticum aestivum L.). The randomized block design (RBD) was used to design the experimental layout with five levels of irrigation treatments based on the percentage depletion of available soil water (ASW) in the root zone. The maximum allowable depletion (MAD) of the available soil water (ASW) of 10, 40 and 60 per cent, fully wetted (no stress) and no irrigation (fully stressed) were maintained in the crop experiments. The lower (non-stressed) and upper (fully stressed) baselines were determined empirically from the canopy and ambient air temperature data obtained using infrared thermometry and vapour pressure deficit (VPD) under fully watered and maximum water stress crop, respectively. The canopy-air temperature difference and VPD resulted linear relationships and the slope (m) and intercept (c) for lower baseline of pre-heading and post-heading stages of wheat crop were found m = −1.7466, c = −1.2646 and m = −1.1141, c = −2.0827, respectively. The CWSI was determined by using the developed empirical equations for three irrigation schedules of different MAD of ASW. The established CWSI values can be used for monitoring plant water status and planning irrigation scheduling for wheat crop.     

Daylight crop water stress index for continuous monitoring of water status in apple trees

We studied the suitability of empirical crop water stress index (CWSI) averaged over daylight hours (CWSI_d) for continuous monitoring of water status in apple trees. The relationships between a midday CWSI (CWSI_m) and the CWSI_d and stem water potential (ψ _stem), and soil water deficit (SWD) were investigated. The treatments were: (1) non-stressed where the soil water was close to field capacity and (2) mildly stressed where SWD fluctuated between 0 and a maximum allowable depletion (MAD of 50 %). The linear relationship between canopy and air temperature difference (ΔT) and air vapor pressure deficit (VPD) averaged over daylight hours resulted in a non-water-stressed baseline (NWSBL) with higher correlation (?T = ?0.97 VPD – 0.46, R ² = 0.78, p < 0.001) compared with the conventional midday approach (?T = ?0.59 VPD – 0.67, R ² = 0.51, p < 0.001). Wind speed and solar radiation showed no significant effect on the daylight NWSBL. There was no statistically meaningful relationship between midday ψ _stem and CWSI_m. The CWSI_d agreed well with SWD (R ² = 0.70, p < 0.001), while the correlation between SWD and CWSI_m was substantially weaker (R ² = 0.38, p = 0.033). The CWSI_d exhibited high sensitivity to mild variations in the soil water content, suggesting it as a promising indicator of water availability in the root zone. The CWSI_d is stable under transitional weather conditions as it reflects the daily activity of an apple crop.     

