Using ESAP software for predicting the spatial distributions of NDVI and transpiration of cotton

Observations of the normalized difference vegetation index (NDVI) from aerial imagery can be used to infer the spatial variability of basal crop coefficients (Kcb), which in turn provide a means to estimate variable crop water use within irrigated fields. However, monitoring spatial Kcb at sufficient temporal resolution using only aerial acquisitions would likely not be cost-effective for growers. In this study, we evaluated a model-based sampling approach, ESAP (EC_e Sampling, Assessment, and Prediction), aimed at reducing the number of seasonal aerial images needed for reliable Kcb monitoring. Aerial imagery of NDVI was acquired over an experimental cotton field having two treatments of irrigation scheduling, three plant density levels, and two N levels. During both 2002 and 2003, ESAP software used input imagery of NDVI on three separate dates to select three ground sampling designs having 6, 12, and 20 sampling locations. On three subsequent dates during both the years, NDVI data obtained at the design locations were then used to predict the spatial distribution of NDVI for the entire field. Regression of predicted versus imagery observed NDVI resulted in r² values from 0.48 to 0.75 over the six dates, where higher r² values occurred for predictions made near full cotton cover than those made at partial cover. Prediction results for NDVI were generally similar for all three sample designs. Cumulative transpiration (Tr) for periods from 14 to 28 days was calculated for treatment plots using Kcb values estimated from NDVI. Estimated cumulative Tr using either observed NDVI from imagery or predicted NDVI from ESAP procedures compared favorably with measured cumulative Tr determined from soil water balance measurements for each treatment plot. Except during late season cotton senescence, errors in estimated cumulative Tr were between 3.0% and 7.3% using observed NDVI, whereas they were they were between 3.4% and 8.8% using ESAP-predicted NDVI with the 12 sample design. Thus, employing a few seasonal aerial acquisitions made in conjunction with NDVI measurements at 20 or less ground locations optimally determined using ESAP, could provide a cost-effective method for reliably estimating the spatial distribution of crop water use, thereby improving cotton irrigation scheduling and management.     

Using the depleted fraction to manage the groundwater table in irrigated areas

The depleted fraction, defined as the ratio of ET_actual over total inflow (P + V_c), relates parameters of the water balance of an irrigated area with each other in such a way that the (water) manager obtains information on the rate of change of water stored in the area (soil moisture and groundwater). If the annual average of the depleted fraction equals about 0.6 water storage in the area is stable, while water is stored for lower values of the depleted fraction. If the value of the depleted fraction exceeds about 0.6, the volume of water stored in the area decreases. This decrease is partly due to natural drainage and partly due to capillary rise into the root zone of the irrigated crop. Despite this capillary rise, the actual evapo-transpiration drops below the potential ET-value. For most crops, a decrease of ET by about 25% would result in a higher productivity in terms of yield per cubic meter water. However, the yield per hectare (and thus farm income) would decrease. Management of an irrigation system is recommended in such a way that the monthly values of the depleted fraction range is between 0.5 and 0.8. Such a management rule would provide sufficient water for leaching (at the 0.5 side of the range) and provide high crop yield per unit water consumed (at the 0.8 side).     

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     

Agronomic and economic response to furrow diking tillage in irrigated and non-irrigated cotton (Gossypium hirsutum L.)

