中国农业科学 ›› 2017, Vol. 50 ›› Issue (17): 3286-3299.doi: 10.3864/j.issn.0578-1752.2017.17.004

• 耕作栽培·生理生化·农业信息技术 • 上一篇    下一篇

AquaCrop作物模型应用研究进展

孙仕军1,张琳琳1,陈志君1,孙娟2

 
  

  1. 1沈阳农业大学水利学院,沈阳 110866;2辽宁省水文水资源勘测局,沈阳110003
  • 收稿日期:2017-01-16 出版日期:2017-09-01 发布日期:2017-09-01
  • 作者简介:孙仕军,E-mail:sunshijun2000@yeah.net
  • 基金资助:
    国家公益性行业(农业)科研专项(201303125)、国家自然科学基金(51609137)、国家留学基金资助项目(201308210026)、辽宁省教育厅项目(2009A630)

Advances in AquaCrop Model Research and Application

SUN ShiJun1, ZHANG LinLin1, CHEN ZhiJun1, SUN Juan2   

  1. 1College of Water Conservancy, Shenyang Agricultural University, Shenyang 110866; 2Liaoning Hydrology and Water Resources Survey Bureau, Shenyang 110003
  • Received:2017-01-16 Online:2017-09-01 Published:2017-09-01

摘要: AquaCrop是FAO于2009年研发的一款新型作物模型,它以输入参数少、界面简单等优点被广泛应用于生产实践中。论文基于AquaCrop模型原理和特点,深入探讨了AquaCrop模型国内外应用研究进展。当前,AquaCrop模型在灌溉策略、气候变化下的情景模拟以及与其他模型联合应用等方面取得了显著进展。但是,该模型在应用过程中还存在若干缺陷。一是模型在保守参数缺少验证的情况下,会使得模拟精度不稳定;二是由于土壤空间变异性的客观存在,模型在由点位向面上扩展时应用效果不佳;三是当前对雨养区作物生长模拟研究还很少,且其非保守参数难以准确确定;四是目前该模型生理、养分和水养互作模块尚不够完善,未考虑作物病虫害和品种遗传差异,当作物生长遭受水分、盐分或温度等严重胁迫时会导致模拟精度下降。今后在模型应用时,可利用多年数据对保守参数进行校正,将区域同一站点多年数据和多站点相关数据相结合调试模型非保守参数;其次,应加强雨养地区模拟研究,从而扩大模型应用范围。开发者应进一步完善AquaCrop模型子模块,为提高模拟精度和拓宽应用范围提供支撑。

关键词: AquaCrop模型, 灌溉策略, 情景模拟, 作物模型

Abstract: AquaCrop is a kind of new crop model developed by FAO in 2009. It is widely used in agricultural fields, because it need fewer parameters, and can provide users more simple interface, compared with other similar crop models. According to the principle and characteristics of the AquaCrop model, some further discussions were developed on the application of this model at domestic and abroad. Analysis shows that, the AquaCrop model has achieved remarkable results in irrigation strategy, scenario simulation under climate change and joint application with other models. However, at present, the model is not perfect enough, because of the following reasons. Firstly, the lack of verification of the conservative parameters of the model usually results in lower simulation accuracy. Secondly, the objective existence of spatial variability of soil, which is commonly suitable and helpful so much when applied at single experimental station, but when applied to larger area, some more stations and data are needed. Thirdly, less research on crop growth in rain-fed areas was conducted, and its non-conservative parameters are difficult to be obtained accurately. Finally, the physiological modules, nutrient modules and interaction modules of water and nutrient are not perfect, and the crop genetic varieties and pests are not included, which result in lower simulation accuracy under severe stress conditions. It is concluded that, when the model is applied, the conservative parameters should be modified by using many years' data of crop, and non-conservative modeling parameters should be corrected by combining multi-year data at a single site with multi-sites data in the experimental region. Currently, scholars and researches are supposed to strengthen the research in rain-fed areas, enlarge the scope of application of the model, and related designers should develop more sub-modules of AquaCrop model to increase the modeling accuracy and broaden its application scope.

Key words: AquaCrop model, irrigation strategy, scene simulation, crop model