AquaCrop模型与模型预测控制相结合的灌溉决策方法

doi:10.14088/j.cnki.issn0439-8114.2026.09.030

湖北农业科学 ›› 2026, Vol. 65 ›› Issue (9): 186-193.doi: 10.14088/j.cnki.issn0439-8114.2026.09.030

AquaCrop模型与模型预测控制相结合的灌溉决策方法

孙淼¹, 刘湃^2,3, 赵东保², 李艺超²

1.河南省自然资源监测和国土整治院,郑州 450000;
2.华北水利水电大学测绘与地理信息学院,郑州 450046;
3.中交第二公路工程局有限公司,西安 710000

收稿日期:2026-06-10 出版日期:2026-09-25 发布日期:2026-09-17
通讯作者: 赵东保（1979-）,男,河南宜阳人,教授,博士,主要从事时空数据挖掘、智慧灌溉研究,（电子信箱）zhaodongbao@ncwu.edu.cn。
作者简介:孙淼（1981-）,男,湖北大悟人,高级工程师,主要从事水文地质、工程地质、水利灌溉研究,（电子信箱）sunm429@163.com
基金资助:
四川省科技计划项目重点研发项目（2022YFN0022）

Irrigation decision-making method combining the AquaCrop model with model predictive control

SUN Miao¹, LIU Pai^2,3, ZHAO Dong-bao², LI Yi-chao²

1. Institute of Natural Resources Monitoring and Comprehensive Land Improvement of Henan Province, Zhengzhou 450000, China;
2. College of Surveying and Geo-informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China;
3. CCCC Second Highway Engineering Co., Ltd., Xi’an 710000, China

Received:2026-06-10 Published:2026-09-25 Online:2026-09-17

摘要/Abstract

摘要： 针对传统基于AquaCrop模型的灌溉决策对短期气象变化的动态响应不足,灌溉方案调整滞后的问题构建了一种AquaCrop模型与模型预测控制（MPC）相结合的灌溉决策方法。利用AquaCrop模型确定夏玉米各生育阶段的灌溉上限,将土壤水分平衡、地表径流、深层渗漏和短期降水预报信息纳入MPC决策框架,构建AquaCrop-MPC动态灌溉决策模型,通过滚动优化确定灌溉量。以河南省商丘市粉砂质壤土条件下的夏玉米为研究对象开展仿真试验。结果表明,在总供水量为100、130和160 mm条件下,与AquaCrop预设灌溉制度相比,AquaCrop-MPC方法的模拟产量分别提高0.4%、0.3%和0.1%,灌溉用水量分别减少36.0%、42.3%和40.0%,灌溉水生产效率分别提高56.9%、74.0%和66.9%,水分利用效率分别提高8.3%、9.1%和8.3%。该方法能够利用短期降水预报信息动态调整灌溉量,在维持作物模拟产量的同时减少灌溉用水,可为供水受限条件下夏玉米智能灌溉决策提供科学参考。

关键词: AquaCrop模型, 模型预测控制, 智能灌溉, 灌溉决策, 夏玉米

Abstract: Traditional irrigation decision-making methods based on the AquaCrop model have limited capability for dynamic response, making it difficult to promptly adjust irrigation schedules according to short-term meteorological variations. An irrigation decision-making method integrating the AquaCrop model with model predictive control (MPC) was developed. The AquaCrop model was used to determine irrigation upper limits for different growth stages of summer maize. Soil water balance, surface runoff, deep percolation, and short-term rainfall forecast information were incorporated into the MPC decision-making framework. An AquaCrop-MPC dynamic irrigation decision-making model was constructed, and irrigation amounts were determined through rolling-horizon optimization. A simulation experiment was conducted for summer maize grown in silt loam soil in Shangqiu City, Henan Province. Under total water supply levels of 100, 130, and 160 mm, the AquaCrop-MPC method increased simulated yield by 0.4%, 0.3%, and 0.1%, respectively, reduced irrigation water use by 36.0%, 42.3%, and 40.0%, respectively, increased irrigation water productivity by 56.9%, 74.0%, and 66.9%, respectively, and improved water use efficiency by 8.3%, 9.1%, and 8.3%, respectively, compared with the preset irrigation schedules determined by AquaCrop. The proposed method dynamically adjusted irrigation amounts using short-term rainfall forecast information and reduced irrigation water use while maintaining simulated crop yield. These findings provided a scientific reference for irrigation decision-making of summer maize under limited water supply conditions.

Key words: AquaCrop model, model predictive control, smart irrigation, irrigation decision-making, summer maize

中图分类号:

S161.4

孙淼, 刘湃, 赵东保, 李艺超. AquaCrop模型与模型预测控制相结合的灌溉决策方法[J]. 湖北农业科学, 2026, 65(9): 186-193.

SUN Miao, LIU Pai, ZHAO Dong-bao, LI Yi-chao. Irrigation decision-making method combining the AquaCrop model with model predictive control[J]. HUBEI AGRICULTURAL SCIENCES, 2026, 65(9): 186-193.

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AquaCrop模型与模型预测控制相结合的灌溉决策方法

Irrigation decision-making method combining the AquaCrop model with model predictive control

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