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作物杂志,2025, 第2期: 215–221 doi: 10.16035/j.issn.1001-7283.2025.02.029

• 生理生化·植物营养·栽培耕作 • 上一篇    下一篇

WOFOST模型对江淮地区水稻生长发育模拟的适应性评价

伍露1(), 张皓2, 杨霏云1, 郭尔静1, 斯林林3, 曹凯3, 程陈4()   

  1. 1中国气象局气象干部培训学院，100081，北京
    2上海市生态气象和卫星遥感中心，200030，上海
    3浙江省农业科学院环境资源与土壤肥料研究所，310021，浙江杭州
    4丽水学院生态学院，323000，浙江丽水
  • 收稿日期:2023-11-07 修回日期:2024-05-08 出版日期:2025-04-15 发布日期:2025-04-16
  • 通讯作者: 程陈
  • 作者简介:伍露，主要从事农业资源高效利用研究，E-mail：duyulu5566@163.com
  • 基金资助:
    国家自然科学基金(32101294);中国气象局创新发展专项(CXFZ2022J053);丽水学院人才启动基金项目(6604CC01Z)

Adaptability Assessment of WOFOST Model for Simulating Rice Growth and Development in the Jianghuai Region

Wu Lu1(), Zhang Hao2, Yang Feiyun1, Guo Erjing1, Si Linlin3, Cao Kai3, Cheng Chen4()   

  1. 1China Meteorological Administration Training Center, Beijing 100081, China
    2Shanghai Ecological Metorology and Satellite Remote Sensing Center, Shanghai 200030, China
    3Institute of Environment and Resource & Soil Fertilizer, Zhejang Academy of Agricultural Sciences, Hangzhou 310021, Zhejiang, China
    4College of Ecology, Lishui University, Lishui 323000, Zhejiang, China
  • Received:2023-11-07 Revised:2024-05-08 Online:2025-04-15 Published:2025-04-16
  • Contact: Cheng Chen

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摘要：

通过收集2006-2012年江淮地区水稻生长发育和气象资料，对WOFOST模型进行调参验证，确定了关键发育阶段内所需积温、比叶面积、分配系数和枯萎速率等作物参数，并评价了模型在江淮地区的适应性。结果表明，WOFOST模型可以较好地模拟江淮地区水稻生长发育动态变化过程，开花期、成熟期、叶面积指数（LAI）、叶干物质量、茎干物质量、穗干物质量、地上干物质量和产量观测值与模拟值的RMSE分别为1.73~4.66 d、1.94~4.42 d、0.39~2.51、（0.43~0.86）×103 kg/hm2、（0.86~1.52）×103 kg/hm2、（0.52~1.21）×103 kg/hm2、（1.38~1.96）×103 kg/hm2和（0.45~1.33）×103 kg/hm2；NRMSE分别为0.75%~1.96%、0.74%~1.49%、8.74%~43.40%、14.94%~30.55%、18.16%~28.84%、9.44%~22.81%、11.33%~15.89%和5.49%~13.43%，其中合肥水稻发育期，叶、茎、穗和地上部干物质量，镇江水稻LAI和荆州水稻产量模拟效果最优。水稻LAI、叶和茎干物质量随移栽天数增加呈现先上升后下降的变化趋势，而穗和地上部干物质量随移栽天数增加呈现逐渐上升的趋势。

关键词: WOFOST模型, 江淮地区, 水稻, 生长发育, 适应性

Abstract:

This study collected rice growth and meteorological data from 2006 to 2012 in the Jianghuai region and validated the WOFOST model by adjusting plant genetic parameters. The following crop parameters for determining development stages and rice growth, such as accumulated temperature, specific leaf area, distribution coefficient and leaf senescence rate, were calibrated, and the adaptability of the model in the Jianghuai region was evaluated. The results showed that the WOFOST model can effectively simulate the dynamic changes in rice growth and development in the Jianghuai region. The RMSE of the measured and simulated values for flowering period, maturity period, leaf area index (LAI), leaf dry matter weight, stem dry matter weight, panicle dry matter weight, aboveground dry matter weight, and yield were 1.73-4.66 d, 1.94-4.42 d, 0.39-2.51, (0.43-0.86)× 103 kg/ha, (0.86-1.52)×103 kg/ha, (0.52-1.21)×103 kg/ha, (1.38-1.96)×103 kg/ha, and (0.45-1.33)×103 kg/ha, respectively and the NRMSE were 0.75%-1.96%, 0.74%-1.49%, 8.74%-43.40%, 14.94%-30.55%, 18.16%- 28.84%, 9.44%-22.81%, 11.33%-15.89%, and 5.49%-13.43%, respectively. Among different study stations, rice development stage, dry matter weight of leaves, stems, panicles, and aboveground in Hefei, LAI in Zhenjiang, and yield in Jingzhou presented the most accurate simulation results. The LAI, leaf and stem dry matter weight of rice first increased and then decreased with the increase of transplanting days, while the dry matter weight of panicles and aboveground parts showed a gradually increasing trend with the increase of transplanting days.

