YAN Li, ZHANG Ji-Quan, WANG Chun-Yi, YAN Deng-Hua, LIU Xing-Peng, TONG Zhi-Jun. Vulnerability evaluation and regionalization of drought disaster risk ofmaize in Northwestern Liaoning Province[J]. Chinese Journal of Eco-Agriculture, 2012, 20(6): 788-794. DOI: 10.3724/SP.J.1011.2012.00788
Citation: YAN Li, ZHANG Ji-Quan, WANG Chun-Yi, YAN Deng-Hua, LIU Xing-Peng, TONG Zhi-Jun. Vulnerability evaluation and regionalization of drought disaster risk ofmaize in Northwestern Liaoning Province[J]. Chinese Journal of Eco-Agriculture, 2012, 20(6): 788-794. DOI: 10.3724/SP.J.1011.2012.00788

Vulnerability evaluation and regionalization of drought disaster risk ofmaize in Northwestern Liaoning Province

  • Based on IPCC definition of vulnerability within the context of climate change, a risk assessment model of maize vulnerability to drought was established from the perspectives of exposure, sensitivity and adaptability. Given drought disaster risk of maize in Northwestern Liaoning Province, 17 indexes related to crop physiological, meteorological and socio-economic factors were selected for the model simulation. The vulnerability indexes of maize to drought were calculated using the entropy and comprehensive weight evaluation methods. Four typical drought years (1999, 2000, 2001 and 2006) in Northeastern Liaoning Province were used to verify and test the applicability of the model. The maize vulnerability indexes to drought were divided into 5 grades on which basis maize vulnerability zone maps were isolated in GIS environment for typical drought years. The results showed that the areas with high drought vulnerability were mainly concentrated around Fuxin, Chaoyang and Huludao Counties. The areas with high vulnerability displayed a temporal regular pattern of 2006 > 1999 > 2001 > 2000. The level of drought vulnerability in 2006 was the highest, and had the most extensive impact area due to the precipitation anomaly in the growing season of that year. Regression analysis of maize vulnerability indexes to drought in the four typical drought years and maize yield loss was also conducted. The analysis showed a basic agreement among the factors for F test of significant at α=0.05. This indicated that it was reasonable to evaluate and predict the maize vulnerability to drought using the established model in the region. The model could be used to evaluate and predict maize vulnerability to drought, drought disaster risk and maize yield loss caused by drought. The results of this study strengthened further basis for local agricultural drought risk assessment and early warning.
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