Journal of Agricultural Big Data >
Parameter Adjustment and Optimization Methods for The WheatSM
Received date: 2021-07-20
Online published: 2021-12-22
The crop growth model is an effective tool to evaluate crop production, resource utilization, and climate change impact. The WheatSM (Wheat Growth and Development Simulation Model) has been applied to crop production optimization and management and has achieved good achievements. However, because of the large number of model parameters, it’s complicated to debug the model parameters. To determine the parameters of the WheatSM model quickly and accurately, it is necessary to simplify the parameter adjustment work of the model and promote its wide application in the field of agricultural meteorology. In this study, on the basis of automatic adjustment methods of crop model parameters at home and abroad, an automatic adjustment coupling system of WheatSM model parameters is constructed based on the PEST (Parameter Estimation) method. The phenology and yield parameters of the WheatSM model were optimized automatically. Shangzhuang, Beijing was selected as a representative site.This study compared the optimization results with the trial-and-error simulation results, andused the automatic optimization method and trial-and-error method to adjust wheat phenology parameters and yield parameters for wheat growth model WheatSM, based on the meteorological data, soil data of the test sites, and the test data of different sowing dates of winter wheat from 2014 to 2016. The results show that the PEST method has high precision and good simulation effect for automatic adjustment and optimization of model parameters. The error of simulated phenology was less than 7 days, and the error of simulated yield was less than 228.63 kg·hm-2. The PEST method has the advantages of being less time consuming and allowing for the simultaneous batch processing of data. Using this automatic parameter adjustment system can reduce the workload of parameter calibration, save model operation time, simplify work complexity, and obtain higher simulation accuracy. This study provides a convenient method for WheatSM parameters automatic optimization and a theoretical reference and guidance for improving the efficiency and accuracy of crop model parameters calibration.
Key words： wheat; PEST; WheatSM model; parameter optimization; phenology; yield; crop growth model
Xiafei Jin, Xianguan Chen, Zhihong Gong, Liping Feng . Parameter Adjustment and Optimization Methods for The WheatSM[J]. Journal of Agricultural Big Data, 2021 , 3(3) : 13 -22 . DOI: 10.19788/j.issn.2096-6369.210302
| 1 | Kundu S. S., Skogerboe G. V., Walker W. R.. Using a crop growth simulation model for evaluating irrigation practices[J]. Agricultural Water Management, 1982(5):253-268. |
| 2 | Kn?rzer H., Gr?zinger H., Graeff-H?nninger S., et al. Integrating a simple shading algorithm into CERES-wheat and CERES-maize with particular regard to a changing microclimate within a relay-intercropping system[J]. Field Crops Research, 2011(121):274-285. |