Key words: WOFOST model, Jianghuai region, Rice, Growth and development, Adaptability

表1

江淮地区WOFOST模型水稻发育期模块的遗传参数

站点
Station		 初始
发育期
DVSI		 初始总干
物质量
TDWI
(kg/hm2)		 出苗期—
开花期
所需积温
TSUM1 (℃·d)		 开花期—
成熟期
所需积温
TSUM2 (℃·d)
合肥Hefei 0.30 350 1482 435
荆州Jingzhou 0.23 330 1345 405
武汉Wuhan 0.28 110 1350 440
兴华Xinghua 0.00 310 1210 455
徐州Xuzhou 0.35 180 1610 505
镇江Zhenjiang 0.33 130 1490 610

表2

江淮地区WOFOST模型水稻生长模块的遗传参数

站点
Station		 发育阶段
Developmental stage		 比叶面积
SLA (hm2/kg)		 发育阶段
Developmental stage		 叶分配系数
FL (kg/kg)		 茎分配系数
FS (kg/kg)		 穗分配系数
FO (kg/kg)		 发育阶段
Developmental stage		 枯萎速率
RFSE
合肥
Hefei		 0.10 0.0027 0.00 0.40 0.60 0.00 0.00 0.45
0.70 0.0029 0.50 0.45 0.55 0.00 2.00 0.50
0.98 0.0020 0.71 0.58 0.42 0.60
1.30 0.0029 0.95 0.10 0.30 0.80
1.40 0.0010 1.00 0.00 0.20 1.00
2.00 0.0010 2.00 0.00 0.00 1.00
荆州
Jingzhou		 0.10 0.0017 0.00 0.40 0.60 0.00 0.00 0.30
0.58 0.0019 0.58 0.52 0.48 0.00 2.00 0.40
0.86 0.0020 0.80 0.38 0.62 0.00
1.10 0.0015 0.85 0.00 0.00 1.00
1.40 0.0015 0.90 0.00 0.00 1.00
2.00 0.0010 1.00 0.00 0.00 1.00
2.00 0.00 0.00 1.00
武汉
Wuhan		 0.10 0.0025 0.00 0.55 0.46 0.00 0.00 0.50
0.66 0.0030 0.25 0.58 0.42 0.00 2.00 0.60
0.90 0.0027 0.50 0.45 0.55 0.00
1.30 0.0018 0.72 0.51 0.49 0.00
1.40 0.0010 0.90 0.05 0.28 0.67
2.00 0.0010 1.00 0.00 0.01 0.99
2.00 0.00 0.00 1.00
兴华
Xinghua		 0.00 0.0020 0.00 0.40 0.60 0.00 0.00 0.60
0.60 0.0026 0.50 0.55 0.45 0.00 2.00 0.60
0.90 0.0032 0.70 0.35 0.65 0.00
1.00 0.0022 0.90 0.30 0.15 0.55
2.00 0.0022 1.00 0.00 0.15 0.85
1.10 0.00 0.00 1.00
2.00 0.00 0.00 1.00
徐州
Xuzhou		 0.10 0.0017 0.00 0.40 0.60 0.00 0.00 0.50
0.70 0.0019 0.50 0.45 0.55 0.00 2.00 0.40
0.95 0.0024 0.85 0.38 0.62 0.00
1.10 0.0015 0.90 0.10 0.55 0.35
1.40 0.0015 1.00 0.00 0.20 0.80
2.00 0.0010 2.00 0.00 0.00 1.00
镇江
Zhenjiang		 0.10 0.0017 0.00 0.40 0.60 0.00 0.00 0.30
0.58 0.0019 0.58 0.52 0.48 0.00 2.00 0.40
0.86 0.0020 0.80 0.38 0.62 0.00
1.10 0.0015 0.85 0.00 0.40 0.60
1.40 0.0015 0.90 0.00 0.00 1.00
2.00 0.0010 1.00 0.00 0.00 1.00
2.00 0.00 0.00 1.00

