Using remote sensing to evaluate the spatial variability of evapotranspiration and crop coefficient in the lower Rio Grande Valley,New Mexico

Pecan is a major crop in the lower Rio Grande Valley (LRGV), New Mexico. Currently, about 11,000 ha of pecan orchards at various stages of growth are consuming about 40% of irrigation water in the area. Pecan evapotranspiration (ET) varies with age, canopy cover, soil type and method of water management. There is a need for better quantification of pecan ET for the purpose of water rights adjudication, watershed management and agronomical practices. This paper describes a process where remote sensing information from Landsat-5 and Landsat-7 were combined with ground level measurements to estimate pecan ET and field scale actual crop coefficient (K _c) for the LRGV. The results showed that annual pecan water use for 279 fields ranged from 498 to 1,259 mm with an average water use of 1,054 mm. For fields with NDVI > 0.6 (normalized difference vegetation index), which represented mature orchards (total of 232 fields), the annual water use ranged from 771 to 1,259 mm with an average water use of 1,077 mm. The results from remote sensing model compared reasonably well with ground level ET values determined by an eddy covariance system in a mature pecan orchard with an average error of 4% and the standard error of estimate (SEE) ranging from 0.91 to 1.06 mm/day. A small fraction (5%) of the pecan fields were within the range of maximum ET and K _c.     

A simple irrigation scheduling approach for pecans

Pecans are a major crop in New Mexico's Lower Rio Grande Valley (LRGV). It is estimated that New Mexico is responsible for about 21% of the world's pecan production (Lillywhite et al., 2007). Currently, approximately 12,000 ha of pecan orchards at various stages of growth consume 45% of the area's irrigation water. Pecan evapotranspiration (ET) varies with age, canopy cover, soil type, crop density and method of water management. Intense competition for the LRGV's limited water supply has created a serious need for better water management through improved irrigation scheduling. Annual pecan ET ranges from as low as 500 mm to as high as 1400 mm. Diversity of the pecan crop coefficient (K_c) and ET makes the task of irrigation scheduling for this crop very complicated. Using remote sensing technology and field ET measurements, a simple relationship was developed to relate crop coefficient and ET to canopy cover. This relationship is then used in combination with climate data to calculate daily and weekly water requirements for each orchard. The difference between annual ET values estimated from canopy cover and values measured with an eddy covariance flux tower ranged from 2 to 5%. The average ratio of estimated monthly ET values over measured ET values was 1.03 with the standard error of the estimate ranging from 10 to 20 mm/month. This methodology provides a simple tool that farmers can use to schedule irrigation of pecan orchards. Even though the methodology was developed for irrigation scheduling in the LRGV, it can be used in other locations by transferring the reference crop coefficients using K_c-GDD relationships.     

Irrigation water management with water deficit index calculated based on oblique viewed surface temperature

In this study, the relationship between water deficit index (WDI) and a number of parameters related to soil water status, crop monitoring and yield were investigated with regard to drip irrigated dwarf green beans (Phaseolus vulgaris, humilis) in Ankara, Turkey during the 2004 and 2005 growing seasons. Three different WDIs were calculated based on three different spectral indexes and oblique viewed surface temperature. Soil water status was quantified by soil water content (SWC) and soil water deficit index (SWDI). Crop evapotranspiration (ET_c), leaf water potential (LWP), spectral indexes and crop water stress index (CWSI) were determined. Although the WDIs have statistically significant relationships with the parameters, it is hard to use WDIs based on oblique viewed surface temperature for irrigation scheduling purposes. However, total yield estimation and monitoring of seasonal crop water use status could be achieved through this kind of WDI.     

