太行山山前平原主要农作物蒸散量估算方法比较

利用中国科学院栾城农业生态系统试验站1996、1997年气象数据,采用参考作物法和α比值法求得小麦、玉米蒸散量,并与同期大型称重式蒸渗仪监测的小麦、玉米蒸散量进行了比较。结果表明,2种方法估算小麦需水量误差较小。在估算玉米需水量时,丰水年α比值法结果偏低,枯水年参考作物法估算结果偏高。为准确估算作物需水量,建议在确定作物系数时应该尽量采用长系列观测数据分别确定不同年型的作物系数或耗水特征系数,或者采用误差较小的估算方法。     

日光温室膜下滴灌番茄作物系数试验研究

作物系数是在没有实测需水量资料情况下,用参考作物蒸发蒸腾量来估算实际作物蒸发蒸腾量方法中重要的参数之一。根据实测气象数据计算出的参考作物蒸发蒸腾量和时域反射仪测得的番茄需水量,利用单作物系数法得到番茄作物系数Kc。通过对作物需水量和作物系数Kc的变化及影响因素进行分析,结果表明：温室膜下滴灌番茄作物需水量与温度、辐射呈正相关,而作物系数Kc与温度、辐射的线性关系不明显。对已求作物系数的可靠性进行验证,结果表明模型预测值和实测值的相对误差为8.2%,模型有效性指数达到89.3%,模型合理有效。研究成果对日光温室膜下滴灌作物需水量的计算及其灌溉制度的制定具有一定的参考价值。     

用空气饱和差推算作物需水量

一前言把作物需水量作为蒸发问题,利用蒸发量与气象因子之间的定量关系,建立推算作物需水量的经验公式,而后用于灌溉实践,成为当前国外作物需水量研究工作中的主要课题,也是国外估算作物需水量值的主要方法。为了使用比较综合的气象因子,建立比较简便的估算作物需水量公式,以便用于作物水     

浑善达克沙地东南缘重叠植被生态需水量分析研究

重叠植被非生育期生态需水量是霜期、持续冰冻期地表有效自由水蒸发量,它维系越冬生境。基于2005~2006年对黄柳-扁蓄豆构成的重叠植被生境中气象因子及生理因子野外观测试验数据,用单、双作物系数法计算了重叠植被2个不同水文年生态需水量。这个基础数据对决策重叠植被建设规模、对区域需水预测模提供了基础数据。     

风沙区参考作物需水量的计算

根据国内外相关的研究成果，分析选择并确定了适宜于风沙区参考作物需水量（ET0)的计算模式。利用典型风沙区的气象资料，对多年逐旬参考作物需水量及2001年春小麦与春玉米生育时段内逐日参考作物需水量进行了分析计算。结果表明，FAO最新修正的Penman-Moteith公式可较好地用于风沙区参考作物需水量的估算，一般ET0值在年内与年龄间变化较大，最高值发生在6月上旬左右，多年平均为5.82mm/d，最低值发生在1月上旬，多年平均0.43mm/d左右，年内各日ET0值受气象因素的影响变幅很大，因此，精确灌溉应设法提高短期天气预报和灌溉预报的精度。     

基于多因素影响的区域旱作物有效降水量估算

【目的】确定区域尺度旱作物有效降水量估算方法。【方法】通过分析降水、土壤和作物因素对作物有效降水量的综合影响,提出了包括冠层截留量、土壤可容水量、地表径流量、降水量和深层渗漏量等4个计算模块的作物有效降水量估算模型,采用田间尺度水量平衡方程计算值对估算模型模拟值进行验证,并分析了河北平原5个县域作物有效降水量的时空分布特性。【结果】①作物有效降水量估算模型模拟结果与农田尺度水量平衡法计算值的决定系数R2和纳什系数NSE均大于0.85,模拟精度较高;②研究区域冬小麦-夏玉米连作条件下作物有效降水量为400.03 mm,降水入渗系数为0.84;丰水年、平水年、枯水年作物有效降水量分别为419、454和355 mm,降水入渗系数分别为0.76、0.86和0.83,栾城和元氏的作物有效降水量较赵县偏高。【结论】提出的估算模型可以用来估算区域尺度作物有效降水量。     