The Southeast U.S. receives an average of 1300 mm annual rainfall, however poor seasonal distribution of rainfall often limits production. Irrigation is used during the growing season to supplement rainfall to sustain profitable crop production. Increased water capture would improve water use efficiency and reduce irrigation requirements. Furrow diking has been proposed as a cost effective management practice that is designed to create a series of storage basins in the furrow between crop rows to catch and retain rainfall and irrigation water. Furrow diking has received much attention in arid and semi-arid regions with mixed results, yet has not been adapted for cotton production in the Southeast U.S. Our objectives were to evaluate the agronomic response and economic feasibility of producing cotton with and without furrow diking in conventional tillage over a range of irrigation rates including no irrigation. Studies were conducted at two research sites each year from 2005 to 2007. Irrigation scheduling was based on Irrigator Pro for Cotton software. The use of furrow diking in these studies periodically reduced water consumption and improved yield and net returns. In 2006 and 2007, when irrigation scheduling was based on soil water status, an average of 76 mm ha⁻¹ of irrigation water was saved by furrow diking, producing similar cotton yield and net returns. Furrow diking improved cotton yield an average of 171 kg ha⁻¹ and net return by $245 ha⁻¹ over multiple irrigation rates, in 1 of 3 years. We conclude that furrow diking has the capability to reduce irrigation requirements and the costs associated with irrigation when rainfall is periodic and drought is not severe.     

HydroLOGIC: An irrigation management system for Australian cotton

The worldwide need to improve water use efficiency within irrigated agriculture has been recognised in response to environmental concerns and conflicts in resource use. Within the Australian cotton industry, the imperative to reduce water use and optimise irrigation management through the understanding of risk, using information generated by computerised decision aids was identified and subsequently developed into the HydroLOGIC irrigation management software. This paper summarises the attributes of the HydroLOGIC irrigation management software, with particular emphasis on functionality and its application to irrigation decisions within the Australian cotton industry. The software development process is documented to provide direction for future software application initiatives, with particular emphasis on a process of user feedback, evaluation and support requirements providing direction to software development. On-farm experiments throughout the development period allowed the validation of internal software logic, irrigator decision processes, and the OZCOT cotton growth model. The software demonstrated the ability to improve yield and water use efficiency by optimising strategic and tactical irrigation decisions in the Australian furrow irrigation cotton production system. In 7 of the 11 on-farm experiments conducted, the use of HydroLOGIC helped improve overall field water use efficiency by optimising the timing of irrigation events or by indicating further irrigations would not provide yield or maturity benefits. The paper also presents useful insights into the development of software targeted for irrigation utilising in-field measurements of soil water, crop growth and a crop growth simulation model.     

Water requirements of maize in the middle Heihe River basin, China

As part of an intercomparison study on crop evapotranspiration (ET_c), six methods for estimating ET_c have been applied to maize field in the middle Heihe River basin, China. The ET_c was estimated by the soil water balance and Bowen ratio-energy balance methods while the Priestley-Taylor, Penman, Penman-Monteith and Hargreaves methods were used for estimating the reference evapotranspiration (ET₀). The results showed that the trend of ET_c was very similar, while the differences were significant among the different methods. The variations of ET_c were closely related to the LAI as well as to the meteorological features. The ET_c for the Bowen ratio-energy balance, Penman, Penman-Monteith, soil water balance, Priestley-Taylor and Hargreaves methods totaled 777.75, 693.13, 618.34, 615.67, 560.31 and 552.07 mm, respectively, with the daily mean values for 5.26, 4.68, 4.18, 4.16, 3.79 and 3.73 mm day⁻¹. The Penman-Monteith method provided fairly good estimation of ET_o as compared with the Priestley-Taylor, Penman, Hargreaves methods. By contrast with the Penman-Monteith method, the Bowen ratio-energy balance and Penman methods were 25.8% and 12.0% higher, while the Priestley-Taylor and Hargreaves methods were 9.4% and 10.7% lower, respectively. Therefore, the Hargreaves and Priestley-Taylor methods were the alternative ET_c methods in arid regions of Northwest China.     