The effect of soil surface temperature on the crop water stress index

Summary A coupled soil-vegetation energy balance model which treats the canopy foliage as one layer and the soil surface as another layer was validated againt a set of field data and compared with a single-layer model of a vegetation canopy. The two-layer model was used to predict the effect of increases in soil surface temperature (T _s ) due to the drying of the soil surface, on the vegetation temperature (T _v ). In the absence of any change in stomatal resistance the impact of soil surface drying on the Crop Water Stress Index (CSWI) calculated from T _v was predicted. Field data came from a wheat crop growing on a frequently irrigated plot (W) and a plot left un watered (D) until the soil water depletion reached 100 mm. Vegetation and soil surface temperatures were measured by infrared thermometers from tillering to physiological maturity, with meteorological variables recorded simultaneously. Stomatal resistances were measured with a diffusion porometer intensively over five days when the leaf area index was between 5 and 8. The T _v predicted by the single-layer and the two-layer models accounted for 87% and 88% of the variance of measured values respectively, and both regression lines were close to the 11 relationship. Study of the effect of T _s on the CWSI with the two-layer model indicated that the CWSI was sensitive to changes in T _s . The overestimation of crop water stress calculated from the CWSI was predicted to be greater at low leaf area indices and high levels of stomatal resistance. The implications for this bias when using the CWSI for irrigation scheduling are discussed.List of Symbols C Sensible heat flux from the soil-vegetation system (W m^–2) - c _{l shade} Mean stomatal conductance of the shaded leaf area (m s^–1) - c _{l sun} Mean stomatal conductance of the sunlit leaf area (m s^–1) - c _max Maximum stomatal conductance (m s^–1) - c ₀ Minimum stomatal conductance (m s^–1) - C _p Specific heat at constant pressure (J kg^–1 °C^–1) - C _s Sensible heat flux from the soil (W m^–2) - C _v Sensible heat flux from the vegetation (W m^–2) - c _v Bulk stomatal conductance of the vegetation (m s^–1) - CWSI Crop Water Stress Index (dimensionless) - e _a Vapor pressure at the reference height (kPa) - e _b Vapor pressure at the virtual source/sink height of heat exchange (kPa) - e ₀ ^* Saturated vapor pressure at T ₀ (kPa) - e _s Vapor pressure at the soil surface (kPa) - e _v ^* Saturated vapor pressure at T _v (kPa) - G Soil heat flux (Wm^–2) - GLAI Green leaf area index (dimensionless) - GLAI_shade Green shaded leaf area index (dimensionless) - GLAI_sun Green sunlit leaf area index (dimensionless) - k Extinction coefficient for photosynthetically active radiation (dimensionless) - k ₁ Damping exponent for Eq. A 5 (m² W^–1) - LAI Leaf area index (dimensionless) - LE Latent heat flux from the soil-vegetation system (W m^–2) - LE _s Latent heat flux from the soil (W m^–2) - LE _v Latent heat flux from the vegetation (W m^–2) - p _a Density of air (kg m^–3) - PAR_a Photosynthetically active radiation above the canopy (W m^–2) - PAR_u Photosynthetically active radiation under the canopy (W m^–2) - r _a Aerodynamic resistance (s m^–1) - r _b Heat exchange resistance between the vegetation and the adjacent air boundary layer (s m^–1) - r _c Bulk stomatal resistance of the vegetation (s m^–1) - R _n Net radiation above the canopy (W m^–2) - R _s Net radiation flux at the soil surface (W m^–2) - r _st Mean stomatal resistance of leaves in the canopy (s m^–1) - R _v Net radiation absorbed by the vegetation (W m^–2) - r _w Heat exchange resistance between the soil surface and the boundary layer (s m^–1) - S Photosynthetically active radiation on the shaded leaves (W m^–2) - S _d Diffuse photosynthetically active radiation (W m ^–2) - S ₀ Photosynthetically active radiation on a surface perpendicular to the beams (W m^–2) - T _a Air temperature at the reference height (°C) - T _b Temperature at the virtual source/sink height of heat exchange (°C) - T ₀ Aerodynamic temperature (°C) - T _s Soil surface temperature (°C) - T _v Vegetation temperature (°C) - w ₀ Single scattering albedo (dimensionless) - Psychrometric constant (kPa °C) - ₀ Cosine of solar zenith angle (dimensionless)     

Evaluation of a crop water stress index for irrigation scheduling of bermudagrass

This study was conducted to assess crop water stress index (CWSI) of bermudagrass used widely on the recreational sites of the Mediterranean Region and to study the possibilities of utilization of infrared thermometry to schedule irrigation of bermudagrass. Four different irrigation treatments were examined: 100% (I₁), 75% (I₂), 50% (I₃), and 25% (I₄) of the evaporation measured in a Class A pan. In addition, a non-irrigated treatment was set up to determine CWSI values. The status of soil water content and pressure was monitored using a neutron probe and tensiometers. Meanwhile the canopy temperature of bermudagrass was measured with the infrared thermometry. The empirical method was used to compute the CWSI values. In this study, the visual quality of bermudagrass was monitored seasonally using a color scale. The best visual quality was obtained from I₁ and I₂ treatments. Average seasonal CWSI values were determined as 0.086, 0.102, 0.165, and 0.394 for I₁, I₂, I₃, and I₄ irrigation treatments, respectively, and 0.899 for non-irrigated plot. An empirical non-linear equation, Qave=1+⌊6[1+(4.853 CWSIave)^2.27]^−0.559⌋$Q_{\text{ave}}=1+⌊6{[1+{(4.853\text{CWS}{\text{I}}_{\text{ave}})}^{2.27}]}^{-0.559}⌋$, was deduced by fitting to measured data to find a relation between quality and average seasonal CWSI values. It was concluded that the CWSI could be used as a criterion for irrigation timing of bermudagrass. An acceptable color quality could be sustained seasonally if the CWSI value can be kept about 0.10.     