Methods for estimating irrigation needs of spring wheat in the middle Heihe basin,China

Understanding reference crop evapotranspiration (ET₀) is essential in planning the most effective use of water resources in the arid northwest China. The objective of the present work in the middle Heihe River basin were: (1) to determine the best model for calculating the areal distribution of reference crop evapotranspiration in this region, and (2) to estimate the spatial distribution of the irrigation requirements of spring wheat. Note that eight commonly used formulates were tested and that FAO-Penman was the best.The irrigation amount of spring wheat in 2000 was estimated by three steps. First, DEM-based and GIS-assisted methods were employed to estimate the spatial distribution of reference crop evapotranspiration (ET₀) according to FAO-Penman model. Then, spring wheat evapotranspiration (ET) was calculated by ET₀ and crop-coefficient (K_c). Finally, the maximum irrigation amount of spring wheat was estimated with the spring wheat evapotranspiration and precipitation in the different growing stage. The maximum irrigation has temporal–spatial variation. Temporally the irrigation amount appears the largest in June when it is the peak period of spring wheat development. The irrigation amount is the smallest in July because spring wheat was in late-season stage. In April, spring wheat was in seedling stage during which the water demand is also small. Spatially the irrigation amount increases from southeast to northwest.     

An improved water use efficiency of cereals under temporal and spatial deficit irrigation in north China

Water shortage is the major bottleneck that limits sustainable development of agriculture in north China. Crop physiological water-saving irrigation methods such as temporal (regulated deficit irrigation) and spatial (partial root zone irrigation) deficit irrigation have been tested with much improved crop water use efficiency (WUE) without significant yield reduction. Field experiments were conducted to investigate the effect of (1) spatial deficit irrigation on spring maize in arid Inland River Basin of northwest China during 1997–2000; (2) temporal deficit irrigation on winter wheat in semi-arid Haihe River Basin during 2003–2007 and (3) temporal deficit irrigation on winter wheat and summer maize in Yellow River Basin during 2006–2007. Results showed that alternate furrow irrigation (AFI) maintained similar photosynthetic rate (P_n) but reduced transpiration rate (T_r), and thus increased leaf WUE of maize. It also showed that the improved WUE might only be gained for AFI under less water amount per irrigation. The feasible irrigation cycle is 7d in the extremely arid condition in Inner River Basin of northwest China and less water amount with more irrigation frequency is better for both grain yield and WUE in semi-arid Haihe River Basin of north China. Field experiment in Yellow River Basin of north China also suggests that mild water deficit at early seedling stage is beneficial for grain yield and WUE of summer maize, and the deficit timing and severity should be modulated according to the drought tolerance of different crop varieties. The economical evapotranspiration for winter wheat in Haihe River Basin, summer maize in Yellow River Basin of north China and spring maize in Inland River Basin of northwest China are 420.0 mm, 432.5 mm and 450.0 mm respectively. Our study in the three regions in recent decade also showed that AFI should be a useful water-saving irrigation method for wide-spaced cereals in arid region, but mild water deficit in earlier stage might be a practical irrigation strategy for close-planting cereals. Application of such temporal and spatial deficit irrigation in field-grown crops has greater potential in saving water, maintaining economic yield and improving WUE.     

A review of downscaling methods for remote sensing-based irrigation management: part I

High-resolution daily evapotranspiration (ET) maps would greatly improve irrigation management. Numerous ET mapping algorithms have been developed to make use of thermal remote sensing data acquired by satellite sensors. However, adoption of remote sensing-based ET maps for irrigation management has not been feasible due to inadequate spatial and temporal resolution of ET maps. Data from a coarse spatial resolution image in agricultural fields often cause inaccurate ET estimation because of a high level of spatial heterogeneity in land use. Image downscaling methods have been utilized to overcome spatial and temporal scaling issues in numerous remote sensing applications. In the field of hydrology, the image downscaling method has been used to improve spatial resolution of remote sensing-based ET maps for irrigation scheduling purposes and thus improves estimation of crop water requirements. This paper (part I) reviews downscaling methods to improve spatial resolution of land surface characteristics such as land surface temperature or ET. Each downscaling method was assessed and compared with respect to their capability of downscaling spatial resolutions of images. The companion paper (part II) presents review of image fusion methods that are also designed to increase spatial resolutions of images by integrating multi-spectral and panchromatic images.     

