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小麥模型算法集成平臺構建與算法比較
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國家重點研發(fā)計劃項目(2016YFD0300201、2016YFD0300105),、中國氣象局河南省農業(yè)氣象保障與應用技術重點實驗室開放研究基金項目(AMF201805)和中央高?;究蒲袠I(yè)務費專項資金項目(2021TC117)


Establishment of Wheat Model Algorithms Integration Platform and Algorithm Comparison
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    摘要:

    為方便小麥模型算法比較與多算法集成模擬,本研究參考國內外主流作物模型CERES-Wheat,、APSIM-Wheat,、WheatSM、WOFOST,、SWAT等的主要算法,,集成了發(fā)育期、生物量,、產量形成等模塊的多種算法,,構建了小麥模型算法集成平臺(Wheat model algorithm integration platform, WMAIP)。發(fā)育期模塊集成了小麥鐘模型和熱時兩種算法,;生物量模塊集成了群體光合作用,、光能利用效率和二氧化碳同化率3種算法;產量形成模塊集成了籽粒灌漿,、生物量轉移和收獲指數(shù)3種算法,?;谀P推脚_組成了6個具有代表性的模擬模型。利用河北省吳橋縣2017—2019年兩年播期試驗的田間觀測數(shù)據(jù)結合2011—2014年3年播期耦合水分文獻資料對模型進行參數(shù)校準與驗證,,并對特定模塊的不同算法進行比較,。結果表明,各模型的模擬結果與實測值均吻合良好,,模擬誤差在合理范圍之內,,其中發(fā)育期、地上部生物量,、產量和土壤貯水量模擬值和實測值的歸一化均方根誤差(NRMSE)分別在0.56%~4.00%,、16.13%~18.72%、12.48%~18.95%和10.78%~11.63%之間,,模型集合的模擬效果優(yōu)于單一模型,。通過算法比較發(fā)現(xiàn),發(fā)育期模塊中熱時法模擬播種至拔節(jié)階段較優(yōu),,小麥鐘模型模擬播種至開花階段和播種至成熟階段較優(yōu),;生物量模塊中3種算法均為模擬小麥生物量的較佳模型,但在高輻射條件下,,群體光合作用法模擬的生物量較高,;產量模塊中3種算法模擬的產量變化趨勢較為一致,但生物量轉移法效果略好,。該平臺集成了特定模塊的多種算法,,能較好地模擬土壤貯水量和冬小麥的生物學指標,在小麥模型算法比較與改進,、集成模擬及氣候變化影響評估方面具有較大的應用潛力,。

    Abstract:

    In order to facilitate the comparison of wheat model algorithms and multi-algorithm integrated simulation, a wheat model algorithm integration platform (WMAIP) was established by referring to the main module algorithms of domestic and foreign mainstream crop models (CERES-Wheat, APSIM-Wheat, WheatSM, WOFOST, SWAT, etc.). The method for simulation phenology integrated two algorithms with “wheat clock” model method and thermal time method based on WheatSM and APSIM-Wheat phenology module, respectively. The method for simulation biomass integrated three algorithms with carbon assimilation (CA), canopy photosynthesis (CP) and radiation use efficiency (RUE) based on WOFOST, APSIM-Wheat and WheatSM biomass modules, respectively. The method for simulation yield formation integrated three algorithms with harvest index (HI), grain filling (GF) and biomass remobilization (BR) based on SWAT, APSIM-Wheat and WheatSM grain yield modules, respectively. Six representative simulation models were constructed based on the model platform. The parameters of model were calibrated and verified by using field observation data of sowing date experiment from 2017 to 2019 in Wuqiao, Hebei Province and literature data of sowing date coupling irrigation experiment from 2011 to 2014. Finally, different algorithms for specific modules were compared. The results showed that simulated values of different algorithms in each module could be used to represent measured values with a reasonable error range. Therefore, the NRMSE values of phenology, above ground biomass, yield and soil water storage were ranged from 0.56% to 4.00%, from 16.13% to 18.72%, from 12.48% to 18.95% and from 10.78% to 11.63%, respectively. The effect simulated by multi-model platform was better than that of the single model. In the phenology module, the simulation of duration from sowing to jointing by thermal time method was better, while the simulation of durations from sowing to anthesis and from sowing to maturity were poorer than that by “wheat clock” model method. In the biomass module, the three algorithms were the best models to predict the biomass of wheat, but the simulated biomass of CP method was higher under high radiation conditions. In the yield formation module, the variation trend of yield simulated by the three algorithms was consistent, but the simulation results by BR method was rather better than that by others. In general, the WMAIP platform integrated multiple algorithms for specific modules to simulate soil water storage and biological indicators of winter wheat well. The application potential of this platform was great in comparison and improvement of wheat model algorithms, integrated simulation and assessment of climate change impacts.

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陳先冠,馮利平,白慧卿,王春雷,王靖,余衛(wèi)東.小麥模型算法集成平臺構建與算法比較[J].農業(yè)機械學報,2022,53(6):237-249. CHEN Xianguan, FENG Liping, BAI Huiqing, WANG Chunlei, WANG Jing, YU Weidong. Establishment of Wheat Model Algorithms Integration Platform and Algorithm Comparison[J]. Transactions of the Chinese Society for Agricultural Machinery,2022,53(6):237-249.

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  • 收稿日期:2021-01-30
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  • 在線發(fā)布日期: 2021-03-12
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