Water quality implications of raising crop water productivity

Because of a growing and more affluent population, demand for agricultural products will increase rapidly over the coming decades, with serious implications for agricultural water demand. Symptoms of water scarcity are increasingly apparent, threatening ecosystem services and the sustainability of food production. Improved water productivity will reduce the additional water requirements in agriculture. However, there is a tradeoff between the quantity of water used in agriculture and the quality of return flow. Where yields are low due to limited nitrogen (N) and water supply, water productivity can be enhanced through higher fertilizer applications and improved water management. This limits the amount of additional water needed for increased food demand, thus leaving more water for environmental requirements. But it also increases the amount of nitrate (NO₃–N) leaching, thus adversely affecting the water quality of return flows.This paper quantifies the tradeoff between enhanced water productivity and NO₃–N leaching and shows the importance of the right management of water and N applications. Using the Decision Support System for Agro-technology Transfer (DSSAT) crop model, several scenarios combining different water and N application regimes are examined for maize (Zea mays L.) in Gainesville, FL, USA. Without adequate water, nitrogen use efficiency (NUE) remains low, resulting in substantial NO₃–N leaching. Too much water leads to excessive NO₃–N leaching and lower water productivity. The lack of N is a cause of low water productivity but too much of it leads to lower NUE and higher losses. The paper concludes that increased NO₃–N leaching is an inevitable by-product of increased water productivity, but its adverse impacts can greatly be reduced by better management of water and N application. The paper briefly shows that leaching can be reduced and water productivity increased by split application of N-fertilizer. This implies that improved water and nutrient management at field- and scheme-level is a prerequisite to limit adverse impacts of agriculture on ecosystems, now and especially in the future.     

Minimizing instrumentation requirement for estimating crop water stress index and transpiration of maize

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.     

Variable upper and lower crop water stress index baselines for corn and soybean

Upper and lower crop water stress index (CWSI) baselines adaptable to different environments and times of day are needed to facilitate irrigation scheduling with infrared thermometers. The objective of this study was to develop dynamic upper and lower CWSI baselines for corn and soybean. Ten-minute averages of canopy temperatures from corn and soybean plots at four levels of soil water depletion were measured at North Platte, Nebraska, during the 2004 growing season. Other variables such as solar radiation (R _s), air temperature (T _a), relative humidity (RH), wind speed (u), and plant canopy height (h) were also measured. Daily soil water depletions from the research plots were estimated using a soil water balance approach with a computer model that used soil, crop, weather, and irrigation data as input. Using this information, empirical equations to estimate the upper and lower CWSI baselines were developed for both crops. The lower baselines for both crops were functions of h, vapor pressure deficit (VPD), R _s, and u. The upper baselines did not depend on VPD, but were a function of R _s and u for soybean, and R _s, h, and u for corn. By taking into account all the variables that significantly affected the baselines, it should be possible to apply them at different locations and times of day. The new baselines developed in this study should facilitate the application of the CWSI method as a practical tool for irrigation scheduling of corn and soybean.     