Changes in evapotranspiration over irrigated winter wheat and maize in North China Plain over three decades

Evapotranspiration (ET) is an important component of the water cycle at field, regional and global scales. This study used measured data from a 30-year irrigation experiment (1979-2009) in the North China Plain (NCP) on winter wheat (Triticum aestivum L.) and summer maize (Zea mays L.) to analyze the impacts of climatic factors and crop yield on ET. The results showed that grass reference evapotranspiration (ET_o, calculated by FAO Penmen-Monteith method) was relatively constant from 1979 to 2009. However, the actual seasonal ET of winter wheat and maize under well-watered condition gradually increased from the 1980s to the 2000s. The mean seasonal ET was 401.4 mm, 417.3 mm and 458.6 mm for winter wheat, and 375.7 mm, 381.1 mm and 396.2 mm for maize in 1980s, 1990s and 2000s, respectively. The crop coefficient (K_c) was not constant and changed with the yield of the crops. The seasonal average K_c of winter wheat was 0.75 in the 1980s, 0.81 in the 1990s and 0.85 in the 2000s, and the corresponding average grain yield (GY) was 4790 kg ha⁻¹, 5501 kg ha⁻¹ and 6685 kg ha⁻¹. The average K_c of maize was 0.88 in the 1980s, 0.88 in the 1990s and 0.94 in the 2000s, with a GY of 5054 kg ha⁻¹, 7041 kg ha⁻¹ and 7874 kg ha⁻¹, respectively, for the three decades. The increase in ET was not in proportion to the increase in GY, resulting improved water use efficiency (WUE). The increase in ET was possibly related to the increase in leaf stomatal conductance with renewing in cultivars. The less increase in water use with more increase in grain production could be partly attributed to the significant increase in harvest index. The results showed that with new cultivars and improved management practices it was possible to further increase grain production without much increase in water use.     

Effect of sodium and nitrogen on yield function of irrigated maize in southern Portugal

Salinization and nitrate leaching are two of the leading threats to the environment of the European Mediterranean regions. Inefficient use of water and fertilizers has led to a nitrate increase in the aquifers and reduction in crop yields caused by salts. In this study, a triple emitter source irrigation system delivers water, salt (Na⁺), and fertilizer (N) applications to maize (Zea mays L.). The objective of the study was to evaluate the combined effect of saline water and nitrogen application on crop yields in two different textured soils of Alentejo (Portugal) and to assess if increasing salinity levels of the irrigation water can be compensated by application of nitrogen while still obtaining acceptable crop yield. Maximum yield was obtained from both soils with an application of 13 g m⁻² of nitrogen. Yield response to Na⁺ application was different in the two studied soils and depended on the total amount of Na⁺ or irrigation water applied. No significant interaction was found between nitrogen and sodium, but a positive effect on maize yield was observed in the medium textured soil for amounts of Na⁺ less than 905 g m⁻² when applied in the irrigation water.     

Validation and testing of the AquaCrop model under full and deficit irrigated wheat production in Iran

Accurate crop development models are important tools in evaluating the effects of water deficits on crop yield or productivity and predicting yields to optimize irrigation under limited available water for enhanced sustainability and profitable production. Food and Agricultural Organization (FAO) of United Nations addresses this need by providing a yield response to water simulation model (AquaCrop) with limited sophistication. The objectives of this study were to evaluate the AquaCrop model for its ability to simulate wheat (Triticum aestivum L.) performance under full and deficit water conditions in a hot dry environment in south of Iran, to study the effect of different scenarios of irrigation (crop growth stages and depth of water applied) on wheat yield. The AquaCrop model was evaluated with experimental data collected during the three field experiments conducted in Ahvaz. The AquaCrop model was able to accurately simulate soil water content of root zone, crop biomass and grain yield, with normalized root mean square error (RMSE) less than 10%. The analysis of irrigation scenarios showed that the highest grain yield could be obtained by applying four irrigations (200 mm) at sowing, tillering, stem elongation and flowering or grain filing stages for wet years, four irrigations (200 mm) at sowing, stem elongation and flowering stages for normal years and six irrigations (300 mm) at sowing, emergence, tillering, stem elongation, flowering and grain filing stages for dry years. The least amount of irrigation water to provide enough water to response to evaporative demand of environment and to obtain high WUE for wet, normal and dry years were 100, 200 and 250 mm, respectively.     

