Title
The Estimation of Regional Crop Yield Using Ensemble-Based Four-Dimensional Variational Data Assimilation
Abstract
To improve crop model performance for regional crop yield estimates, a new four-dimensional variational algorithm (POD4DVar) merging the Monte Carlo and proper orthogonal decomposition techniques was introduced to develop a data assimilation strategy using the Crop Environment Resource Synthesis (CERES)-Wheat model. Two winter wheat yield estimation procedures were conducted on a field plot and regional scale to test the feasibility and potential of the POD4DVar-based strategy. Winter wheat yield forecasts for the field plots showed a coefficient of determination (R-2) of 0.73, a root mean square error (RMSE) of 319 kg/ha, and a relative error (RE) of 3.49%. An acceptable yield at the regional scale was estimated with an R-2 of 0.997, RMSE of 7346 tons, and RE of 3.81%. The POD4DVar-based strategy was more accurate and efficient than the EnKF-based strategy. In addition to crop yield, other critical crop variables such as the biomass, harvest index, evapotranspiration, and soil organic carbon may also be estimated. The present study thus introduces a promising approach for operationally monitoring regional crop growth and predicting yield. Successful application of this assimilation model at regional scales must focus on uncertainties derived from the crop model, model inputs, data assimilation algorithm, and assimilated observations.
Year
DOI
Venue
2014
10.3390/rs6042664
REMOTE SENSING
Keywords
Field
DocType
four-dimensional variation,crop model,data assimilation,yield estimation,leaf area index,remote sensing
Leaf area index,Monte Carlo method,Crop yield,Hydrology,Remote sensing,Mean squared error,Coefficient of determination,Data assimilation,Statistics,Geology,Evapotranspiration,Approximation error
Journal
Volume
Issue
ISSN
6
4
2072-4292
Citations 
PageRank 
References 
3
0.44
3
Authors
6
Name
Order
Citations
PageRank
Zhiwei Jiang1416.41
Zhongxin Chen26718.05
Jin Chen325931.87
Jianqiang Ren4499.27
zongnan li5111.33
liang sun6255.83