Assimilation of Observations with Crop Growth Model Based on the Constrained Analysis of Parameters

Sun Linli; Ma Yuping; Jing Yuanshu; E Youhao; Zou Yandong; Xing Kaiyu

Vol.24, NO.3, 2013

Article Contents

Article Navigation > Journal of Applied Meteorological Science > 2013 > 24(3): 287-296

Sun Linli, Ma Yuping, Jing Yuanshu, et al. Assimilation of observations with crop growth model based on the constrained analysis of parameters. J Appl Meteor Sci, 2013, 24(3): 287-296.

Citation:

Sun Linli, Ma Yuping, Jing Yuanshu, et al. Assimilation of observations with crop growth model based on the constrained analysis of parameters. J Appl Meteor Sci, 2013, 24(3): 287-296.

Sun Linli, Ma Yuping, Jing Yuanshu, et al. Assimilation of observations with crop growth model based on the constrained analysis of parameters. J Appl Meteor Sci, 2013, 24(3): 287-296.

Citation:

Sun Linli, Ma Yuping, Jing Yuanshu, et al. Assimilation of observations with crop growth model based on the constrained analysis of parameters. J Appl Meteor Sci, 2013, 24(3): 287-296.

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Assimilation of Observations with Crop Growth Model Based on the Constrained Analysis of Parameters

1.
Chinese Academy of Meteorological Sciences, Beijing 100081
2.
Tongliao Meteorological Bureau of Inner Mongolia, Tongliao 028000
3.
Nanjing University of Information Science & Technology, Nanjing 210044
4.
Sichuan Provincial Climate Center, Chengdu 610072

Received Date: 2012-08-17
Rev Recd Date: 2013-02-26
Publish Date: 2013-06-30

Abstract

Abstract

Data assimilation may support regional applications of crop growth model, in which the selection of parameters and initial value of variables need lots of optimizing. Constraint reflects the controllability of observations on model parameters or variable initial value. Optimization of constrained parameters will most likely reach optimal results in data assimilation. An assimilation method of observations and crop growth model is established based on constrained analysis of model parameters. Sensitive parameters and initial value of the state variables in crop growth models are first selected using sensitivity analysis based on optimization algorithms. Constrained parameters of different variables are then obtained through constrained analysis, which is defined according to the relation of goodness of fit (Q_T) and optimization results of parameters. The optimal value of each parameter is got by means of combinatorial optimization of constrained parameters at last. Based on the constrained analysis, observations of summer maize leaf area index (LAI) in North China can constrain initial total crop dry weight (T_DWI), initial specific leaf area (S_LA1), initial maximum leaf CO₂ assimilation rate (A_max1) and life span of leaves growing at 35 Celsius (S_PAN) in WOFOST under optimal soil water condition. Dry weight of living storage organs (WSO) with the same results as the LAI is achieved. Total above ground production (TAGP) still include specific leaf area between jointing stage and tasseling stage (S_LA2). Constrained parameters of LAI under water stress level include not only T_DWI, S_LA1, A_max1, and S_PAN, but also initial amount of available water in total root zone (W_AV), maximum daily increase in rooting depth (R_RI), and maximum initial and soil moisture content of the initial root depth (SMLIM). Parameters constrained by LAI, WSO, TAGP and soil moisture content (SM) are not exactly the same with each other. The values of crop and soil parameters and initial conditions in WOFOST are obtained using observations over North China in 2009. Simulation shows that WOFOST can reflect the process of summer maize development, growth, and yield formation. The assimilation approaches are the foundation for application of crop growth model at regional scale.
- constrained analysis;
- assimilation;
- crop growth model;
- observations

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References(39)

Figures and Tables

Fig. 1 Assimilation method of observations with Crop Growth Model based on the analysis of constrained character

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Fig. 2 The changes of Q_T values with parameter values in assimilating LAI to WOFOST under potential production level (CK treatment in 2009)

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Table 1 Main parameters in WOFOST

参数	定义	单位
T_DWI	初始地上部总干物重	kg·hm^-2
S_LA	比叶面积	hm²·kg^-1
S_PAN	叶片衰老系数	d
E_FF	单叶光能利用率	kg·hm^-2·h^-1·J^-1·m²·s
A_max	叶片最大CO₂同化速率	kg·hm^-2·h^-1
R_ML	叶片相对维持呼吸速率	kgCH₂O·kg^-1·d^-1
R_MO	贮存器官相对维持呼吸速率	kgCH₂O·kg^-1·d^-1
R_MS	茎相对维持呼吸速率	kgCH₂O·kg^-1·d^-1
R_DRS	茎相对死亡速率	kg·kg^-1·d^-1
C_FET	蒸散速率订正系数
R_DI	初始根深	cm
R_RI	根深最大日增量	cm·d^-1
W_AV	初始土壤有效水	cm
S_MLIM	初始根深的初始水分含量	cm³·cm^-3