Remote sensing of biotic and abiotic stress for irrigation management of cotton

The applicability of commercially available remote sensing instrumentation was evaluated for site-specific management of abiotic and biotic stress on cotton (Gossypium hirsutum L.) grown under a center pivot low energy precision application (LEPA) irrigation system. This study was conducted in a field where three irrigation regimes (100%, 75%, and 50% ET_c) were imposed on areas of Phymatotrichum (root rot) with the specific objectives to (1) examine commercial remote sensing instrumentation for locating areas showing biotic and abiotic stress symptomology in a cotton field, (2) compare data obtained from commercial aerial infrared photography to that collected by infrared transducers (IRTs) mounted on a center pivot, (3) evaluate canopy temperature changes between irrigation regimes and their relationship to lint yield with IRTs and/or IR photography, and (4) explore the use of deficit irrigation and the use of crop coefficients for irrigation scheduling. Pivot-mounted IRTs and an IR camera were able to differentiate water stress among irrigation regimes. The IR camera distinguished between biotic (root rot) and abiotic (drought) stress with the assistance of groundtruthing. The 50% ET_c regime had significantly higher canopy temperatures than the other two regimes, which was reflected in significantly lower lint yields when compared to the 75% and 100% ET_c regimes. Deficit irrigation down to 75% ET_c had no impact on lint yield, indicating that water savings were possible without reducing yield.     

Spectral vegetation indices for benchmarking water productivity of irrigated cotton and sugarbeet crops

Irrigation performance and water productivity can be benchmarked if estimates of spatially distributed yield and crop water use are available. A commonly used method to estimate crop evapotranspiration in irrigated areas is to multiply reference evapotranspiration values by appropriate crop coefficients. This study evaluated convenient ways to derive such coefficients using multispectral vegetation indices obtained by remote sensing. Detailed ground radiometric measurements were taken in small plots perpendicular to the crop rows to obtain canopy reflectance values. Ancillary measurements of green ground cover, plant height, leaf area index and biomass were taken in the cropped strip covered by the radiometer field-of-view. The results were up-scaled using 10 Landsat-5 and 1 Landsat-7 images. Crop measurements and ground radiometry were made at the time of Landsat overpass on two commercial fields, one grown with sugarbeet and the other with cotton. Crop height and ground cover were determined weekly in these two fields, three additional sugarbeet fields and one additional cotton field. The ground and satellite observations of canopy reflectance yielded similar results. Two vegetation indices, the normalized difference vegetation index (NDVI) and the soil adjusted vegetation index (SAVI) were evaluated. Both indices described the crop growth well, but SAVI was used in further evaluations because it could be conveniently related to both ground cover and the basal crop coefficient using a simple model. Based on these findings, crop water use variability was analyzed in a large sample of sugarbeet and cotton fields, within a homogeneous irrigation scheme in Southern Spain. The yield versus evapotranspiration data points were highly scattered for both cotton and sugarbeet. The yield values obtained from the sugarbeet fields and cotton fields were substantially lower than values predicted by a linear yield function, and close to a curvilinear yield function, respectively. Evapotranspired water productivity varied in the cotton fields from 0.3 to 0.78 kg m⁻³, and in the sugarbeet fields from 7.15 to 14.8 kg m⁻³.     

A rule-based method for the development of crop management systems applied to grain sorghum in south-western France

A generic approach is proposed for the development and testing of crop management systems in contrasting situations of water availability. Ecophysiological knowledge, expertise, regional references and simulation models are combined to devise management strategies adapted to production targets and constraints. The next stage consists of converting these crop management strategies into logical and consistent sets of decision rules. Each rule describes the reasoning which is used to apply a technical decision by taking account of observed or simulated environmental conditions or predicted agronomic risks.

This approach was applied to design crop management systems for grain sorghum (Sorghum bicolor L. Moench.) in south-western France. For spring-sown crops, management (sowing date, plant density, varietal choice, N fertilizer rate and timing) was based on water availability, both for economic and environmental reasons. Specific sets of decision rules were written for irrigated and rainfed conditions. The establishment of rules was based on agronomic principles (e.g. for plant density) or on the application of a simulation model (e.g. for sowing date, variety). N fertilization and irrigation were applied using combined N and water dynamic models.

