Document Type : Research Paper
Authors
1
Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, P. R. China; Graduate School of the Chinese Academy of Sciences, Beijing 100039, P.R. China
2
Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, P. R. China
3
CSIRO Land and Water, Canberra ACT 2601, Australia
4
Plant Research International, Wageningen University and Research Center, 6700 AA Wageningen, Netherlands
Abstract
Summer maize (Zea mays L.) is one of the dominant crops in the North China Plain (NCP). Its growth is greatly influenced by the spatial-temporal variation of climatic variables, especially solar radiation, temperature and rainfall. The WOFOST (version 7.1) model was applied to evaluate the impact of climatic variability on summer maize yields using historical meteorological data from 1961 to 2000. The model was calibrated and validated using data from field experiments conducted during the period 1998-1999 and simulations were run to analyses the climate impact. Simulated potential yield ranges from 7.7 to 10.0 Mg ha-1, with an increasing trend from south to north, while rainfed yield ranges from 4.3 to 8.1 Mg ha-1, and with an increasing trend from the middle to the north and south of NCP. Gaps between potential and rainfed yields also decreased from the middle to the north and south. The pattern of potential yield was mainly attributed to the distribution of solar radiation and temperature, whereas rainfed yield was mainly influenced by the distribution of rainfall. Interannual variability n of potential yield is small, and was closely related to the variation of solar radiation, while rainfed yield varied greatly, especially in the middle of the plain, where the rainfall is lowest. Combined with consistent research results of winter wheat, results of this study offer scientific basis for policy makers and researchers concerned with the management of food marketing decisions and water resource reallocation.
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