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Table 2 Errors of WOFOST while LAI and TAGP as assimilation data in 2009

同化数据	参变量	统计量	生产水平
同化数据	参变量	统计量	潜在	水分胁迫
LAI	A_max1	绝对误差/(kg·hm^-2·kg^-1)	3	2.5
	A_max1	相对误差/%	6	5
	S_PAN	绝对误差/d	0.1	0.08
	S_PAN	相对误差/%	0.2	0
	S_LA1	绝对误差/(hm²·kg^-1)	0.0001	0
	S_LA1	相对误差/%	3	0
	WSO	绝对误差/(kg·hm^-2)	76	96
	WSO	相对误差/%	0.9	1
	TAGP	绝对误差/(kg·hm^-2)	179	271
	TAGP	相对误差/%	1	2
TAGP	T_DWI	绝对误差/(kg·hm^-2)	2	1.1
	T_DWI	相对误差/%	4	2
	S_LA2	绝对误差/(hm²·kg^-1)	0.0001	0
	S_LA2	相对误差/%	6	0
	S_PAN	绝对误差/d	4	4
	S_PAN	相对误差/%	8	8
	WSO	绝对误差/(kg·hm^-2)	70	62
	WSO	相对误差/%	0.9	1
	TAGP	绝对误差/(kg·hm^-2)	96	100
	TAGP	相对误差/%	0.6	1

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Table 3 Q_T of sensitivity parameters in WOFOST

参数	潜在生产水平 (2009年CK处理)				水分胁迫生产水平 (2009年K2处理)
参数	LAI	WSO/(kg·hm^-2)	TAGP/(kg·hm^-2)	LAI	WSO/(kg·hm^-2)	TAGP/(kg·hm^-2)	SM/%
T_DWI	0.35	1295.89	1142.58	0.31	1542.93	251.96	4.05
S_LA1	0.37	1291.53	980.39	0.29	305.24	269.21	3.89
A_max1	0.37	1293.18	1029.72	0.29	808.56	439.72	4.26
E_FF2	0.41		1075.47	0.34	1088.23	1437.47
S_LA2	0.47	805.91	909.88	0.31	1568.69	1597.23	3.91
A_max2	0.66	1265.34	1008.89	0.34	1009.37	1088.11	4.65
E_FF1	0.96		1075.38	0.79	1426.45	2340.61
S_PAN	1.00	1278.54	980.71	0.64	532.05	1130.70	4.67
R_MO		1019.33	910.88		1476.14
A_max4		1043.29	929.49		1413.26	2690.93
A_max3		1216.73			1336.32	2646.97
S_LA3		1271.46	1056.22		1704.76	2856.13	4.67
A_max5		1117.89	972.11
R_DRS3		1205.73
R_ML		1208.80	960.28
R_RI				0.25	322.81	268.69	4.43
W_AV				0.29	305.41	245.65	4.68
S_MLIM				0.31	313.93	249.74	4.32
R_DI				0.32		1732.18	4.58
C_FET2				0.90	1288.60		4.38
C_FET1				0.56	1474.08	2236.67	4.58

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Table 4 Constrained parameters of different observations in WOFOST under water stress production level (K2 treatment in 2009)

状态变量	可约束参数
LAI	W_AV, A_max1, S_LA1, R_RI, S_MLIM, T_DWI, S_PAN
WSO	W_AV, S_LA1, S_MLIM, S_LA2, S_PAN, R_RI
TAGP	W_AV, S_LA1, R_RI, S_MLIM, T_DWI
SM	W_AV, R_RI, S_MLIM, T_DWI, S_PAN

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Table 5 Optimal values of constrained parameters while assimilation of observations with WOFOST in 2009

项目	潜在生产水平 (CK处理)					水分胁迫生产水平 (K2处理)
项目	LAI	WSO	TAGP			LAI		WSO	SM
可约束参数	T_DWI/(kg·hm^-2)	S_LA1/(hm²·kg^-1)	S_PAN/d	S_LA2/(hm²·kg^-1)	A_MAX1/(kg·hm^-2·h^-1)	R_RI/(cm·d^-1)	S_MLIM/(cm³·cm^-3)	S_LA2/(hm²·kg^-1)	W_AV/cm
参数优化值	22.41	0.0028	49.81	0.0015	74.82	0.74	0.24	0.0011	23.07

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