无人机遥感技术在精量灌溉中应用的研究进展

以提高农业用水效率为目标的精量灌溉是未来农业灌溉的主要模式,精量灌溉的前提条件是对作物缺水的精准诊断和科学的灌溉决策。用于作物缺水诊断和灌溉决策定量指标的信息获取技术主要基于田间定点监测、地面车载移动监测及卫星遥感。无人机从根本上解决了卫星遥感由于时空分辨率低而导致的瞬时拓延、空间尺度转换、遥感参数与模型参数定量对应等技术难题,也克服了地面监测效率低、成本高、影响田间作业等问题。近几年的研究结果表明,无人机遥感系统可以高通量地获取多个地块的高时空分辨率图像,使精准分析农业气象条件、土壤条件、作物表型等参数的空间变异性及其相互关系成为可能,为大面积农田范围内快速感知作物缺水空间变异性提供了新手段,在精量灌溉技术应用中具有明显的优势和广阔的前景。无人机遥感系统已经应用在作物覆盖度、株高、倒伏面积、生物量、叶面积指数、冠层温度等农情信息的监测方面,但在作物缺水诊断和灌溉决策定量指标监测方面的研究才刚刚起步,目前主要集中在作物水分胁迫指数(CWSI)、作物系数、冠层结构相关指数、土壤含水率、叶黄素相关指数(PRI)等参数估算的研究,有些指标已经成功应用于监测多种作物的水分胁迫状况,但对于大多数作物和指标,模型的普适性还有待进一步研究。给出了无人机遥感在精准灌溉技术中应用的技术体系,并指出,为满足不同尺度的高效率监测和实现农业用水精准动态管理的需求,今后无人机遥感需要结合卫星遥感和地面监测系统,其中天空地一体化农业水信息监测网络优化布局方法与智能组网技术、多源信息时空融合与同化技术、作物缺水多指标综合诊断模型、农业灌溉大数据等将是未来重点研究内容。     

Effect of seasonal water stress imposed on drip irrigated second crop watermelon grown in semi-arid climatic conditions

A study was conducted to determine the water stress effect on yield and some physiological parameters including crop water stress index for drip irrigated second crop watermelon. Irrigations were scheduled based on replenishment of 100, 75, 50, 25, and 0% soil water depletion from 90 cm soil depth with 3-day irrigation interval. Seasonal crop evapotranspiration (ET) for I₁₀₀, I₇₅, I₅₀, I₂₅, and I₀ were 660, 525, 396, 210, and 70 mm in 2003 and 677, 529, 405, 221, and 75 mm in 2004. Fruit yield was significantly lowered by irrigation water stress. Average water-yield response factor for both of the years was 1.14. The highest yield was obtained from full irrigated treatment as 34.5 and 38.2 t ha⁻¹ in 2003 and 2004, respectively. Lower ET rates and irrigation amounts in water stress treatments resulted in reductions in all measured parameters, except water-soluble dry matter concentrations (SDM). Canopy dry weights, leaf relative water content, and total leaf chlorophyll content were significantly lowered by water stress. Yield and seasonal ET were linearly correlated with mean CWSI values. An average threshold CWSI value of 0.17 before irrigation produced the maximum yield and it could be used to initiate the irrigation for watermelon.     

Remote sensing to estimate ET-fluxes and the performance of an irrigation district in southern Italy

Satellite remote sensed data on canopy biophysical properties, ground data and agro-meteorological information were combined to estimate evapotranspiration (ET) fluxes of orange orchards using a modified Penman–Monteith equation. The study was carried out during the irrigation season 2004 in an irrigation district, cover for about 95% with orange groves, of 1550 ha located in eastern Sicily (Italy). The spatial pattern in ET-fluxes have been analysed using IKONOS high-resolution satellite and hyper-spectral ground data acquired and processed for the study-area. The remote estimates of ET-fluxes varied between 1.3 and 5.7 mm/day, with a daily average value of about 4.2 mm, showing a good agreement with crop ET values determined as residual of soil water balance of selected ground control sites. Crop coefficient estimates ranged between 0.22 and 1.08 showing positive correlations with percentages of ground cover (C_g) increasing from 30 to 80% ground shading and with LAI values. By comparing ET estimates with water volumes supplied in each sub-district of the study-area, the performance indicator “IP” was evaluated, allowing to rank the conditions of un-fulfilment of crop water requirements by public and private water distribution systems. Generally, out of 29 sub-districts, 14 had “IP” values less than 50%, revealing a sub-optimal water supply for the study-area.     