Increasing water productivity in crop production—A synthesis

Scarcity of water resources and growing competition for water in many sectors reduce its availability for irrigation. Effective management of water for crop production in water scarce areas requires efficient approaches. Increasing crop water productivity (WP) and drought tolerance by genetic improvement and physiological regulation may be the means to achieve efficient and effective use of water. But only high water productivity values carry little or no interest if they are not associated with high or acceptable yields. Such association of high (or moderate) productivity values with high (or moderate) yields has important implications on the effective use of water. In this paper we discussed the factors affecting water productivity, and the possible techniques to improve water productivity. A single approach would not be able to tackle the forthcoming challenge of producing more food and fiber with limited or even reduced available water. Combining biological water-saving measures with engineering solutions (water saving irrigation method, deficit irrigation, proper deficit sequencing, modernization of irrigation system, etc.), and agronomic and soil manipulation (seed priming, seedling age manipulation, direct- or wet-seeded rice, proper crop choice, integrating agriculture and aquaculture, increasing soil fertility, addition of organic matter, tillage and soil mulching, etc.) may solve the problem to a certain extent. New scientific information is needed to improve the economic gains of WP because the future improvements in WP seem to be limited by economic rather than a lack of technological means.     

中国灌溉水粮食生产率及其时空变异

为了评价农业引水总量的生产效益,从全国459个主要灌区的实际灌溉水和粮食生产数据入手,计算、比较了1998,2005和2010年31个省区的灌溉水粮食生产率,利用空间自相关分析方法对1998—2010年中国灌溉水粮食生产率的时空变异规律进行探究.结果显示：各省区灌溉水粮食生产率呈增大趋势,代表年的中国均值为1.03 kg/m3,最大、最小值分别为河南的2.15kg/m3和海南的0.25 kg/m3,区域间差异较大;灌溉水粮食生产率在空间上存在显著的聚集现象,聚集程度随时间变化不明显,高值省区以黄淮海平原为核心集中分布,长江以南则密集了低值省区;江西、安徽及重庆灌溉水粮食生产率的变化幅度与其相邻省区不同步,造成了局部分异特征的变化.分析了中国灌溉水粮食生产率格局的形成及其随时间变化的原因.     

Crop coefficient, yield response to water stress and water productivity of teff (Eragrostis tef (Zucc.)

In the semi-arid region of Tigray, Northen Ethiopia a two season experiment was conducted to measure evapotranspiration, estimate yield response to water stress and derive the crop coefficient of teff using the single crop coefficient approach with simple, locally made lysimeters and field plots. During the experiment we also estimated the water productivity of teff taking into account long-term rainfall probability scenarios and different levels of farmers’ skills. During the experimental seasons (2008 and 2009), the average potential evapotranspiration of teff ranged from 260 to 317 mm. The total seasonal water requirement of teff was found to lower in contrast to the assumptions of regional agronomists that teff water requirement is comparable to that of wheat and barley (375 mm). The average single crop coefficient values (k_c) for the initial, mid and late season stages of teff were 0.8-1, 0.95-1.1 and 0.4-0.5, respectively. The seasonal yield response to water stress was 1.04, which indicates that teff exhibits a moderately sensitive and linear response to water stress. The results suggest that teff is likely to give significantly higher grain yield when a nearly optimal water supply is provided. The study showed that, in locations where standard equipment is not affordably available, indicative (rough) crop evapotranspiration values can be obtained by using field plots and employing locally made lysimeters. The difference in economic water productivity (EWP) and the crop water productivity (CWP) for teff were assessed under very wet, wet, normal, dry and very dry scenarios. In addition two groups of farmers were evaluated, a moderately (I) and a highly skilled (II) group. The results showed that higher EWP and CWP were obtained under very wet scenario than very dry scenario. There was also a 22% increase in EWP and CWP under group II compared to group I farmers. The increase was due to a 22% reduction in unwanted water losses achieved through use of improved technology and better irrigation skills. Both EWP and CWP can be used to evaluate the pond irrigation water productivity (IWP) for a given climate, crop and soil type, and skill and technology level of the farmer. For special crops like teff extra criteria may be needed in order to properly evaluate the pond irrigation water productivity. During the experimental seasons, a high IWP for teff was attained when about 90% of the optimal water need of the crop was met. IWP can be used as an indicator as how much supplementary irrigation has to be applied in relation to the rainfall and other sources of water supply in order to assure greatest yield from a total area. However, the supplemental irrigation requirement of the crops may vary with season due to seasonal rainfall variability.     

