Abstract:

Accurate crop growth monitoring and yield forecasting are significant to food security and sustainable development of agriculture. However, Regional crop growth simulation under water stress faces the difficulties in determining the spatial distribution of some model parameters and initial conditions, such as initial available soil water and irrigation. It appears to be a big potential in this field to couple remote sensing data with crop model. In this paper, we proposed a way of combining evapotranspiration derived from satellite remote sensing data with crop grow simulation model (WOFOST) under water stress. Some modifications of WOFOST model were performed with field experimental data to make it applicable in North China Plain. The combination method was first applied to simulate the growth, development and yield formation processes for winter wheat at two sites, Tai’an and Zhengzhou, during the growing season from 2001 to 2002. According to the results of sensitivity analysis, the initial available soil water was chosen to be recalibrated by observed evapotranspiration derived from MODIS data based on SEBS model (Surface Energy Balance System). Also the biomass at reviving and irrigation at heading stage were selected to re-estimated by observed SAVI and evapotranspiration, considering over-winter process and the importance of irrigation on winter wheat yield formation in North China. The difference between observed and simulated evapotranspiration/SAVI was minimized by re-initializing/re-parameterizing three chosen initial conditions/parameters with an optimization program (FSEOPT). The estimated values of initial available soil water and irrigation showed good agreement with observations at the two sites. And the relative errors of simulated dry matter weight of gross above-ground and storage organ were reduced also. On the basis of the regionalization of weather data, model parameters, and initial conditions, we used this method to estimate winter wheat yields in North China during the growing season from 2001 to 2002 at the scale of 0.25 degrees, especially for Henan, Hebei, and Shandong provinces. It was showed that both soil water estimates and final winter wheat production estimates were consistent with ground measurements since the initial available soil water, biomass at reviving and irrigation at heading stage were recalibrated by remote sensing data. The relative root mean square error (RRMSE) decreased from 0.63 to 0.20 for the yield from 32 experimental sites, which distribute uniformly in North China Plain. Also the aggregated yields for three provinces were improved, with relative errors －4.9%, 4.5%, and 8.6%, respectively. These results illustrated that the evapotranspiration derived from MODIS data could be used to improve the winter wheat yield estimate under water stress on a regional scale. Further study should focus on better understanding of processes, error accumulation, and improvement on validation of both evaportranspiration derived from MODIS data and simulated yields for winter wheat.

Key words: Crop growth simulation model, Remote sensing data, Winter wheat in North China: Water stress