园林绿化植物灌溉需水量估算

园林植物灌溉需水量估算多是应用农业灌溉的概念和公式,计算理念和计算精度无法有效描述园林植物需水量实际情况.从园林植物需水的特殊考虑着手,通过引入园林植物腾发量、参考作物腾发量,园林系数公式、有效降雨量、运行时间倍乘数等相关概念,确定了园林植物实际需求的灌溉需水量,提出了一种园林绿化植物需水量的估算方法和估算过程.     

作物需水量在农业灌溉中的应用研究

农业灌溉用水是粮食生产安全的重要保障,合理的灌溉用水规划是水资源高效利用的重要保障。不同类型农作物在整个生长周期对水的实际需求是一个动态变化过程,传统大水漫灌会造成水资源的严重浪费,同时在灌溉过程中作物缺水或用水过量都不利于作物生长。为提高水资源利用效率,在灌溉过程准确估算作物实际用水需求,根据未来农业智能化发展和节水灌溉需求,结合项目实际及农业智能化灌溉理论研究发展现状,以作物实际需水量研究为基础,按作物类型建立全生长周期需水基础数据库及实际需水量决策模型实施按需灌溉。在灌溉区域布置传感器及微型气象监测系统,传感器网络节点监测和采集农田土壤参数,微型气象监测系统监测周边环境温度、湿度、风速及辐射等数据,通过LoRa无线通信将数据传输至数据处理终端,数据处理终端利用农作物实际需水量灌溉决策模型,综合考虑蒸腾、土壤蒸发、作物需水量等因素,分析计算得出作物实际需水量,生成灌溉时间、灌溉水量等指令,通过智能灌溉控制系统实现对作物的及时性、精准性灌溉,实现智能化、高效率、可持续的农业用水管理。     

泾惠渠灌区作物种植结构变化对灌溉需水量的影响

研究种植结构变化对灌区作物需水量和灌溉需水量的影响,能够为作物生育期的灌溉用水管理和农业水资源规划提供基础数据。依据泾惠渠灌区实测降水和蒸发蒸腾等气象数据,采用FAO推荐的Penman-Monteith公式和作物系数法计算灌区主要作物需水量;通过频率计算和配线法确定灌区丰水年(25%)、平水年(50%)和枯水年(75%)的有效降水量;根据1988—2014年Landsat卫星遥感影像提取的泾惠渠灌区不同历史时期农业种植结构数据,计算典型水文年份灌区总灌溉需水量,并分析作物需水量和灌溉需水量在不同典型水文年的年际和月际变化。结果表明,随着泾惠渠灌区农业种植结构的变化,灌区总的作物需水量和灌溉需水量都呈现显著下降趋势。但泾惠渠灌区在1988—2005年间,单位面积平均作物需水量和平均灌溉需水量都基本保持不变,随后均呈小幅下降趋势。各月份作物总需水量和总灌溉需水量除6月份之外,其余各月份都呈现显著下降趋势;但在此期间,灌区单位面积平均作物需水量和平均灌溉需水量除在4、8、9月份呈下降趋势,而6月份呈显著增加趋势外,其余各月份基本保持不变。灌区总的作物需水量和灌溉需水量的下降主要是由农作物种植面积大量减少所致,种植结构的变化对其影响较小,但灌区种植结构调整后的作物需水量状况更符合区域有效降水特点。     

