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

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.