Application of GIS and crop growth models in estimating water productivity

Tighter competition in water use is projected in the future. As water demand increases, water related problems could happen along the way. Accordingly, issues on water availability and use could be crucial to study to search for ways and means on how to cope up with the present trend. Sound water management practices could play a key role to the solution of problems relating to water availability and use. Water use in agriculture is considered the highest among other water users because of the water intensive processes involved in it. Aside from the crop water requirements, water loss, which are not beneficial to crop processes can add a huge volume to the total water usage in agriculture. Base from this argument, there could be greater possibility to save water from agriculture, which can be used for other purposes thereafter. To explore this option, analysis at the crop level could be beneficial. However, the issue of scaling should be also considered because the knowledge on the field scale could not be generally true in the basin scale. The objective of the study was to apply crop growth simulation models coupled with geographic information system (GIS) to analyze water productivity, which is an indicator of water use efficiency, at the basin scale.The methodology was applied to Laoag River Basin in Ilocos Norte, Philippines to study water productivity in spatial and temporal dimensions. Three crops were considered in the analysis: rice, maize and peanut. Simulations were done for both existing and potential agricultural areas. The potential productions of the selected crops from October 1996–September 1997 were used as bases in determining water productivity for the three cropping seasons (CS) being considered in the study. Water-limited productions were simulated for each of the crops, for each of the CS in the basin. Moreover, a marginal productivity analysis was done to determine the potential of water for crop production in the basin. Subsequently, the significance of irrigation was emphasized in the analysis when availability of water, and the combination of water and nitrogen (N) are limiting, respectively. The results showed that the spatio-temporal analysis of water productivity could provide substantial information for water saving opportunities and, hence, strategies in irrigated agriculture.     

Cover crop evapotranspiration under semi-arid conditions using FAO dual crop coefficient method with water stress compensation

Cover cropping is a common agro-environmental tool for soil and groundwater protection. In water limited environments, knowledge about additional water extraction by cover crop plants compared to a bare soil is required for a sustainable management strategy. Estimates obtained by the FAO dual crop coefficient method, compared to water balance-based data of actual evapotranspiration, were used to assess the risk of soil water depletion by four cover crop species (phacelia, hairy vetch, rye, mustard) compared to a fallow control. A water stress compensation function was developed for this model to account for additional water uptake from deeper soil layers under dry conditions. The average deviation of modelled cumulative evapotranspiration from the measured values was 1.4% under wet conditions in 2004 and 6.7% under dry conditions in 2005. Water stress compensation was suggested for rye and mustard, improving substantially the model estimates. Dry conditions during full cover crop growth resulted in water losses exceeding fallow by a maximum of +15.8% for rye, while no substantially higher water losses to the atmosphere were found in case of evenly distributed rainfall during the plant vegetation period with evaporation and transpiration concentrated in the upper soil layer. Generally the potential of cover crop induced water storage depletion was limited due to the low evaporative demand when plants achieved maximum growth. These results in a transpiration efficiency being highest for phacelia (5.1 g m⁻² mm⁻¹) and vetch (5.4 g m⁻² mm⁻¹) and substantially lower for rye (2.9 g m⁻² mm⁻¹) and mustard (2.8 g m⁻² mm⁻¹). Taking into account total evapotranspiration losses, mustard performed substantially better. The integration of stress compensation into the FAO crop coefficient approach provided reliable estimates of water losses under dry conditions. Cover crop species reducing the high evaporation potential from a bare soil surface in late summer by a fast canopy coverage during early development stages were considered most suitable in a sustainable cover crop management for water limited environments.     