Ground-based remote sensing for assessing water and nitrogen status of broccoli

Remote sensing (RS) can facilitate the management of water and nutrients in irrigated cropping systems. Our objective for this study was to evaluate the ability of several RS indices to discriminate between limited water and limited nitrogen induced stress for broccoli. The Agricultural Irrigation Imaging System (AgIIS) was used over a 1-ha broccoli field in central Arizona to measure green (550 nm), red (670 nm), far red (720 nm), and near infrared (NIR-790 nm) reflectances, and thermal infrared radiation. Measurements were taken at a 1 m × 1 m resolution, every several days during the season. The following indices were calculated: ratio vegetation index (RVI), normalized difference vegetation index (NDVI), normalized difference based on NIR and green reflectance (NDNG), canopy chlorophyll concentration index (CCCI), and the water deficit index (WDI). The experimental design was a two-factor, nitrogen × water, Latin square with four treatments (optimal and low water and optimal and low nitrogen) and four replicates. In addition to RS measurements, the following in-situ measurements were taken: SPAD chlorophyll (closely related to nitrogen status), plant petiole nitrate-nitrogen concentrations, soil water content, and plant height, width, and leaf area index (LAI). Fresh marketable broccoli yield was harvested from plots 130 days after planting.Seasonal water application (irrigation plus rainfall) was 14% greater for optimal than low water treatments, whereas total nitrogen application was 35% greater for optimal than low N treatments. Although both nitrogen and water treatments affected broccoli growth and yield, nitrogen effects were much more pronounced. Compared to the optimal water and nitrogen treatment, broccoli yield was 20% lower for low water but optimal nitrogen, whereas yield was 42% lower for optimal water but low nitrogen. The RVI, NDVI, and NDNG indices detected treatment induced growth retardation but were unable to distinguish between the water and nitrogen effects. The CCCI, which was developed as an index to infer differences in nitrogen status, was found to be highly sensitive to nitrogen, but insensitive to water stress. The WDI provided appropriate information on treatment water status regardless of canopy cover conditions and effectively detected differences in water status following several irrigation events when water was withheld from low but not optimal water treatments. Using a RS ground-based monitoring system to simultaneously measure vegetation, nitrogen, and water stress indices at high spatial and temporal resolution could provide a successful management tool for differentiating between the effects of nitrogen and water stress in broccoli.     

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.     

基于蒸渗仪的冬小麦-夏玉米ET估算模型特征参数研究

为快速准确估算农田蒸散量,利用24个群集式蒸渗仪,在国家节水灌溉北京工程技术研究中心大兴节水灌溉试验站进行了两年的灌溉试验,获得冬小麦-夏玉米生育期的日内冠气温差和实际日蒸散量(ET_a)等数据,对不同水分处理下的S-I蒸散量估算模型进行率定及验证,并分析模型特征参数a、b的变化规律及两者的差异。结果表明:冬小麦的S-I模型特征参数a在日间随时间变化先增大、后减小,在严重水分胁迫处理时a为负值、且数值较小,其余灌溉处理时参数a由正值逐渐变化至负值;不同灌水处理b均为负值,充分灌溉处理时b在日间随时间变化逐渐增大,严重水分胁迫处理时b相对较大,日间变化趋势不稳定。水分胁迫对夏玉米模型参数的影响程度低于冬小麦,特征参数a均为正值,参数b均为负值,且随时间变化逐渐增大;水分胁迫处理时b变化范围明显小于其他两个处理,干旱处理特征参数日间变化较大。冬小麦与夏玉米不同处理之间模型参数a、b变化差异较大,但冠层温度和空气温度差T_c-T_a与日蒸散量和日净辐射量差ET_d-Rn_d间拟合精度都在13:00时最高,此时充分灌溉冬小麦和夏玉米的模型参数a、b分别为1.082、-1.127和1.588、-1.363。利用率定的S-I模型计算冬小麦和夏玉米主要生育期ET_d与实测ET_a之间的决定系数R~2均在0.7以上,均方根误差RMSE均小于0.89 mm/d,一致性系数d均在0.9以上。尤其是充分灌溉处理的数据间R~2和d均较高,RMSE小于其他处理,说明水分胁迫影响模型的估算精度,S-I模型能够更准确地估算水分胁迫较少农田的蒸散量。     