| 3 | Graves A.R., Hess T., Matthews R.B., et al. Crop simulation models as tools in computer laboratory and classroombased education[J]. Journal of Natural Resources and Life Sciences Education, 2002(31):48-54. |
| 4 | 沈国权. 影响作物发育速度的非线性温度模式[J]. 气象, 1980,6(06):9-11. |
| 4 | Shen G Q. Non-linear Temperature Model that Affects the Growth Rate of Crops [J]. Meteorological,1980,6(06):9-11. |
| 5 | Weir A.H., et al. A winter wheat crop simulation model without water or nutrient limitations[J]. The Journal of Agricultural Science, 1984,102(2):371-382. |
| 6 | 高亮之,金之庆. 水稻计算机模拟模型及其应用之一:水稻钟模型——水稻发育动态的计算机模型[J]. 中国农业气象, 1989,10(03):3-10. |
| 6 | Gao L Z, Jin Z Q. Rice Computer Simulation Model and One of Its Applications: Rice Clock Model-A Computer Model of Rice Development Dynamics [J]. Chinese Agricultural Meteorology, 1989,10(03):3-10. |
| 7 | Jones J.W., Hoogenboom G., Porter C.H., et al. The DSSAT cropping system model[J]. European Journal of Agronomy, 2003, 18(3-4):235-265. |
| 8 | Brown D. M., Chapman L. J.. Soybean ecology: II Development temperature-moisture relationship from field studies[J]. Agronomy Journal, 1960(52):496-499. |
| 9 | 陈先冠, 冯利平, 白慧卿, 等. 基于小麦模型算法集成平台的三种水分胁迫算法比较[J].农业工程学报, 2021, 37(16):47-57. |
| 9 | Chen X G, Feng L P, Bai H Q, et al. Comparison of three water stress algorithms based on the integration platform of wheat model algorithms[J]. Transactions of the Chinese Society of Agricultural Engineering, 2021, 37(16):47-57. |
| 10 | Ritchie J. T., Otter S.. Description and Performance of CERES-Wheat: A User-Oriented Wheat Yield Model[J]. Willis W O, ARS Wheat Yield Project, 1985, US: USDA-ARS, ARS-38. |
| 11 | Keating B. A., Carberry P. S., Hammer G. L., et al. An overview of APSIM, a model designed for farming systems simulation[J]. European Journal of Agronomy, 2003, 18(3-4):267-288. |
| 12 | Allard D W, Hendrik B, Davide F, et al. 25 years of the WOFOST cropping systems model[J]. Agricultural Systems, 2019, 168: 154-167. |
| 13 | 杨妍辰,王建林,宋迎波. WOFOST作物模型机理及使用介绍[J]. 气象科技进展, 2013(5):29-35. |
| 13 | Yang Y C,Wang J L,Song Y B. Introduction to the Mechanism and Use of WOFOST Crop Model[J]. Meteorological science and technology progress, 2013(5):29-35. |
| 14 | 赵诗奎. 基于遗传算法的柔性资源调度优化方法研究[D]. 杭州：浙江大学, 2013. |
| 14 | Zhao S K. Research on Optimization Method of Flexible Resource Scheduling Based on Genetic Algorithm[D]. Hangzhou: Zhejiang University, 2013. |
| 15 | 庄嘉祥,姜海燕,刘蕾蕾,等. 基于个体优势遗传算法的水稻生育期模型参数优化[J]. 中国农业科学, 2013,46(11):2220-2231. |
| 15 | Zhuang J X,Jiang H Y, Liu L L,et al. Parameters Optimization of Rice Development Stages Model Based on Individual Advantages Genetic Algorithm [J]. Scientia Agricultura Sinica, 2013,46(11):2220-2231. |
| 16 | Beven K., Freer J.. Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology[J]. Journal of Hydrology, 2001, 249(1-4):0-29. |
| 17 | 姚宁, 周元刚, 宋利兵, 等. 不同水分胁迫条件下DSSAT-CERES-Wheat模型的调参与验证[J]. 农业工程学报, 2015, 31(012):138-150. |
| 17 | Yao N,Zhou Y G,Song L B,et al. Validation of DSSAT-CERES-Wheat Model Under Different Water Stress Conditions[J]. Journal of Agricultural Engineering, 2015, 31(012):138-150. |
