基于留一交叉验证法的APSIM-Maize产量模拟

doi:10.3724/SP.J.1006.2023.23064

作物学报 ›› 2023, Vol. 49 ›› Issue (10): 2854-2860.doi: 10.3724/SP.J.1006.2023.23064

• 研究简报 • 上一篇

基于留一交叉验证法的APSIM-Maize产量模拟

杨雪宁¹^,²(), 张永强¹(), 张选泽¹, 马宁¹, 张俊梅³

¹中国科学院地理科学与资源研究所陆地水循环及地表过程重点实验室, 北京 100101
²中国科学院大学中丹学院, 北京 100101
³达拉特旗农业技术推广中心, 内蒙古达拉特 014300

收稿日期:2023-09-27 接受日期:2023-04-18 出版日期:2023-10-12 网络出版日期:2023-04-27
通讯作者: 张永强, E-mail: zhangyq@igsnrr.ac.cn
作者简介:E-mail: xnyang1999@163.com
基金资助:
“科技兴蒙”行动重点专项(十大孔兑综合治理与水资源集约高效利用集成示范) ()和 ()(KJXM-EEDS-2020005);鄂尔多斯科技重大专项(鄂尔多斯陆地生态系统碳储量、碳汇核算及潜力评价)(2022EEDSKJZDZX016)

Yield simulation from APSIM-Maize by using the leave-one-out cross validation approach

YANG Xue-Ning¹^,²(), ZHANG Yong-Qiang¹(), ZHANG Xuan-Ze¹, MA Ning¹, ZHANG Jun-Mei³

¹Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
²Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100101, China
³Dalat Banner Agricultural and Animal Husbandry Technology Extension Center, Dalat 014300, Inner Mongolia, China

Received:2023-09-27 Accepted:2023-04-18 Published:2023-10-12 Published online:2023-04-27
Contact: E-mail: zhangyq@igsnrr.ac.cn
Supported by:
“Science for a Better Development of Inner Mongolia” Program (Integrated Demonstration of Comprehensive Management and Effective Utilization of Water Resources in the Ten Kongduis)(KJXM-EEDS-2020005);Bureau of Science and Technology of the Inner Mongolia Autonomous Region, and the Ordos Science & Technology Plan (Calculation and Evaluation of Carbon Storage and Carbon Sink in Terrestrial Ecosystem in Ordos)(2022EEDSKJZDZX016)

摘要/Abstract

摘要：

作物生长模型APSIM广泛应用于作物估产和农业生产管理中, 在观测数据有限的情况下, 开展留一交叉验证是提高模型模拟能力的关键途径。本研究以内蒙古十大孔兑地区春玉米为研究对象, 量化分析了APSIM-Maize模型模拟2012—2019年间玉米产量对关键参数的敏感性, 并根据参数敏感性强弱对APSIM-Maize模型进行交叉验证与参数率定, 提高了模型模拟能力。主要结果为: (1) 影响春玉米产量的敏感性参数由强到弱依次是: 蒸腾效率系数、辐射利用效率、开花到成熟的积温、出苗到拔节的积温、开花到灌浆的积温、潜在灌浆速率、光周期和最大穗粒数; (2) 交叉验证时, APSIM-Maize模型各参数变异系数在1.06%~23.32%之间波动, 总体上模型参数变异性小, 可靠性高; (3) APSIM-Maize模型经过参数率定后的模拟产量与实测产量具有较好的一致性(R²= 0.72, RMSE = 401.5 kg hm^-2), 模型在十大孔兑地区春玉米产量的评估中表现出较好的适应性。本研究为在农田试验数据有限情况下提高模型率定参数的可靠性提供了新的研究思路和科学依据。

关键词: APSIM-Maize模型, 交叉验证, 春玉米

Abstract:

The Agricultural Production Systems Simulator (APSIM) has been extensively used in crop yield estimation and agricultural management. Leave-one-out cross validation is a key way to improve the model simulation capability with the limited filed data. In this study, we evaluate the parameters sensitivity to maize yield and evaluate the reliability of parameters with the leave-one-out cross validation based on the sensitivity rank of parameters. These results showed that: (1) The sensitive parameters for maize yield were ranked in descending order as: transpiration efficiency coefficient, radiation use efficiency, thermal time from flower to maturity, thermal time from emergence to end of juvenile phase, thermal time from flowering to start grain-filling, potential grain growth rate, photoperiod slope, and potential grains per head. (2) The coefficients of variation of parameters fluctuated from 1.06% to 23.32%, which indicates that the variation of parameter was small and the reliability of parameters was high. (3) The adjusted APSIM-Maize model performed well in simulating spring maize yield (R² = 0.72; RMSE = 401.5 kg hm^-2), which indicates that the model had great adaptability in estimating spring maize yield in the Ten Kongduis. Our study provides an insight to improve the reliability of parameters with limited field data.

Key words: APSIM-Maize model, cross validation, spring maize

杨雪宁, 张永强, 张选泽, 马宁, 张俊梅. 基于留一交叉验证法的APSIM-Maize产量模拟[J]. 作物学报, 2023, 49(10): 2854-2860.

YANG Xue-Ning, ZHANG Yong-Qiang, ZHANG Xuan-Ze, MA Ning, ZHANG Jun-Mei. Yield simulation from APSIM-Maize by using the leave-one-out cross validation approach[J]. Acta Agronomica Sinica, 2023, 49(10): 2854-2860.

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参考文献 28

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年份Year	产量Yield (kg hm^-2)	种植密度Plant density (plant m^-3)
2012	11,801.41	6.30-6.75
2013	12,141.89	6.30-6.75
2014	11,967.90	6.75-7.50
2015	11,237.44	6.75-7.50
2016	11,606.40	6.75-7.50
2017	11,675.40	7.50-8.25
2018	11,859.90	7.50-8.25
2019	12,429.90	7.50-8.25

参数名称 Parameter name	交叉验证 Cross validation								CV (%)	率定 Calibration
参数名称 Parameter name	1	2	3	4	5	6	7	8	CV (%)	率定 Calibration
transp_eff_cf	0.012	0.013	0.012	0.013	0.012	0.012	0.012	0.012	3.53	0.012
rue	1.84	1.73	1.81	1.81	1.82	1.81	1.8	1.9	2.42	1.82
tt_flower_to_maturity	740	729	733	737	723	740	726	748	1.06	723
tt_emerg_to_endjuv	180	174	187	170	200	192	186	177	5.07	180
tt_flower_to_start_grain	246	142	222	238	225	244	225	268	15.39	225
grain_gth_rate	16.81	9.06	11.37	15.56	11.39	15.55	17.02	19.95	23.32	11.41
photoperiod_slope	14	12.07	14.5	21.67	13.48	13.96	16.06	14.06	18.24	20.08

基于留一交叉验证法的APSIM-Maize产量模拟

Yield simulation from APSIM-Maize by using the leave-one-out cross validation approach

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