基于ZigBee和模糊控制决策的自动灌溉系统的设计

针对节水灌溉受多种因素影响难以建立精确控制模型的特点,为了实现作物的自动、实时与适量灌溉,设计了基于ZigBee和模糊控制决策的全自动灌溉系统。该系统通过ZigBee无线传感器网络采集土壤水势与环境气象信息,由农田蒸散量和土壤水势作为输入,以作物需水量为输出,采用模糊推理规则,使用分段模糊控制策略获得了作物的需水量,构成智能灌溉系统;采用ARM9微处理器,基于嵌入式Linux开发了网关节点,实现了数据的汇聚和GPRS通信方式的远程数据及命令转发。试验结果表明:该系统能快速准确地计算出作物的需水量,经济实用,有效地实现了全自动节水灌溉,特别适用于中小型灌溉区域的精细灌溉。     

基于遥感的农业用水效率评价方法研究进展

遥感技术的发展为区域尺度蒸散发计算、作物分布识别及估产提供了一条有效途径,为基于遥感信息的灌区灌溉水利用效率及作物水分利用效率定量评价奠定了基础。回顾总结了遥感蒸散发模型、瞬时蒸散发升尺度方法、日蒸散发插值方法、作物分布识别方法及作物估产模型的研究进展,评述了遥感蒸散发及作物估产结果在灌区灌溉水利用效率及作物水分利用效率评价中的应用情况。提出了相关领域需要进一步研究的问题,包括适合非均匀下垫面特点且具有较强物理基础的灌区遥感蒸散发模型、日蒸散发插值中灌溉或降雨引起土壤含水量突变情况的处理、农田蒸散发中灌溉水有效消耗量的准确估算、能适应复杂种植结构并且适用于多年的作物分布遥感识别模型以及精度较高且可操作性强的遥感估产模型等。     

Regional analysis of irrigation water requirements using kriging: Application to potato crop (Solanum tuberosum L.) at Trás-os-Montes

Aiming at the analysis of the regional variation of potato crop irrigation water requirements over the Trás-os-Montes region, data from 106 rainfall stations and eight weather stations were utilized in an irrigation scheduling simulation model to estimate net irrigation water requirements of the potato crop. The simulation model was first validated using a field experiment which allows to derive the required crop data to be used in the simulations. The reference evapotranspiration (ET₀) was estimated using the FAO Penman–Monteith method. The model was applied to all 106 locations, each with a data set spanning a 19-year period. As a result of this application, series of the net irrigation water requirements for a 19-year period were obtained for each location. The resulting 106 point values of the net water requirements of the potato crop have been treated as a regionalized variable. The respective semivariograms have been computed and the kriging method then applied to estimate the spatial distribution of the water requirements in the region. Contour lines of this regionalized variable have been drawn using a GIS system. Results show an estimation error averaging 5% for the entire region.     

Combining remote sensing-simulation modeling and genetic algorithm optimization to explore water management options in irrigated agriculture

We present an innovative approach to explore water management options in irrigated agriculture considering the constraints of water availability and the heterogeneity of irrigation system properties. The method is two-folds: (i) system characterization using a stochastic data assimilation procedure where the irrigation system properties and operational management practices are estimated using remote sensing (RS) data; and (ii) water management optimization where we explored water management options under various levels of water availability. We set up a soil–water–atmosphere–plant model (SWAP) in a deterministic–stochastic mode for regional modeling. The distributed data, e.g. sowing dates, irrigation practices, soil properties, depth to groundwater and water quality, required as inputs for the regional modeling were estimated by minimizing the residuals between the distributions of field-scale evapotranspiration (ET) simulated by the regional application of SWAP, and by surface energy balance algorithm for land (SEBAL) using two Landsat7 ETM+ images. The derived distributed data were used as inputs in exploring water management options. Genetic algorithm was used in data assimilation and water management optimizations. The case study was conducted in Bata minor (lateral canal), Kaithal, Haryana, India during 2000–2001 rabi (dry) season. Our results showed that under limited water condition, regional wheat yield could improve further if water and crop management practices are considered simultaneously and not independently. Adjusting sowing dates and their distribution in the irrigated area could improve the regional yield, which also complements the practice of deficit irrigation when water availability is largely a constraint. This result was also found in agreement with the scenario that water is non-limited with the exception that the farmers have more degrees of freedom in their agricultural activities. An improvement of the regional yield to 8.5% is expected under the current scenario.     