Magnetic treatment of irrigation water: Its effects on vegetable crop yield and water productivity

This study examines whether there are any beneficial effects of magnetic treatment of different irrigation water types on water productivity and yield of snow pea, celery and pea plants. Replicated pot experiments involving magnetically treated and non-magnetically treated potable water (tap water), recycled water and saline water (500 ppm and 1000 ppm NaCl for snow peas; 1500 ppm and 3000 ppm for celery and peas) were conducted in glasshouse under controlled environmental conditions during April 2007 to December 2008 period at University of Western Sydney, Richmond Campus (Australia). A magnetic treatment device with its magnetic field in the range of 3.5-136 mT was used for the magnetic treatment of irrigation water. The analysis of the data collected during the study suggests that the effects of magnetic treatment varied with plant type and the type of irrigation water used, and there were statistically significant increases in plant yield and water productivity (kg of fresh or dry produce per kL of water used). In particular, the magnetic treatment of recycled water and 3000 ppm saline water respectively increased celery yield by 12% and 23% and water productivity by 12% and 24%. For snow peas, there were 7.8%, 5.9% and 6.0% increases in pod yield with magnetically treated potable water, recycled water and 1000 ppm saline water, respectively. The water productivity of snow peas increased by 12%, 7.5% and 13% respectively for magnetically treated potable water, recycled water and 1000 ppm saline water. On the other hand, there was no beneficial effect of magnetically treated irrigation water on the yield and water productivity of peas. There was also non-significant effect of magnetic treatment of water on the total water used by any of the three types of vegetable plants tested in this study. As to soil properties after plant harvest, the use of magnetically treated irrigation water reduced soil pH but increased soil EC and available P in celery and snow pea. Overall, the results indicate some beneficial effect of magnetically treated irrigation water, particularly for saline water and recycled water, on the yield and water productivity of celery and snow pea plants under controlled environmental conditions. While the findings of this glasshouse study are interesting, the potential of the magnetic treatment of irrigation water for crop production needs to be further tested under field conditions to demonstrate clearly its beneficial effects on the yield and water productivity.     

Plant indicators of wheat and soybean crop water stress

Summary The onset of water stress within a crop is defined as the time at which the rate of water loss declines below that of a well watered crop in the same locality. The relation to the onset of water stress and soil water status of several readily measured plant parameters was investigated in crops of wheat and soybeans over three years. Evapotranspiration ET was monitored with weighing lysimeters. A noticeable decline in the rate of ET for both wheat and soybeans was detected once 20% to 30% of the total plant available water PAW remained in the 1 m deep lysimeter soil profile. Extension growth of wheat declined when PAW was 33% and 34% in two years of measurement. In soybeans, the decline in the rate of leaf extension coincided with the decline in the rate of ET. Midmorning measurement of exposed leaf water potential _L, covered leaf water potential _CL and covered plant leaf water potential _CP yielded similar results for both wheat and soybeans. Day-to-day variability was least in _CP and most in _L. Values of _CP, _L and _CL decreased rapidly with PAW < 30%. Daily values of leaf diffusive conductance were variable but there was a general decline in conductance with PAW < 30%. It is suggested that _CL may be the easiest and most reliable parameter to monitor as a means of detecting the onset of stress. The results indicated that PAW levels in the root zone of 50% for wheat and 30% for soybean probably do not affect extension growth or plant water status parameters and can thus be used as criteria for irrigation scheduling.Seconded from the Water Research Commission, Pretoria; present address: CSIRO, Division of Irrigation Research, Griffith, N SW 2680, Australia     

GEPIC – modelling wheat yield and crop water productivity with high resolution on a global scale

With population growth and economic development, the agricultural sector is facing the challenge to produce more food with less water. Crop water productivity (CWP) is important for understanding water–food relationships. It also provides a basis for the assessment of water use efficiency embodied in global food trade. However, traditional methods are not sufficient for estimating CWP on a global scale considering large spatial and temporal variations across different geographical locations. In this paper, a GIS-based EPIC model (GEPIC) is developed and tested to estimate wheat (Triticum aestivum L.) yield and CWP at a grid resolution of 30′ on the land surface. A comparison between simulated yields and FAO statistical yields in 102 countries over 10 years shows a good agreement. The simulated CWP is also mostly in line with the CWP reported in the literature.