Remote sensing and in situ-based estimates of evapotranspiration for subirrigated meadow,dry valley,and upland dune ecosystems in the semi-arid sand hills of Nebraska,USA

Water consumed through evapotranspiration (ET) impacts local and regional hydrologic regimes on various spatial and temporal scales. Estimating ET in the Great Plains is a prerequisite for effective regional water resource management of the Ogallala (High Plains) Aquifer, which supplies vital water resources in the form of irrigation for extensive agricultural production. The Sand Hills region of Nebraska is one of the largest grass-stabilized eolian (windblown) sand dune formations in the world, with an area of roughly 50,000–60,000 km² that supports a system of five major land cover types: (1) lakes, (2) wetlands (with lakes, ~5%), (3) subirrigated meadows (water table is within ~1 m of surface; ~10%), (4) dry valleys (water table is 1–10 m below surface; ~20%), and (5) upland dunes (water table is more than 10 m below surface; ~65%). Fully understanding the hydrologic regime of these different ecosystems is a fundamental challenge in regional water resource assessment. The surface energy and water balances were analyzed using Bowen Ratio Energy Balance Systems (BREBS) at three locations: (1) a meadow, (2) a valley, and (3) an upland dune. Measurement of the energy budget by BREBS, in concert with Landsat remote sensing image processing for 2004 reveals strong spatial gradients between sites in latent heat flux that are associated with undulating topographic relief. We find that daily estimates of ET from BREBS measurements and remote sensing agree well, with an uncertainty within 1 mm, which is encouraging when applying remote sensing results across such a broad spatial scale and undulating topography.     

Estimation of crop evapotranspiration of irrigation command area using remote sensing and GIS

This paper describes the use of satellite-based remote sensing (RS) data and geographic information system (GIS) tools for estimating seasonal crop evapotranspiration in Mahi Right Bank Canal (MRBC) command area of Gujarat, India. Crop coefficients (K_c) for various major crops grown in MRBC were estimated, empirically, from the RS derived soil adjusted vegetation index (SAVI) values. A reference crop evapotranspiration (ET₀) map was generated from point meteorological observations. The K_c and ET₀ maps were combined to generate seasonal crop evapotranspiration (ET_crop) map which highlighted spatial variation in ET_crop ranging from more than 600 mm for healthy tobacco crops to less than 150 mm for very poor wheat crops.     

Water–yield relations and optimal irrigation scheduling of wheat in the Mediterranean region

Crop yield is primarily water-limited in areas of West Asia and North Africa with a Mediterranean climate. Ten years of supplemental irrigation (SI) experiments in northern Syria were conducted to evaluate water–yield relations for bread wheat (Triticum aestivum L.) and durum wheat (Triticum turgidum L.), and optimal irrigation scheduling was proposed for various rainfall conditions. The sensitive growth stages of wheat to water stress were from stem elongation to booting, followed by anthesis, and grain-filling. Water stress to which crop subjected depends on rainfall and its distribution during the growing season; the stress started from early March (stem-elongation stage) or even in seedling stage in a dry year, and from mid-April (anthesis) in an average or wet year. Crop yield linearly increased with increase in evapotranspiration (ET), with an increase of 160 kg for bread wheat and of 116 kg for durum wheat per 10 mm increase of ET above the threshold of 200 mm. Water-use efficiency (WUE) with a yield ≥3 t ha⁻¹ was ca. 60% higher than that with yield <3 t ha⁻¹; this emphasises the importance of that to achieve effective use of water, optimal water supply and relatively high yields need to be ensured. Quadratic crop production functions with the total applied water were developed and used to estimate the levels of irrigation water for maximizing yield, net profit and levels to which the crops could be under-irrigated without reducing income below that which would be earned for full SI under limited water resources. The analysis suggested that irrigation scenarios for maximizing crop yield and/or the net profit under limited land resource conditions should not be recommended. The SI scenarios for maximizing the profit under limited water resource conditions or for a targeted yield of 4–5 t ha⁻¹ were recommended for sustainable utilization of water resources and higher WUE. The time of irrigation was also suggested on the basis of crop sensitivity index to water stress taking rainfall probability and available soil water into account.     