Scheduling the cropping calendar in wet-seeded rice schemes in Malaysia

The Besut Irrigation Scheme, Terengganu, Malaysia is one of the eight gazetted main rice-growing areas in Malaysia. These eight granaries are targeted to produce only 65% of the total rice requirements of the nation. This scheme faces water scarcity especially during the off-season with the present existing cropping schedule. This study discusses the ways and means to overcome the water scarcity problem by setting the calendar for cropping schedules taking into consideration rainfall, river flow available and irrigation water requirements. A water balance approach using 48 years of rainfall and weather data was pursued in this study. The present main season from land preparation to crop harvest lasts from 1st November to 6th April, with land preparation being carried out during the heaviest rains in early November. However, the heavier rains may result in the postponement of seeding. Delays in crop planting during this main season can result in the cancellation of the following off-season crop from May to October. Shifting the land preparation works from November 1 to an earlier date, September 15, would result in a better match of crop water needs with the prevailing rainfall season (normally most of the rainfall occurs between September and December). This proposed schedule (15th September–10th February) also increases the probability that land preparation and subsequent seeding can be done for a second crop in the revised off-season period, 15th March–10th August. The present off-season schedule is from 5th May to 7th October and water scarcity during the vegetative and reproductive phases of the crop growth can be a problem. With the shifting of the off-season to start on March 15, severe water shortage can be avoided. The proposed revised cropping schedules could reduce the irrigation water requirements for the main season and off-season by 30% (equivalent to 60 mm of water) and 19% (equivalent to 37 mm of water), respectively.     

Comparison of different irrigation methods based on the parametric evaluation approach in Dosalegh plain: Iran

Declining water resources and limited clean water reservoirs call for more efficient water use for food production in the future. The objective of this research was to compare different irrigation methods based on a parametric evaluation system in an area of 60,000 ha in the Dosalegh plain of the Khuzestan province, in the southwest of Iran. After the soil properties were analyzed and evaluated, suitability maps were generated for surface, sprinkler and drip irrigation methods, using Remote Sensing (RS) techniques and Geographic Information System (GIS). The results demonstrated that by applying sprinkler and drip irrigation instead of surface irrigation method, the land suitability of 23,790 and 33,261 ha (39.89%) in the Dosalegh plain will improve, respectively. The comparison of the different types of irrigation techniques revealed that the drip and sprinkler irrigations methods were more effective and efficient than that of surface irrigation for improved land productivity. However, the main limiting factor in using either surface or/and sprinkler irrigation methods in this area were soil texture, salinity, and slope, and the main limiting factor in using drip irrigation methods were the calcium carbonate content, soil texture and salinity.     

A GIS-based model to estimate the regionally distributed drought water demand

A GIS-based Water Resources and Agricultural Permitting and Planning System (GWRAPPS) was developed by integrating the Agricultural Field Scale Irrigation Requirements Simulation (AFSIRS) crop water model, a geographic information system (GIS) and a database management system within an ArcGIS framework. GWRAPPS facilitates the quantification of irrigation water for regional planning and farm scale permitting purposes under statistically average to drought conditions using spatially distributed soils, land-use, and long-term daily climate data. In addition, the system provides regional estimates of daily water withdrawals that are necessary for input into conjunctive surface/groundwater models. This paper presents two Florida case studies that demonstrate GWRAPPS’ ability to characterize irrigation needs based on spatially heterogeneous soil and climate data in contrast to a spatially lumped model. The results show that while inclusion of soil heterogeneity is important to capture water requirements at individual farms, regional water demands are adequately captured using each farm’s predominant soil.     

