Assessing Maize Drought Hazard for Agricultural Areas Based on the Fuzzy Gamma Model  

作　　者：LIU Xing-peng ZHANG Ji-quan CAI Wei-ying TONG Zhi-jun 

机构地区：[1]Natural Disaster Research Institute, College of Urban and Environmental Sciences, Northeast Normal University [2]Key Laboratory for Vegetation Ecology, Ministry of Education/Northeast Normal University [3]College of Tourism, Changchun University

出　　处：《Journal of Integrative Agriculture》2013年第3期532-540,共9页农业科学学报（英文版）

基　　金：supported by the National High-Tech R&D Program of China (2011BAD32B00-04);the National Basic Research Program of China (2010CB951102);the National Natural Science Foundation of China (41071326);the National Scientific Research Special Project of Public Sectors (Agriculture) of China (200903041)

摘　　要：Drought is one of the severe meteorological disasters and causes of serious losses for agricultural productions, and early assessment of drought hazard degree is critical in management of maize farming. This study proposes a novel method for assessment of maize drought hazard in different growth stages. First, the study divided the maize growth period into four critical growth stages, including seeding, elongation, tasseling, and filling. Second, maize drought causal factors were selected and the fuzzy membership function was established. Finally, the study built a fuzzy gamma model to assess maize drought hazards, and the gamma 0.93 was finally established using Monte Carlo Analysis. Performing fuzzy gamma operation with 0.93 for gamma and classifying the area yielded a map of maize drought hazards with four zones of light, moderate, severe, and extreme droughts. Using actual field collected data, seven selected samples for drought hazard degree were examined, the model output proved to be a valid tool in the assessment maize drought hazard. This model will be very useful in analyzing the spatial change of maize drought hazard and influence on yield, which is significant for drought management in major agricultural areas.Drought is one of the severe meteorological disasters and causes of serious losses for agricultural productions, and early assessment of drought hazard degree is critical in management of maize farming. This study proposes a novel method for assessment of maize drought hazard in different growth stages. First, the study divided the maize growth period into four critical growth stages, including seeding, elongation, tasseling, and filling. Second, maize drought causal factors were selected and the fuzzy membership function was established. Finally, the study built a fuzzy gamma model to assess maize drought hazards, and the gamma 0.93 was finally established using Monte Carlo Analysis. Performing fuzzy gamma operation with 0.93 for gamma and classifying the area yielded a map of maize drought hazards with four zones of light, moderate, severe, and extreme droughts. Using actual field collected data, seven selected samples for drought hazard degree were examined, the model output proved to be a valid tool in the assessment maize drought hazard. This model will be very useful in analyzing the spatial change of maize drought hazard and influence on yield, which is significant for drought management in major agricultural areas.

关 键 词：maize growth period fuzzy gamma modeling drought hazard 

分 类 号：S513[农业科学—作物学] TP18[自动化与计算机技术—控制理论与控制工程]