Dry matter,harvest index,grain yield and water use efficiency as affected by water supply in winter wheat

Food production and water use are closely linked processes and, as competition for water intensifies, water must be used more efficiently in food production worldwide. A field experiment with wither wheat (Triticum Aestivum L.), involving six irrigation treatments (from rain-fed to 5 irrigation applications), was maintained in the North China Plain (NCP) for 6 years. The results revealed that dry matter production, grain yield and water use efficiency (WUE) were each curvilinearly related to evapotranspiration (ET). Maximum dry matter at maturity was achieved by irrigating to 94% and maximum grain yield to 84% of seasonal full ET. A positive relationship was found between harvest index (HI) and dry matter mobilization efficiency (DMME) during grain filling. Moderate water deficit during grain filling increased mobilization of assimilate stored in vegetative tissues to grains, resulting in greater grain yield and WUE. Generally, high WUE corresponded with low ET, being highest at about half potential ET. At this location in NCP, highest WUE and grain yield was obtained at seasonal water consumption in the range 250–420 mm. For that, with average seasonal rainfall of 132 mm, irrigation requirements was in the range of 120–300 mm and due to the deep root system of winter wheat and high water-holding capacity of the soil profile, soil moisture depletion of 100–150 mm constituted the greater part of the ET under limited water supply. The results reveal that WUE was maximized when around 35% ET was obtained from soil moisture depletion. For that, seasonal irrigation was around 60–140 mm in an average season.     

Responses of winter wheat (Triticum aestivum L.) evapotranspiration and yield to sprinkler irrigation regimes

The North China Plain (NCP) is one of the main productive regions for winter wheat (Triticum aestivum L.) and summer maize (Zea mays L.) in China. However, water-saving irrigation technologies (WSITs), such as sprinkler irrigation technology and improved surface irrigation technology, and water management practices, such as irrigation scheduling have been adopted to improve field-level water use efficiency especially in winter wheat growing season, due to the water scarcity and continuous increase of water in industry and domestic life in the NCP. As one of the WSITs, sprinkler irrigation has been increasingly used in the NCP during the past 20 years. In this paper, a three-year field experiment was conducted to investigate the responses of volumetric soil water content (SWC), winter wheat yield, evapotranspiration (ET), water use efficiency (WUE) and irrigation water use efficiency (IWUE) to sprinkler irrigation regimes based on the evaporation from an uncovered, 20-cm diameter pan located 0-5 cm above the crop canopy in order to develop an appropriate sprinkler irrigation scheduling for winter wheat in the NCP. Results indicated that the temporal variations in SWC for irrigation treatments in the 0-60-cm soil layer were considerably larger than what occurred at deeper depths, whereas temporal variations in SWC for non-irrigation treatments were large throughout the 0-120-cm soil layer. Crop leaf area index, dry biomass, 1000-grains weight and yield were negatively affected by water stress for those treatments with irrigation depth less than 0.50E, where E is the net evaporation (which includes rainfall) from the 20-cm diameter pan. While irrigation with a depth over 1.0E also had negative effect on 1000-grains weight and yield. The seasonal ET of winter wheat was in a range of 206-499 mm during the three years experiments. Relatively high yield, WUE and IWUE were found for the irrigation depth of 0.63E. Therefore, for winter wheat in the NCP the recommended amount of irrigation to apply for each event is the total 0.63E that occurred after the previous irrigation provided total E is in a range of 30-40 mm.     

