Uncertainty Analysis Of The Input Variables Based On Wheat Growth Model

Crop growth model is an imperfect approximation of the interaction between biotic and abiotic factors in the real world.In some cases,the uncertainty of the structure,input and parameter selection of the model may exceed the spatiotemporal variability of the simulated yield,thus limiting the model’s predictability.Uncertainty analysis is an important part of model-based risk analysis and decision making.It can provide risk assessors and decision makers with the accuracy information of the model output.There are three sources of uncertainty in the crop growth model,namely,input variables,parameter values and model equations.Among these,the uncertainty of the model input variable is mainly due to the error of the input data,such as climate,soil and other relative actual values,which is often caused by measurement error or data loss.In the crop growth model application,the uncertainty of models caused by the input variables is often greater than the uncertainty caused by the internal parameters or equations.Therefore,analyzing the input variables of crop growth simulation model on the uncertainty of the model simulation results can provide the risk analysis and decision support for the model users,and provide a theoretical basis for improving the accuracy of the model output.In this study,the uncertainty of simulation results caused by soil and meteorological input variables in APSIM,CERES,Nwheat and WheatGrow crop models were analyzed based on the different soil and climate scenarios.The results are as follows:(1)For the APSIM,CERES and Nwheat models,the coefficient of the yield simulation results under S1.1.1.1,S1.2.2.2,S1.2.3.3 soil scenarios and the actual soil scenarios(S1.2.3.4)is small,which indicates that the deeper soil data can be instead with the upper soil data when the soil data in deeper layers was absence.For the WheatGrow model,the accuracy of the simulation results is highly correlated with the depth of the soil,so detailed soil data should be obtained when using this model.In addition,by comparing the uncertainty of different soil characteristic parameters on the model simulation results,it is found that soil moisture parameters such as soil wilting point,field water holding capacity and saturated water content have great influence on the uncertainty of simulation results,while other soil property parameters have less impact on the uncertainty of the simulation results.Moreover,the study also found that meteorological scenarios have little effect on the uncertainty of model simulation results caused by soil layers and soil parameters,indicating that the study of soil input parameters in the model can basically ignore the impact of climate.(2)Under the low greenhouse gas emission scenario,the uncertainty of the yield simulation results of the four wheat growth models is small,while the uncertainty of the yield simulation results under the high greenhouse gas emission scenario is large.The effect of different warming time on the uncertainty of the simulation results in the same day is as follows:nighttime warming>daytime warming>all day warming.In addition,the uncertainty of the simulation results varies with the model and the study area.Among them,the precipitation has the greatest impact on the uncertainty of the model results in the Northern Subregion.In the Huang-Huai Subregion and the Middle-Lower Reaches of Yangzi River Subregion,the precipitation and temperature have the great effect on the uncertainty,and in the Southwest Subregion the radiation is the main uncertainty factor.Moreover,for APSIM and Nwheat model,temperature is the most important factor affecting the uncertainty of simulation results,precipitation is the main factor affecting the uncertainty of simulation results of CERES model,and radiation and temperature are the most important factors that affects the uncertainty of simulation results of WheatGrow model.(3)In general,both meteorological models and crop growth simulation models can lead to the uncertainty of simulation results,and the uncertainty caused by the crop growth model is greater than the uncertainty caused by the meteorological model.In addition,by comparing the effects of soiland meteorological input parameters on the simulation uncertaintyof the four wheat growth models,it is found that:soil moisture parameters>meteorological factors>soil layers>climate models.It is suggested that more attention should be paid to the selection of suitable growth simulation models and the accuracy of soil moisture data and meteorological data when applying the crop simiulation models to assess the crop productivity.