图1

基于WOFOST模型的江淮地区水稻关键发育期验证

图2

基于WOFOST模型的江淮地区水稻生长过程验证图

图3

基于WOFOST模型的江淮地区水稻生长指标动态模拟过程

[1] 程陈, 冯利平, 薛庆禹, 等. 日光温室黄瓜生长发育模拟模型. 应用生态学报, 2019, 30(10):3491-3500.
[2] 程陈, 董朝阳, 黎贞发, 等. 日光温室芹菜外观形态及干物质积累分配模拟模型. 农业工程学报, 2021, 37(10):142-151.
[3] 何强, 陈立云, 邓华凤, 等. 水稻C815S及其同源株系的育性光温特性. 作物学报, 2007, 33(2):262-268.
[4] Qiu R, Li L, Liu C, et al. Evapotranspiration estimation using a modified crop coefficient model in a rotated rice-winter wheat system. Agricultural Water Management, 2022,264:107501.
[5] Paleari L, Movedi E, Zoli M, et al. Sensitivity analysis using Morris:Just screening or an effective ranking method?. Ecological Modelling, 2021, 455(6):109648.
[6] 黄健熙, 贾世灵, 马鸿元, 等. 基于 WOFOST 模型的中国主产区冬小麦生长过程动态模拟. 农业工程学报, 2017, 33(10):222-228.
[7] Wu L, Feng L P, Zhang Y, et al. Comparison of five wheat models simulating phenology under different sowing dates and varieties. Agronomy Journal, 2017, 109(4):1280-1293.
[8] 李秀芬, 马树庆, 赵慧颖, 等. 基于WOFOST模型的内蒙古河套灌区玉米低温冷害评价. 中国农业气象, 2016, 37(3):352-360.
[9] 董智强, 王萌萌, 李鸿怡, 等. WOFOST模型对山东省夏玉米发育期与产量模拟的适用性评价. 作物杂志, 2019(5):159-165.
[10] Mongiano G, Titone P, Tamborini L, et al. Advancing crop modelling capabilities through cultivar-specific parameters sets for the Italian rice germplasm. Field Crops Research, 2019,240:44-54.
[11] Roberto C, Marco A, Gianni B, et al. Multi-metric evaluation of the models WARM, CropSyst, and WOFOST for rice. Ecological Modelling, 2009, 220(11):1395-1410.
[12] Eitzinger J, Trnka M, Hosch J, et al. Comparison of CERES, WOFOST and SWAP models in simulating soil water content during growing season under different soil conditions. Ecological Modelling, 2004, 171(3):223-246.
[13] Gardner A S, Maclean I M D, Gaston K J, et al. Forecasting future crop suitability with microclimate data. Agricultural Systems, 2021,190:103084.
[14] Singh V, Chaudhari R, Kumar N, et al. Simulation of wheat (Triticum aestivum L.) yield using WOFOST model under different management levels. AkiNik Publications, 2018, 7(5):1425-1428.
[15] 谢文霞, 严力蛟, 王光火. 运用WOFOST模型对浙江水稻潜在生长过程的模拟与验证. 中国水稻科学, 2006, 20(3):319-323.
[16] 谢晓金, 李秉柏, 李映雪, 等. 长江流域近55年水稻花期高温热害初探. 江苏农业学报, 2009, 25(1):28-32.
[17] 魏瑞江, 郑昌玲, 王鑫, 等. WOFOST作物生长模型在国内应用研究进展. 气象科学, 2023, 43(3):402-411.
[18] 程陈, 李春, 李文明, 等. 园艺作物发育期和采收期模拟模型的最优模拟路径. 农业工程学报, 2023, 39(12):158-167.
[19] Cheng C, Feng L P, Barcena J F B, et al. A growth model based on standardized growing degree days for hydroponic fresh cut tulip in solar greenhouses. European Journal of Horticultural Science, 2022, 87(4):1-13.
[20] 何亮, 侯英雨, 赵刚, 等. 基于全局敏感性分析和贝叶斯方法的WOFOST作物模型参数优化. 农业工程学报, 2016, 32(2):169-179.
[21] 陈艳玲, 顾晓鹤, 宫阿都, 等. 基于遥感信息和WOFOST模型参数同化的冬小麦单产估算方法研究. 麦类作物学报, 2018, 38(9):1127-1136.
[22] 秦格霞, 吴静, 李纯斌, 等. 不同草地类型WOFOST模型参数敏感性分析. 草业学报, 2022, 31(5):13-25.
[23] Jiang G Y, Zhang W J, Xu M G, et al. Manure and mineral fertilizer effects on crop yield and soil carbon sequestration: a meta‐ analysis and modeling across China. Global Biogeochemical Cycles, 2018, 32(11):1659-1672.
[24] Liu X, Li M, Guo P, et al. Optimization of water and fertilizer coupling system based on rice grain quality. Agricultural Water Management, 2019,221:34-46.
[25] Yang J H, Liu H X, Zhu G M, et al. Diversity analysis of antagonists from rice-associated bacteria and their application in biocontrol of rice diseases. Journal of Applied Microbiology, 2010, 104(1):91-104.
[26] Mustafa S M T, Nossent J, Ghysels G, et al. Integrated Bayesian Multi-model approach to quantify input, parameter and conceptual model structure uncertainty in groundwater modeling . Environmental Modelling & Software, 2020,126:104654.
[27] 许伟, 秦其明, 张添源, 等. SCE标定结合EnKF同化遥感和WOFOST模型模拟冬小麦时序LAI. 农业工程学报, 2019, 35(14):166-173.
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