基于SIMDual_Kc模型估算非充分灌水条件下冬小麦蒸散量

为研究关中冬小麦植株蒸腾和土壤蒸发规律,利用2 a冬小麦小区控水试验实测数据,率定和验证了双作物系数SIMDual_Kc模型在关中地区的适用性.用大型称重式蒸渗仪的实测蒸散量值(或水量平衡法计算值)与模型模拟值进行对比.结果表明:SIMDualKc模型可较准确地模拟关中不同水分条件下冬小麦蒸散量,且模拟精度较高.模型估算的平均绝对误差为0.643 3 mm/d.模型估算的冬小麦初期、中期和后期的基础作物系数分别为0.35,1.30,0.20.另外,模型还可以较准确地估算不同水分供应条件下的土壤水分胁迫系数、土壤蒸发量和植株蒸散量.冬小麦整个生育期,土壤蒸发主要发生在作物生育前期,中期较低,后期略微增大;植株蒸腾主要发生在作物快速生长期和生长中期,整个生育期中呈先增大后减小的趋势.     

Water-yield relations and water-use efficiency of winter wheat in the North China Plain

Limited precipitation restricts yield of winter wheat (Triticum aestivum L.) grown in the North China Plain. Water stress effects on yield can be avoided or minimized by application of irrigation. We examined the multiseasonal irrigation experiments in four locations of the piedmont and lowland in the region, and developed crop water-stress sensitivity index, relationship between seasonal evapotranspiration (ET) and yield, and crop water production functions. By relating relative yield to relative ET deficit, we found that the crop was more sensitive to water stress from stem elongation to heading and from heading to milking. For limited irrigation, irrigation is recommended during the stages sensitive to water stress. Grain yield was 258–322 g m⁻² in the piedmont and 260–280 g m⁻² in the lowland under rainfed conditions. The corresponding seasonal ET was 242–264 mm in the piedmont and 247–281 mm in the lowland. Irrigation significantly increased seasonal ET and therefore grain yield as a result of increased kernel numbers per m⁻² and kernels per ear. On average, one irrigation increased grain yield by 21–43% and two to four irrigations by 60–100%. Grain yield was linearly related to seasonal ET with a slope of 1.15 kg m⁻³ in the lowland and 1.73 kg m⁻³ in the piedmont. Water-use efficiency was 0.98–1.22 kg m⁻³ for rainfed wheat and 1.20–1.40 kg m⁻³ for the wheat irrigated 2–4 times. Grain yield response to the amount of irrigation (IRR) was developed using a quadratic function and used to analyze different irrigation scenarios. To achieve the maximum grain yield, IRR was 240 mm in the piedmont and 290 mm in the lowland. When the maximum net profit was achieved, IRR was 195 mm and 250 mm in the piedmont and lowland, respectively. The yield response curve to IRR showed a plateau over a large range of IRR, indicating a great potential in saving IRR while maintaining reasonable high levels of grain yield.     

Estimation of dwarf green bean water use under semi-arid climate conditions through ground-based remote sensing techniques

Determination of temporal and spatial distribution of water use (WU) within agricultural land is critical for irrigation management and could be achieved by remotely sensed data. The aim of this study was to estimate WU of dwarf green beans under excessive and limited irrigation water application conditions through indicators based on remotely sensed data. For this purpose, field experiments were conducted comprising of six different irrigation water levels. Soil water content, climatic parameters, canopy temperature and spectral reflectance were all monitored. Reference evapotranspiration (ET₀), crop coefficient K_c and potential crop evapotraspiration (ET_c) were calculated by means of methods described in FAO-56. In addition, WU values were determined by using soil water balance residual and various indexes were calculated. Water use fraction (WUF), which represents both excessive and limited irrigation applications, was defined through WU, ET₀ and K_c. Based on the relationships between WUF and remotely sensed indexes, WU of each irrigation treatments were then estimated. According to comparisons between estimated and measured WU, in general crop water stress index (CWSI) can be offered for monitoring of irrigated land. At the same time, under water stress, correlation between measured WU and estimated WU based on CWSI was the highest too. However, canopy-air temperature difference (T_c − T_a) is more reliable than others for excessive water use conditions. Where there is no data related to canopy temperature, some of spectral vegetation indexes could be preferable in the estimation of WU.