A novel methodology combining crop diagnosis, analytical trials and crop simulation was developed to evaluate the management systems. An irrigated and a rainfed rule-based management system were compared near Toulouse (S.W. France) from 1995 to 2002. The profitability of rainfed low-input management was confirmed for sorghum in spite of high yields under irrigation (up to 10 t ha⁻¹). The adaptation of sorghum management in rainfed conditions was mainly achieved through early maturing cultivars and by reducing N applications by 65%.     

The use of remote sensing for estimating ET of irrigated wheat and cotton in Northwest Mexico

Components of a satellite-based system for estimating the crop water requirements of irrigated vegetation have been combined, applied, and tested against field data in the Yaqui Valley, northwest Mexico. Frequent satellite observations have the potential to provide snap shots of cloud variability at the high spatial and temporal resolutions that are needed for making simple, near real-time estimates of incoming solar radiation and, thus, daytime evaporation required for irrigation scheduling. Less frequent polar orbiting satellites offer the capacity of following the vegetation development at higher spatial resolution. The operational framework for obtaining cloud cover has been developed and applied using hourly sampled, 1 km resolution, GOES-10 data received in real-time. The high-resolution, cloud-screening algorithm has proved to be efficient and reliable and has been used to provide high-resolution (4 km) estimates of solar radiation. Relationships between vegetation indices (NDVI and SAVI) and crop coefficients (the ratio of measured to reference evapotranspiration) have been derived with four different models (Shuttleworth, Penman, Priestley–Taylor and Makkink), using ground-based surface reflectance measured over the crop. Continuous measurements of surface fluxes and other meteorological variables were made following almost the entire vegetative cycle of the plant using a station equipped with standard meteorological instruments and an eddy-correlation system. Actual evapotranspiration was computed as the product of the estimated crop coefficients, derived from field radiometer measurements, and reference evapotranspiration. In comparison with ground data, RMSE values are on the order of 1 mm per day. Finally the opportunity to use high-resolution satellite data to make near real-time estimates of crop evaporation is discussed.     

Irrigation water use estimates based on crop simulation models and kriging

In Georgia and many other southeastern states in the USA, the amount of water used by agriculture for irrigation is largely unknown due to the lack of reporting requirements. Recent droughts and a water dispute with the neighboring states that include Alabama and Florida have highlighted the need for an accurate estimate of water use by agriculture. The goal of this study was to evaluate the use of a crop simulation model combined with kriging for estimating the spatial distribution of the monthly irrigation water use for cotton in the Coastal Plain region of Georgia. Farmers’ monthly irrigation applications for cotton during the 2002 and 2003 growing seasons were obtained from selected sites of the Agricultural Water Pumping program. We selected 80 fields for 2002 and 51 fields for 2003. For each of these fields, we used the Cropping System Model-CROPGRO-Cotton to simulate farmers’ irrigation applications. Ordinary kriging was used to estimate the spatial distribution of monthly total irrigation in the region. We then compared the spatial and temporal distribution of irrigation amounts predicted by the Cropping System Model-CROPGRO-Cotton with the amount of water that the farmers actually applied. The Cropping System Model-CROPGRO-Cotton simulated the temporal pattern of irrigation applications very well during the growing season. The root mean square error (RMSE) between observed and simulated total irrigation for different months ranged from 5 to 23 mm in 2002 and from 2 to 14 mm in 2003. The RMSE values were generally higher in 2002 when the irrigation applications across the region were more variable when compared with 2003. Consequently, a better agreement on the spatial distribution of monthly total irrigation for the observed and simulated was obtained for 2003 than for 2002.     