| 18 | Mohamed A.. Multi-objective design approach of passive filters for single-phase distributed energy grid integration systems using particle swarm optimization[J]. Elsevier Ltd, 2020:157-172. |
| 19 | 奚茂龙, 卢丹, 齐志明, 等. 随机漂移粒子群算法的RZWQM替代模型参数优化[J]. 计算机工程与应用, 2016(23) : 35-41. |
| 19 | Xi M L, Lu D, Qi Z M, et al. Optimization of RZWQM Alternative Model Parameters Based on Random Drift Particle Swarm Optimization[J]. Computer Engineering and Applications, 2016(23) : 35-41. |
| 20 | Doherty J.. PEST, Model-Independent Parameter Estimation User Manual: 5th Edition. Brisbane, Australia: Watermark Numerical Computing, 2004. |
| 21 | 梁浩, 胡克林, 李保国. 基于PEST的土壤-作物系统模型参数优化及灵敏度分析[J]. 农业工程学报, 2016(3):78-85. |
| 21 | Liang H, Hu K L, Li B G. Parameter optimization and sensitivity analysis of soil-crop system model based on PEST[J]. Journal of Agricultural Engineering, 2016(3):78-85. |
| 22 | 冯利平, 高亮之, 金之庆, 等. 小麦发育期动态模拟模型的研究[J]. 作物学报, 1997,23(04):418-424. |
| 22 | Feng L P,Gao L Z,Jin Z Q,et al. Study on the Dynamic Simulation Model of Wheat Development Period[J]. Acta Agronomica, 1997,23(04):418-424. |
| 23 | 胡克林, 李保国, 吕贻忠, 等．中国农业大学上庄实验站土壤理化性质的空间分布特征[J]．中国农业大学学报,2006（06）：27-33. |
| 23 | Hu K L,Li B G,Lv Y Z, et al. Spatial Distribution Characteristics of Soil Physical and Chemical Properties in Shangzhuang Experimental Station of China Agricultural University[J]．Journal of China Agricultural University, 2006 (06): 27-33. |
| 24 | 孙美, 张晓琳, 冯绍元, 等. 基于PEST的RZWQM2模型参数优化与验证[J]. 农业机械学报, 2014(11):151-158. |
| 24 | Sun M,Zhang X L,Feng S Y, et al. Optimization and Verification of RZWQM2 Model Parameters Based on PEST[J]. Journal of Agricultural Machinery, 2014(11):151-158. |
| 25 | 王礼恒等. 基于PEST的地下水数值模拟参数优化的应用[J]. 工程勘察, 2014,42(03):38-42. |
| 25 | Wang L H,et al. Application of PEST-based Groundwater Numerical Simulation Parameter Optimization[J]. Engineering Investigation, 2014,42(03):38-42. |
| 26 | 冯利平. 小麦生长发育模拟模型(WHEATSM) 的研究[D]. 南京:南京农业大学, 1995. |
| 26 | Feng L P. Research on Wheat Growth and Development Simulation Model (WHEATSM) [D]. Nanjing: Nanjing Agricultural University, 1995. |
| 27 | 诸叶平, 李世娟, 李书钦. 作物生长过程模拟模型与形态三维可视化关键技术研究[J]. 智慧农业(中英文), 2019, 1(1): 53-66. |
| 27 | Zhu Y P, Li S J, Li S Q. Research on key technologies of crop growth process simulation model and morphological 3D visualization[J]. Smart Agriculture, 2019, 1(1): 53-66. |
| 28 | 高亮之, 金之庆, 黄耀, 等. 农业模型学[M]. 北京：气象出版社, 2019. |
| 28 | Gao L Z,Jin Z Q,Huang Y, et al. Agricultural Modeling[M]. Beijing: Meteorological Press, 2019. |
| 29 | 郭其乐,李颖,田宏伟. 小麦生长发育模型WheatSM参数优化及适用性分析[J]. 麦类作物学报, 2017,37(12):1571-1580. |
| 29 | Guo Q L,Li Y,Tian H W. Parameter Optimization and Applicability Analysis of Wheat Growth and Development Model WheatSM[J]. Journal of Triticeae Crops, 2017,37(12):1571-1580. |
| 30 | 曹宏鑫, 葛道阔, 张文宇, 等. 农业模型发展分析及应用案例[J]. 智慧农业(中英文), 2020, 2(1): 147-162. |
| 30 | Cao H X, Ge D K, Zhang W Y, et al. Developmental analysis and application examples for agricultural models[J]. Smart Agriculture, 2020, 2(1): 147-162. |
| 31 | 张志刚. 基于遗传算法的模糊控制器的优化和研究[D]. 太原理工大学, 2005. |
| 31 | Zhang Z G. Optimization and Research of Fuzzy Controller Based on Genetic Algorithm[D]. Taiyuan University of Technology, 2005. |
/
| 〈 |
|
〉 |
