Rezaul Mahmood 0000-0002-1849-7970
Date of this Version
Published in Ecological Modelling 106:2-3 (March 1998), pp 201–212.
Potential increase in air temperature due to climatic change and inter-annual climatic variability and its impacts on crop productivity is of major concern to crop scientists. A number of physically-based models have been developed and applied to estimate crop–environment relationships. In the present study the performance of two such models (the YIELD and the CERES-Rice) are discussed. These two models are used to estimate boro rice productivity under normal and abnormal climate scenarios in Bangladesh. This study finds that boro rice productivity at Mymensingh predicted by the YIELD is higher than the prediction by the CERES-Rice. Productivity estimates for Barisal by these two models are almost identical. Assumptions of non-identical management practices, different soil characterization procedures, different methods for calculation of dry matter production by these two models and the range of diurnal temperature variations played an important role in productivity estimates. The YIELD model predicted the lengths of the growing season under the normal and abnormal thermal climate conditions and they are to be shorter than the lengths predicted by the CERES-Rice model. The YIELD model’s assumption of higher threshold temperature and a relatively simple relationship between phenology and air temperature has produced such estimations (shorter growing season). The complex data required by CERES-Rice may be an impediment for its extensive use. If input data for the CERES-Rice is not available, the YIELD model can be considered as a possible tool for various applications in crop–environment relationships.