Evaluating salinity distribution in soil irrigated with saline water in arid regions of northwest China

In arid and semi-arid regions, salinity is a serious and chronic problem for agriculture. A 3-year field experiment in the arid environment of Xinjiang, northwest China, was conducted to study the salinity change in soil resulting from deficit irrigation of cotton with non-saline, moderate saline and high saline water. The salinity profile distribution was also evaluated by an integrated water, salinity, and nitrogen model, ENVIRO-GRO. The simulated and observed salinity distributions matched well. Results indicated that after 3 years of cotton production, the average salinity in the 1.0-m soil profile was 336% and 547% of the original soil profile, respectively, for moderate saline and high saline water irrigation. If the practices continued, the average soil salinity (EC_e) in the 1.0-m soil profile would approach a steady level of 1.7, 10.8, and 14.7 dS m⁻¹, respectively, for the treatments receiving irrigation waters of 0.33, 3.62, and 6.71 dS m⁻¹. It was concluded that deficit irrigation of saline water in this region was not sustainable. Model simulation showed that a big flood irrigation after harvest can significantly reduce the salt accumulation in the soil profile, and that this practice was much more efficient for salinity control than applying the same extra amount of water during the growing season.     

Effects of deficit irrigation on the yield and yield components of drip irrigated cotton in a mediterranean environment

A field study on cotton (Gossypium hirsutum L., cv.) was carried out from 2005 to 2008 in the Çukurova Region, Eastern Mediterranean, Turkey. Treatments were designated as I₁₀₀ full irrigation; DI₇₀, DI₅₀ and DI₀₀ which received 70, 50, and 0% of the irrigation water amount applied in the I₁₀₀ treatment. The irrigation water amount to be applied to the plots was calculated using cumulative pan evaporation that occurred during the irrigation intervals. The effect of water deficit or water stress on crop yield and some plant growth parameters such as yield response, water use efficiencies, dry matter yield (DM), leaf area index (LAI) as well as on lint quality components was evaluated. The average seasonal evapotranspiration ranged from 287 ± 15 (DI₀₀) to 584 ± 80 mm (I₁₀₀). Deficit irrigation significantly affected crop yield and all yield components considered in this study. The average seed cotton yield varied from 1369 ± 197 (DI₀₀) to 3397 ± 508 kg ha⁻¹ (I₁₀₀). The average water use efficiency (WUE_ET) ranged from 6.0 ± 1.6 (I₁₀₀) to 4.8 ± 0.9 kg ha⁻¹ mm⁻¹ (DI₀₀), while average irrigation water use efficiency (WUE_I) was between 9.4 ± 3.0 (I₁₀₀) and 14.4 ± 4.8 kg ha⁻¹ mm⁻¹ (DI₅₀). Deficit irrigation increased the harvest index (HI) values from 0.26 ± 0.054 (I₁₀₀) to 0.32 ± 0.052 kg kg⁻¹ (DI₅₀). Yield response factor (Ky) was determined to be 0.98 based on four-year average. Leaf area index (LAI) and dry matter yields (DM) increased with increasing water use. This study demonstrated that the full irrigated treatment (I₁₀₀) should be used for semiarid conditions with no water shortage. However, DI₇₀ treatment needs to be considered as a viable alternative for the development of reduced irrigation strategies in semiarid regions where irrigation water supplies are limited.     

时段划分对棉花作物水模型的影响与改进

为了改善时段划分对作物水模型模拟精度的影响,依据山西水利职业技术学院试验基地2006和2008年棉花田间试验资料,将棉花全生育期等间隔地划分为不同时段,用非线性优化方法求得了不同时段数条件下的作物水模型参数,分析研究了模型参数与时段数的关系,据此在作物水模型的水分敏感指数累积函数中引入了时段数,并与现有的作物水模型进行了比较。结果表明,引入时段数的作物水模型模拟产量的相对误差随时段数的增加而减小,当时段数大于11时,相对误差平均值和最大值分别减小到7%和15%以下,与现有的作物水模型比较,模拟精度有所提高,但参数个数未增加。该模型更多地反映了水分胁迫时间对作物产量影响的信息。     

