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基于區(qū)域畦灌模擬模型的參數(shù)隨機(jī)模擬方法比較
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國(guó)家高技術(shù)研究發(fā)展計(jì)劃（863計(jì)劃）項(xiàng)目（2013AA102904、2011AA100505）,、國(guó)家自然科學(xué)基金項(xiàng)目（51609237）、中科院“西部之光”項(xiàng)目（XAB2015B04）和中央高?；究蒲袠I(yè)務(wù)費(fèi)專(zhuān)項(xiàng)資金項(xiàng)目（2452016104）


Comparison of Stochastic Parameter Simulation Methods Based on Regional Scale Border Irrigation Numerical Model
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    摘要:

    針對(duì)區(qū)域畦灌隨機(jī)模擬模型中直接蒙特卡洛模擬方法存在的抽樣重復(fù)性及收斂性較差等問(wèn)題,，借助僅考慮土壤特性空間隨機(jī)性的區(qū)域畦灌隨機(jī)模擬模型，研究拉丁超立方模擬,、修正拉丁超立方模擬與直接蒙特卡羅模擬在抽樣精確性,、區(qū)域畦灌模擬計(jì)算收斂性、準(zhǔn)確性,、穩(wěn)定性和計(jì)算效率等方面的差異,。結(jié)果表明：修正拉丁超立方模擬和拉丁超立方模擬能夠很好地表征土壤干容重的區(qū)域分布特征，抽樣精確性較高,。修正拉丁超立方模擬收斂速度最快,，能夠顯著改善抽樣質(zhì)量，模擬準(zhǔn)確性與分布形態(tài)優(yōu)于拉丁超立方模擬與直接蒙特卡洛模擬,。修正拉丁超立方模擬具有比拉丁超立方模擬與直接蒙特卡洛模擬更好的穩(wěn)定性,。基于修正拉丁超立方的區(qū)域畦灌隨機(jī)模擬模型計(jì)算效率比拉丁超立方抽樣和直接蒙特卡洛模擬分別提高0.23倍和1.80倍,，說(shuō)明修正拉丁超立方模擬能夠解決原有模擬方法計(jì)算效率較低的問(wèn)題,，有助于縮短計(jì)算時(shí)間，降低計(jì)算成本,。

    Abstract:

    The uncertainty of border irrigation parameters will directly affect the simulation results of border irrigation flow model for surface irrigation management at regional scale. Latin hypercube sampling (LHS), updated Latin hypercube sampling (ULHS) and simple Monte Carlo sampling (SMCS) are studied in sampling convergence, stability and simulation efficiency based on regional scale border irrigation simulation method and soil properties spatial randomness. In terms of the sampling accuracy, ULHS and LHS can satisfactorily represent the statistical characteristics of soil bulk density. In the simulation convergence aspect, ULHS has the faster convergence than LHS and SMCS, which indicates that ULHS can significantly improve the sampling quality and reduce the sampling frequency. In the simulation accuracy, simulation times of ULHS are less than those of LHS and SMCS, simulation accuracy and distribution pattern are better than those of LHS and SMCS. Stability simulation of ULHS is better than those of LHS and SMCS. Computational efficiency of ULHS is increased by 0.23-fold and 1.8-fold than those of LHS and SMCS, respectively. Convergence rate of ULHS is faster than those of LHS and SMCS. In addition,，ULHS can improve computational efficiency and sampling stability. ULHS can help to improve the simulation performance of regional scale border irrigation stochastic simulation model.

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董勤各,許迪,李益農(nóng),章少輝,白美健.基于區(qū)域畦灌模擬模型的參數(shù)隨機(jī)模擬方法比較[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2016,47(12):130-138，91. Dong Qin’ge, Xu Di, Li Yinong, Zhang Shaohui, Bai Meijian. Comparison of Stochastic Parameter Simulation Methods Based on Regional Scale Border Irrigation Numerical Model[J]. Transactions of the Chinese Society for Agricultural Machinery,2016,47(12):130-138,，91.

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  • 收稿日期:2016-07-08
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  • 在線(xiàn)發(fā)布日期: 2016-12-10
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