中国农业气象 ›› 2023, Vol. 44 ›› Issue (07): 588-598.doi: 10.3969/j.issn.1000-6362.2023.07.004

• 农业生物气象栏目 • 上一篇    下一篇

基于AquaCrop模型评估气候变化下棉花生产的可持续性

王洪博,李国辉,徐雪雯,黄维雄,赵泽艺,高阳,王兴鹏   

  1. 1.塔里木大学水利与建筑工程学院,阿拉尔 843300;2.塔里木大学现代农业工程重点实验室,阿拉尔 843300;3.中国地质大学(武汉)环境学院,武汉 430078;4.中国农业科学院农田灌溉研究所,新乡 453000;5.农业农村部西北绿洲节水农业重点实验室,石河子 832000
  • 收稿日期:2022-09-08 出版日期:2023-07-20 发布日期:2023-07-17
  • 通讯作者: 王兴鹏,博士,教授,主要研究方向为干旱区灌溉排水理论与节水灌溉、作物模型应用,E-mail:13999068354@163.com E-mail:13999068354@163.com
  • 作者简介:王洪博,E-mail:18083915561@163.com
  • 基金资助:
    国家重点研发计划课题(2022YFD1900505);兵团重大科技计划项目(2021AA003);塔里木大学校长基金项目(TDZKSS202146)

Assessing the Sustainability of Cotton Production under Climate Change Based on the AquaCrop Model

WANG Hong-bo, LI Guo-hui, XU Xue-wen, HUANG Wei-xiong, ZHAO Ze-yi, GAO Yang, WANG Xing-peng   

  1. 1.College of Water Hydraulic and Architectural Engineering, Tarim University, Alaer 843300, China; 2.Laboratory of Modern Agricultural Engineering, Tarim University, Alaer 843300; 3.School of Environmental Studies, China University of Geosciences, Wuhan 430078; 4.Farmland Irrigation Research Institute, Chinese Academy of Agricultural Sciences, Xinxiang 453000; 5.Key Laboratory of Northwest Oasis Water-Saving Agriculture, Ministry of Agriculture and Rural Affairs, Shihezi 832000
  • Received:2022-09-08 Online:2023-07-20 Published:2023-07-17

摘要: 运用2017−2018年南疆绿洲区膜下滴灌棉花土壤水分、冠层覆盖度、生物量、蒸散量(ET)及产量(Y)数据,校准和验证AquaCrop模型中作物参数,将数据输入AquaCrop模型气象、作物、灌溉、田间管理模块模拟了6种灌溉水平(18、24、30、36、45和54mm)和5个播期(3月23日、4月3日、4月13日、4月23日和5月3日)共30种情景下南疆绿洲区膜下滴灌棉花的生物量和产量,并分析1988−2017年连续30a棉花产量的稳定性和可持续性。结果表明,AquaCrop模型能够较好地模拟不同灌溉和播期下棉花冠层盖度、地上生物量和土壤水分,归一化均方根误差(NRMSE)均小于20%,协同指数(d)和相关系数(R2)均接近1。AquaCrop模型低估了棉花蒸散量和产量,相对误差(RE)分别为−4.5%~1.2%和−8.6%~−6.8%,但证明了AquaCrop模型可以进行情景模拟。模型预测表明,棉花生产稳定性和可持续性受播期影响较小,而随灌水定额的增大而提高。播期相同时,棉花生物量和产量随灌溉定额的增大而增加,在495mm的灌溉定额下获得了较高的灌溉用水效率,并确保棉花产量无显著下降。同时,在495mm灌溉定额下适当推迟播期至4月13日,可以节约用水36.78mm,如运用早熟棉种于4月23日播种,可以节约用水65.34mm。因此,对于水资源富裕地区可考虑早播获得高产,而水资源匮乏地区在品种与栽培模式配套下,晚播是一种适应现在和未来气候变化下水资源短缺的经济、有效的策略。

关键词: AquaCrop模型, 灌溉定额, 播期, 产量预测

Abstract: Under the condition of limited available water resources, it is increasingly important to optimize irrigation strategies and adjust sowing dates to improve sustainability and profitable production. Authors calibrated and verified the crop parameters in AquaCrop model by using soil moisture, cotton growth, biomass and yield 2017−2018, and inputting the data into the meteorological, crop, irrigation, and field management modules. The biomass and yield of cotton under mulch drip irrigation in the oasis area of southern Xinjiang from 1988 to 2017 were simulated under 30 scenarios of different irrigation (TS1: 18mm, TS2: 24mm, TS3: 30mm, TS4: 36mm, TS5: 45mm, and TS6: 54mm) and sowing dates (D1: March 23, D2: April 3, D3: April 13, D4: April 23, and D5: May 3). The stability and sustainability of cotton production for 30 consecutive years were also analyzed. The results showed that the AquaCrop model could well simulate the cotton canopy coverage, aboveground biomass, and soil moisture under different irrigation and sowing dates. The normalized root mean square error (NRMSE) was less than 20%, and the synergistic index (d) and correlation coefficient (R2) were close to 1. The AquaCrop model underestimated cotton evapotranspiration (ET) and yield (Y) with relative error (RE) of −4.5% to 1.2% and −8.6% to −6.8%, respectively. However, it proves that AquaCrop model can be used for scenario simulation. The model prediction showed that the stability and sustainability of cotton production were less affected by sowing date, but increased with the increase of irrigation quota. With the same sowing date, the cotton biomass and yield increased with the irrigation quota. Under the 495mm irrigation quota, higher irrigation water efficiency was obtained, and the cotton yield was not significantly reduced. At the same time, under the 495mm irrigation quota, if the sowing date was postponed to April 13, it could save 36.78mm of water. If early maturing cotton seeds were used for sowing on April 23, it could save 65.34mm of water. Therefore, for regions with rich water resources, early sowing can be considered to obtain high yield, while for regions with poor water resources, late sowing is an economic and effective strategy to adapt to the current and future climate change and the shortage of water resources under the combination of varieties and cultivation models.

Key words: AquaCrop model, Irrigation quota, Planting date, Predicting yield