基于WOFOST模型与遥感数据的旱作玉米估产及精度评价

doi:10.14088/j.cnki.issn0439-8114.2024.08.035

湖北农业科学 ›› 2024, Vol. 63 ›› Issue (8): 209-215.doi: 10.14088/j.cnki.issn0439-8114.2024.08.035

基于WOFOST模型与遥感数据的旱作玉米估产及精度评价

侯晨连^a, 张吴平^a, 王国芳^b, 李富忠^a

山西农业大学,a.软件学院; b.资源与环境学院,山西太谷 030801

收稿日期:2022-10-17 出版日期:2024-08-25 发布日期:2024-09-05
通讯作者: 李富忠,教授,主要从事智慧农业研究,（电子信箱）sxaulfz@126.com。
作者简介:侯晨连（1997-）,女,山西阳城人,在读硕士研究生,研究方向为农业工程,（电话）18434761458（电子信箱）hcl1580128118@163.com。
基金资助:
国家重点研发计划项目（2021YFD1901101）

Yield estimation and precision evaluation of dry-fed maize based on WOFOST model and remote sensing data

HOU Chen-lian^a, ZHANG Wu-ping^a, WANG Guo-fang^b, LI Fu-zhong^a

a. School of Software; b. College of Resources and Environment, Shanxi Agricultural University, Taigu 030801, Shanxi, China

Received:2022-10-17 Published:2024-08-25 Online:2024-09-05

摘要/Abstract

摘要： 选取黄土高原东部地区的山西省灵丘县、介休县、隰县与盐湖县为研究区域,利用2005—2012年研究区域的田间观测数据,采用EFAST方法分析模型参数敏感性,采用试错法对玉米的生长发育参数进行调整;在此基础上融合MCD15A3H遥感数据,以叶面积指数为耦合变量,采用SUBPLEX算法将遥感叶面积指数（LAI）数据同化到校准的WOFOST模型中,并再次模拟各区域玉米的生长发育过程。结果表明,校准后的WOFOST模型对生育期和产量的模拟结果较好,生育期的模拟值与实测值的平均误差均小于3 d,产量的模拟值与实测值的相关系数（r）为0.80,均方根误差（RMSE）为956 kg/hm²;将遥感数据与WOFOST模型同化后,产量的模拟值和实测值的r由0.80提高至0.91,RMSE从956 kg/hm²降低到660 kg/hm²。

关键词: 数据同化, WOFOST模型, 遥感数据, 旱作玉米, 精度评价

Abstract: Lingqiu County, Jiexiu County, Xi County and Yanhu County of Shanxi Province in the eastern part of the Loess Plateau were selected as the study area. Field observation data from 2005 to 2012 were used to analyze the sensitivity of model parameters by using EFAST method, and the growth parameters of maize were adjusted by trial and error method. On this basis, MCD15A3H remote sensing data was fused, leaf area index （LAI） data, which was taken as the coupling variable was assimilated into the calibrated WOFOST model using SUBPLEX algorithm, and the growth and development process of maize in each region was simulated again. The results showed that the calibrated WOFOST model had better simulation results for growth period and yield. The average error between simulated value and measured value in the growth period was less than 3 days, the correlation coefficient （r） between simulated value and measured value of yield was 0.80, and the root mean square error （RMSE） was 956 kg/hm². After assimilating remote sensing data with WOFOST model, the r of simulated and measured yield increased from 0.80 to 0.91, and the RMSE decreased from 956 kg/hm² to 660 kg/hm².

Key words: data assimilation, WOFOST model, remote sensing data, dryland corn, precision evaluation

中图分类号:

TP79

侯晨连, 张吴平, 王国芳, 李富忠. 基于WOFOST模型与遥感数据的旱作玉米估产及精度评价[J]. 湖北农业科学, 2024, 63(8): 209-215.

HOU Chen-lian, ZHANG Wu-ping, WANG Guo-fang, LI Fu-zhong. Yield estimation and precision evaluation of dry-fed maize based on WOFOST model and remote sensing data[J]. HUBEI AGRICULTURAL SCIENCES, 2024, 63(8): 209-215.

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基于WOFOST模型与遥感数据的旱作玉米估产及精度评价

Yield estimation and precision evaluation of dry-fed maize based on WOFOST model and remote sensing data

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