河套灌区玉米农田蒸散动态变化及其影响因子的通径分析

采用大型称重式蒸渗仪研究了内蒙古河套灌区玉米蒸散动态规律,并运用通径分析法探讨了玉米蒸散量ET与各影响因子间的相关关系.结果表明:充分灌溉处理下玉米生育期(播前-收获)累积蒸散量为593.72 mm,亏缺灌溉处理下为395.21 mm,日平均蒸散量分别为4.24和2.82 mm/d.由各生育期的分布情况可知苗期蒸散量最小,分别占全生育期的3.7%和5.8%;拔节期开始,蒸散量逐渐增大,在抽雄期达到峰值,2种处理总蒸散量分别为279.38和166.76 mm,日平均蒸散量分别为8.47和5.05 mm/d,分别占整个生育期蒸散总量的47.1%和42.2%.由小时尺度蒸散量变化规律可知,玉米日蒸散量变化规律表现为早晚低、中午高的“单峰型”曲线特征.通径分析表明:2种灌溉处理下,饱和水气压和平均气温对ET的综合决定能力较大,是2个主要的环境驱动因子;2种灌溉处理下对蒸散作用最小的因子均为风速,且风速对ET的影响以间接作用为主.影响河套灌区玉米蒸散的主要气象因子为饱和水气压与气温.     

Review of measured crop water productivity values for irrigated wheat,rice, cotton and maize

The great challenge of the agricultural sector is to produce more food from less water, which can be achieved by increasing Crop Water Productivity (CWP). Based on a review of 84 literature sources with results of experiments not older than 25 years, it was found that the ranges of CWP of wheat, rice, cotton and maize exceed in all cases those reported by FAO earlier. Globally measured average CWP values per unit water depletion are 1.09, 1.09, 0.65, 0.23 and 1.80 kg m⁻³ for wheat, rice, cotton_seed, cotton_lint and maize, respectively. The range of CWP is very large (wheat, 0.6–1.7 kg m⁻³; rice, 0.6–1.6 kg m⁻³; cotton_seed, 0.41–0.95 kg m⁻³; cotton_lint, 0.14–0.33 kg m⁻³ and maize, 1.1–2.7 kg m⁻³) and thus offers tremendous opportunities for maintaining or increasing agricultural production with 20–40% less water resources. The variability of CWP can be ascribed to: (i) climate; (ii) irrigation water management and (iii) soil (nutrient) management, among others. The vapour pressure deficit is inversely related to CWP. Vapour pressure deficit decreases with latitude, and thus favourable areas for water wise irrigated agriculture are located at the higher latitudes. The most outstanding conclusion is that CWP can be increased significantly if irrigation is reduced and crop water deficit is intendently induced.     

Management model for decision support when applying low quality water in irrigation

Use of low quality water for irrigation of food crops is an important option to secure crop productivity in dry regions, alleviate water scarcity and recycle nutrients, but it requires assessment of adverse effects on health and environment. In the EU-project “SAFIR¹” a model system was developed that combines irrigation management with risk evaluation, building on research findings from the different research groups in the SAFIR project. The system applies to field scale irrigation management and aims at assisting users in identifying safe modes of irrigation when applying low quality water. The cornerstone in the model system is the deterministic “Plant-Soil-Atmosphere” model DAISY, which simulates crop growth, water and nitrogen dynamics and if required heavy metals and pathogen fate in the soil. The irrigation and fertigation module calculates irrigation and fertigation requirements based on DAISY's water and nitrogen demands. A Water Source Administration module keeps track of water sources available and their water quality, as well as water treatments, storage, and criteria for selection between different sources. At harvest, the soil concentrations of heavy metals and pathogens are evaluated and the risk to consumers and farmers assessed. Crop profits are calculated, considering fixed and variable costs of input and output. The user can run multiple “what-if” scenarios that include access to different water sources (including wastewater), water treatments, irrigation methods and irrigation and fertilization strategies and evaluate model results in terms of crop yield, water use, fertilizer use, heavy metal accumulation, pathogen exposure and expected profit. The management model system can be used for analysis prior to investments or when preparing a strategy for the season.