Agricultural water management in a humid region: sensitivity to climate,soil and crop parameters

A sensitivity analysis of irrigation water requirements at the regional scale was conducted for the humid southeastern United States. The GIS-based water resources and agricultural permitting and planning system (GWRAPPS), a regional scale, GIS-based, crop water requirement model, was used to simulate the effect of climate, soil, and crop parameters on crop irrigation requirements. The effects of reference evapotranspiration (ET_o) methods, available soil water holding capacities (ASWHC), crop coefficients (K_c), and crop root zone depths (z) were quantified for 203 ferneries and 152 potato farms. The irrigation demand exhibited a positive relationship with K_c and z, a negative relationship with ASWHC, and seasonal variations depending on the choice of ET_o methods. The average irrigation demand was most sensitive to the choice of K_c with a 10% shift in K_c values resulting in approximately 15% change in irrigation requirements. Most ET_o methods performed reasonably well in estimating annual irrigation requirements as compared to the FAO-56 PM method. However, large differences in monthly irrigation estimates were observed due to the effect of the seasonal variability exhibited by the methods. Our results suggested that the selection of ET_o method is more critical when modeling irrigation requirements at a shorter temporal scale (daily or monthly) as necessary for many applications, such as daily irrigation scheduling, than at a longer temporal scale (seasonal or annual). The irrigation requirements were more sensitive to z when the resultant timing of irrigation coincided with rainfall events. When compared with the overall average of the irrigation requirements differences, the site-to-site variability was low for K_c values and high for the other variables. In particular, soil properties had considerable average regional differences and variability among sites. Thus, the extrapolation of site-specific sensitivity studies may not be appropriate for the determination of regional responses crop water demand.     

遥感技术获取耕地质量评价指标的研究进展分析

耕地质量指标数据获取是耕地质量评价的基础,遥感为相关数据的快速、大面积获取提供了一种新的手段与方法.本文首先分析了耕地质量内涵和功能,在此基础上利用文献计量法对我国近5年耕地质量评价指标研究进行归纳,结合国外土壤质量的研究现状,提出了基于遥感技术的耕地质量评价指标体系,包括地形条件、土壤属性和田间利用状况3个维度.然后...     

Systematic design and evaluation of crop rotations enhancing soil conservation, soil fertility and farm income: a case study for vegetable farms in South Uruguay

Rapid changes in the social and economic environment in which agriculture is developing, together with the deterioration of the natural resource base threatens sustainability of farm systems in many areas of the world. For vegetable farms in South Uruguay, survival in the long term depends upon the development of production systems able to reduce soil erosion, maintain or improve physical and biological soil fertility, and increase farmer’s income to socially acceptable levels. We propose a model-based explorative land use study to support the re-orientation of vegetable production systems in South Uruguay. In this paper we present a new method to quantitatively integrate agricultural, environmental and socio-economic aspects of agricultural land use based on explicit design objectives. We describe the method followed to design and evaluate a wide variety of land use activities for Canelón Grande (South Uruguay) and we illustrate the usefulness of this approach in an ex-ante evaluation of new farming systems using data from 25 farms in this region. Land use activities resulted from systematic combination of crops and inter-crop activities into crop rotations, different crop management techniques (i.e., mechanisation, irrigation and crop protection) and animal production. We identified and quantified all possible rotations and estimated inputs and outputs at crop rotation scale, explicitly considering interactions among crops. Relevant inputs and outputs (i.e., soil erosion, balance of soil organic matter and nutrients, environmental impact of pesticides, labour and machinery requirements, and economic performance) of each land use activity were quantified using different quantitative methods and following the target-oriented approach. By applying the methodology presented in this paper we were able to design and evaluate 336,128 land use activities suitable for the different soil types in Canelón Grande and for farms with different availability of resources, i.e., land, labour, soil quality, capital and water for irrigation. After theoretical evaluation, a large subset of these land use activities showed promise for reducing soil erosion, maintaining soil organic matter content of the soil and increasing farmer’s income, allowing improvement of current farming systems in the region and providing a widely diverse set of strategic options for farmers in the region to choose from. This method can be used as a stand-alone tool to explore options at the field and farm scale or to generate input for optimisation models to explore options at the farm or regional scale.     

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.