Research Of Operational Application With Crop Model In Meteorological Service To Winter Wheat Production In North China

With the development of computer technology and research on physiological process of crops growth, the crop models which can show the whole process of crop growth and development dynamically has become one of the powerful tools for crop researching. This has positive significance to promote crop condition monitoring, yield prediction and the healthy and stable development of agriculture. Although exploratory application of crop models have been used in the daily work, the huge amount of input parameters required by the model along with the complicated model parameters calibration, limited the development of crop models in the business work.This research calibrated the parameter of the crop model WOFOST based on the characteristics of China’s winter wheat using the conventional observation data. A climate suitability algorithm for each growth stage and whole growing period was established on the crop model; final yield and water use efficient was simulated under different irrigation project, these results provide significant guidance to quantitative irrigation in Huabei district; crop model was combined with the numerical weather system to simulate the crop growth in forecast period. We discussed the application of crop model in North China on behalf of the site to explore and analyze the application prospect of the business use. The main conclusions are as follows:(1) Calibrated the genetic parameter using daily meteorological and agro meteorological data, and adjust the low temperature threshold to set it as the indicator beginning and end of the winter period to overcome the simulation’s difficulty on winter period. Winter wheat growth model was developed to fit Tangshan, Zhengzhou and Shangqiu. Then extent the parameter in district scale, we found that the distribution of growth related parameter is close to latitude:the low temperature threshold(average-2℃), decreased with the latitude, accumulated temperature between sowing to emergence(average120℃d) has the same distribution.(2) Climate suitability algorithm based on the value during simulation was established to integer the external effect and crop growth mechanism; this can avoid the defect of independence in statistical algorithms. Descript the effects of crop growth under environmental change quantitatively is more realistic. (3) With the analysis of result simulated under different growing season and irrigation schemes, we found that when other situation keep same, yield is low in tiny precipitation year; irrigation in heading period can ensure the stable yield. Among the irrigation schemes which irrigated more than once, heading period irrigation corresponding to a higher yield, so other watering time should be arranged in low rainfall period to meet the crop demand. Excessive irrigation do no good to increase the yield, can also reduce the water use efficient, affect the respiration of root zone, leading to a low outcome.(4) Combine the crop model and Numerical Weather Prediction to simulate the growth in forecasting period. Although there is some difference between the forecasted parameter and measured data, due to the internal mechanism of crop model, the difference between simulated and measured data is not that much; compared with the fitness of the forecasted period, it is possible to combine these two models.We discussed the climate fitness, best irrigation project and combination of crop model and Numerical Weather Prediction after calibrated the crop model, proved that is possible to use crop model in daily business work. Because of the limitation of data and time, there are still some works to deal with such use crop model in large area and diminish the error after long time simulation.