Assimilation of Field Measured LAI into Crop Growth Model based on SCE-UA Optimization Algorithm.
ABSTRACT Assimilating external data into a crop growth model to improve accuracy of crop growth monitoring and yield estimation has been a research focus in recent years. In this paper, the shuffled complex evolution (SCE-UA) global optimization algorithm was used to assimilate field measured LAI into EPIC model to simulate yield, sowing date and nitrogen fertilizer application amount of summer maize in Huanghuaihai Plain in China. The results showed that RMSE between simulated yield and field measured yield of summer maize was 0.84 t ha-1 and the R2 was only 0.033 without external data assimilation. While the performances of EPIC model of simulating yield, sowing date and nitrogen fertilizer application amount of summer maize was better through assimilating field measured LAI into the EPIC model. The RMSE of between simulated yield and field measured yield of summer maize was 0.60 t ha-1 and the R2 was 0.5301. The relative error between simulated sowing date and real sowing date of summer maize was 2.28%. On the simulation of nitrogen fertilizer application rate, the relative error was -6.00% compared with local statistical data. These above accuracy could meet the need of crop growth monitoring and yield estimation at regional scale. It proved that assimilating field measured LAI into crop growth model based on SCE-UA optimization algorithm to monitor crop growth and estimate crop yield was feasible.
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ABSTRACT: Surface solar radiation is an important parameter in hydrological models and crop yield models. This study developed a model to estimate solar radiation from sunshine duration. The model is more accurate and more general than traditional Å ngström–Prescott models. It can explicitly account for radiative extinction processes in the atmosphere. Moreover, global data sets that describe the spatial and temporal distribution of ozone thickness and Å ngström turbidity were introduced in the model to enhance its universal reliability and applicability. The model was calibrated in lowland and humid sites and validated at a number of sites in various climate and elevation regions. The new model shows overall better performances than three Å ngström–Prescott models. Because this model follows the simple form of the Å ngström–Prescott model, and its inputs (sunshine duration, air temperature, and relative humidity) are accessible from routine surface meteorological observations, it can be easily applied to hydrological and agricultural studies. The source code and the auxiliary data of the model are available from the authors upon request.Agricultural and Forest Meteorology 03/2006; 137:43-55. · 3.42 Impact Factor
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ABSTRACT: The degree of difficulty in solving a global optimization problem is in general dependent on the dimensionality of the problem and certain characteristics of the objective function. This paper discusses five of these characteristics and presents a strategy for function optimization called the shuffled complex evolution (SCE) method, which promises to be robust, effective, and efficient for a broad class of problems. The SCE method is based on a synthesis of four concepts that have proved successful for global optimization: (a) combination of probabilistic and deterministic approaches; (b) clustering; (c) systematic evolution of a complex of points spanning the space, in the direction of global improvement; and (d) competitive evolution. Two algorithms based on the SCE method are presented. These algorithms are tested by running 100 randomly initiated trials on eight test problems of differing difficulty. The performance of the two algorithms is compared to that of the controlled random search CRS2 method presented by Price (1983, 1987) and to a multistart algorithm based on the simplex method presented by Nelder and Mead (1965).Journal of Optimization Theory and Applications 01/1993; 76(3):501-521. · 1.42 Impact Factor
- edited by Richard G. Allen, Luis S. Pereira, Dirk Raes, Martin Smith, 01/1998; FAO, Rome.