不同气候区和不同产量水平下APSIM-Wheat模型的参数全局敏感性分析

Global sensitivity analysis of APSIM-Wheat parameters in different climate zones and yield levels

量化作物模型的参数敏感性和模拟结果的不确定性对模型的标定和应用具有重要意义。为了探讨小麦生长模型(APSIM-Wheat)在不同气候区和不同产量水平下参数的敏感性,以及由于参数造成模拟结果的不确定性,以华北栾城、黄土高原长武、四川盐亭和新疆乌兰乌苏4个不同气候区下的典型冬小麦生产地为分析对象,运用扩展傅里叶幅度检验法(extended Fourier amplitude sensitivity test,EFAST)的全局敏感性分析方法,量化了小麦生长模型(APSIM-Wheat模型)在3种产量水平下(潜在、雨养和实际产量)的开花期、成熟期、产量、生育期的蒸散(evapotranspiration,ET)对品种、土壤和生化等33个参数的敏感性和不确定性。发现:1影响开花期和成熟期较为敏感的参数依次是:始花期积温、出苗到拔节积温、春化指数、光周期因子、灌浆期积温;2影响产量较敏感的参数依次为:春化指数、出苗到拔节积温、每茎谷粒质量、潜在灌浆速率、光周期指数、最大谷粒质量和辐射利用效率(radiation use efficiency,RUE);影响生育期蒸散较为敏感的参数依次为:春化指数、出苗到拔节积温、光周期指数、始花期积温;3不同产量水平下,参数敏感性差异不大,4个不同气候类型下的冬小麦开花期、成熟期、产量和生育期的蒸散对参数的敏感性基本一致;4不同气候区下,开花期和成熟期对模型参数敏感性差异很小,但产量和生育期的蒸散对参数敏感性有差异。该研究为APSIM-Wheat模型的区域应用和模型调参提供了科学指导依据。

Uncertainties of crop model are mainly from model structure, parameters＆#39; sensitivity and input error. It is essential to quantify the parameters＆#39; sensitivity and the results＆#39; uncertainties of crop model for model calibration and application. Furthermore, uncertainty and sensitivity analysis can improve the reliability of model prediction. There are 2 categories of parameter sensitivity analysis methods, i.e. the local sensitivity and the global sensitivity. Local sensitivity analysis is called derivative-based or one-at-a-time method, which changes only one parameter at a time around a basis point while keeping other parameters constant. It cannot detect the interactions among the parameters and suffers some shortcomings such as a heavy dependence on the input parameters and instability for non-linear models. Global sensitivity analysis is a better method for exploring the entire multi-dimensional parameters simultaneously. It can quantify the influence of single parameter and the interactions among different parameters. Several global sensitivity methods including Morris, variance-based, linear regression, FAST （Fourier amplitude sensitivity test） and EFAST （extended Fourier amplitude sensitivity test） are widely used in the parameter analysis. EFAST is robust and has lower computational cost than the others. Previous studies of sensitivity analysis focused on a single site. However, the performance of crop model is variable in different climatic zones due to the heterogeneity of climate and soil characteristics. In this study, we collected crop experimental data in the locations of Luancheng, Hebei Province Changwu in the Chinese Loess Plateau, Yanting in the Sichuan Basin and Wulanwusu in Xinjiang Autonomous Region. And then using the global sensitivity analysis method i.e. EFAST, we analyzed the sensitivity and uncertainty of crop model （APSIM-Wheat） brought by the cultivar, soil and biological parameters in different climate zones and yield levels （i.e. potential, rainfed and actual yield）. We found that： 1） The most sensitive parameters for anthesis and maturity date were successively： accumulated temperature in the early flowering season, accumulated temperature from emergence to jointing, vernalization index, photoperiod factor, and accumulated temperature in grain filling stage; 2） The most sensitive parameters for yield were successively： vernalization index, accumulated temperature from emergence to jointing, grain mass per stem at the beginning of grain filling, potential daily grain filling rate, photoperiod factor, maximum grain mass and radiation use efficiency; the most sensitive parameters for evapotranspiration （ET） were successively： vernalization index, accumulated temperature from emergence to jointing, photoperiod factor and accumulated temperature in the early flowering season; 3） The parameter sensitivity for anthesis, maturity, yield and ET in different yield levels was almost coincident, which indicated that the simulation of APSIM-Wheat was not influenced by different yield levels; 4） The parameter sensitivity for anthesis and maturity in different climatic zones was almost the same, while that for yield and ET was different. The sensitivity difference in different climatic zones for yield and ET warns the model users to use the model carefully in different locations. The results indicate that we should calibrate the more sensitive parameters for phenology and then calibrate the yield and ET during the APSIM-Wheat calibration.