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稻田土壤-作物系統(tǒng)模型參數(shù)敏感性分析與模型驗(yàn)證
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國(guó)家重點(diǎn)研發(fā)計(jì)劃項(xiàng)目(2016YFD0201202)和中國(guó)博士后科學(xué)基金項(xiàng)目(2019T120159)


Sensitivity Analysis and Parameter Estimation for Soil-Rice System Model
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    摘要:

    為提高稻田土壤-作物模型校準(zhǔn)過(guò)程的效率和精度,以長(zhǎng)江中游地區(qū)兩年的稻田試驗(yàn)數(shù)據(jù)為基礎(chǔ),采用Morris和Sobol’兩種方法對(duì)WHCNS_Rice模型參數(shù)進(jìn)行了全局敏感性分析,并在此基礎(chǔ)上進(jìn)行模型校準(zhǔn)和驗(yàn)證。結(jié)果表明,兩種方法得到的模型主要敏感性參數(shù)基本一致,與Sobol’方法相比,Morris方法具有計(jì)算量小和篩選快速的優(yōu)勢(shì)。土壤水力學(xué)參數(shù)和作物參數(shù)對(duì)模型輸出項(xiàng)均有較大的影響,尤其是土壤水力學(xué)參數(shù)中的飽和含水率、田間持水率以及犁底層飽和導(dǎo)水率;作物參數(shù)中生育期總有效積溫、最大比葉面積和作物系數(shù)對(duì)作物生長(zhǎng)過(guò)程影響較大;氮素轉(zhuǎn)化參數(shù)中僅氨揮發(fā)一階動(dòng)力學(xué)系數(shù)和反硝化經(jīng)驗(yàn)系數(shù)分別對(duì)氨揮發(fā)和氮反硝化有一定的影響,其余參數(shù)均不敏感。在此基礎(chǔ)上,固定非敏感參數(shù),重點(diǎn)校準(zhǔn)上述敏感參數(shù)。模型校驗(yàn)結(jié)果表明,模型模擬的地上部干物質(zhì)質(zhì)量、作物吸氮量、蒸散量和田面水高度均與實(shí)測(cè)值吻合較好,模擬值與實(shí)測(cè)值線性回歸方程的斜率和相關(guān)系數(shù)均接近于1,P小于0.01,說(shuō)明校驗(yàn)后的模型可用于模擬該地區(qū)的水稻生長(zhǎng)過(guò)程及稻田水分動(dòng)態(tài)和氮素去向。采用Morris方法對(duì)篩選出的模型敏感性參數(shù)進(jìn)行模型校準(zhǔn)和驗(yàn)證,可以大大提高模型校驗(yàn)的效率和精度。本研究可為稻田土壤-作物系統(tǒng)WHCNS_Rice模型參數(shù)的校準(zhǔn)和模型的推廣應(yīng)用提供技術(shù)支持。

    Abstract:

    The nitrogen (N) transport and transformation processes in rice field is more complex than that in dry land. Process-based soil-rice system model requires many input parameters and it is difficult to calibrate, which severely restricts the model application in rice production region. To improve the calibration efficiency and reduce uncertainty in simulations, both Morris and Sobol’ methods were used to analyze the global sensitivities of input parameters (soil hydraulic, crop, and N transformation parameters) of the WHCNS_Rice model and guide model calibration. Two years of rice field experiments were conducted in the middle reaches of the Yangtze River. Ponding water depth, evapotranspiration (ET), dry matter weight and crop N uptake were all collected and used to evaluate the model. Results showed that the selected sensitive parameters were almost consistent for two methods, but the Morris method could quickly and effectively screen out sensitive parameters with small calculation workload, which is an effective global sensitivity analysis method for the WHCNS_Rice model. Among all model input parameters, the soil hydraulic parameters and crop parameters had the greatest influence on the output variables of crop growth, water and N fates compared with N transformation parameters. Within the soil hydraulic parameters, saturated moisture, field capacity and saturated hydraulic conductivity of the plowpan were the most sensitive parameters. For crop parameters, LAI, yield, dry matter weight, crop N uptake and ET were sensitive to total accumulated temperature, maximum specific leaf area and crop coefficient in different periods. Among the N turnover parameters, only the first order kinetic constant for volatilization and the denitrification empirical coefficient had some effects on ammonia volatilization and denitrification processes, respectively. Based on the results of sensitivity analysis, the sensitive parameters were calibrated to minimize error between simulated and observed measurements. The results showed that the simulated dry matter weight, crop N uptake, ET and ponding water depth were in good agreement with the measured values. Both the slopes of the linear regression equation and correlation coefficients between the simulated and measured values were close to 1 (P<0.01), indicating that the model could be used to simulate soil water movement, soil N fates, and rice growth for paddy soil in the region. These results suggested that sensitivity analysis based on the Morris method can significantly improve the model calibration efficiency and reduce uncertainty in simulation, which provided technical support for parameter calibration and application of the process-based WHCNS_Rice model.

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史鑫蕊,梁浩,周豐,胡克林.稻田土壤-作物系統(tǒng)模型參數(shù)敏感性分析與模型驗(yàn)證[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2020,51(5):252-262,271. SHI Xinrui, LIANG Hao, ZHOU Feng, HU Kelin. Sensitivity Analysis and Parameter Estimation for Soil-Rice System Model[J]. Transactions of the Chinese Society for Agricultural Machinery,2020,51(5):252-262,271.

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  • 收稿日期:2019-09-03
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  • 在線發(fā)布日期: 2020-05-10
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