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

doi:10.1016/S2095-3119(13)60254-3

Journal of Integrative Agriculture ›› 2013, Vol. 12 ›› Issue (3): 532-540.DOI: 10.1016/S2095-3119(13)60254-3

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

LIU Xing-peng, ZHANG Ji-quan, CAI Wei-ying , TONG Zhi-jun

1.Natural Disaster Research Institute, College of Urban and Environmental Sciences, Northeast Normal University, Changchun 130024,P.R.China
2.Key Laboratory for Vegetation Ecology, Ministry of Education/Northeast Normal University, Changchun 130024, P.R.China
3.College of Tourism, Changchun University, Changchun 130607, P.R.China

收稿日期:2012-03-07 出版日期:2013-03-01 发布日期:2013-03-10
通讯作者: Correspondence LIU Xing-peng, Tel: +86-431-85099550, E-mail: liuxp912@nenu.edu.cn
基金资助:
This study was 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), and the National Scientific Research Special Project of Public Sectors (Agriculture) of China (200903041).

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

LIU Xing-peng, ZHANG Ji-quan, CAI Wei-ying , TONG Zhi-jun

1.Natural Disaster Research Institute, College of Urban and Environmental Sciences, Northeast Normal University, Changchun 130024,P.R.China
2.Key Laboratory for Vegetation Ecology, Ministry of Education/Northeast Normal University, Changchun 130024, P.R.China
3.College of Tourism, Changchun University, Changchun 130607, P.R.China

Received:2012-03-07 Online:2013-03-01 Published:2013-03-10
Contact: Correspondence LIU Xing-peng, Tel: +86-431-85099550, E-mail: liuxp912@nenu.edu.cn
Supported by:
This study was 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), and the National Scientific Research Special Project of Public Sectors (Agriculture) of China (200903041).

摘要/Abstract

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.

关键词: maize growth period , fuzzy gamma modeling , drought hazard

Abstract: 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.

Key words: maize growth period , fuzzy gamma modeling , drought hazard

LIU Xing-peng, ZHANG Ji-quan, CAI Wei-ying , TONG Zhi-jun. Assessing Maize Drought Hazard for Agricultural Areas Based on the Fuzzy Gamma Model[J]. Journal of Integrative Agriculture, 2013, 12(3): 532-540.

参考文献

[1]Bannayan M, Sanjani S, Alizadeh A, Lotfabadi S,Mohamadian A. 2010. Association between climateindices, aridity index, and rainfed crop yield in northeastof Iran. Field Crops Research, 118, 105-114

[2]Boken V K. 2009. Improving a drought early warning modelfor an arid region using a soil-moisture index. AppliedGeography, 29, 402-408

[3]Bonham-Carter G F. 1994. Geographic Information Systems forGeoscientists: Modelling with GIS, Computer Methods inthe Geosciences 13. Pergamon Press, New York.China’s Major Crops Water Consumption Contour MapWork Group. 1993. The Study on China’s Major CropsWater Consumption Contour Map. China AgriculturalScientech Press, Beijing. (in Chinese)

[4]Drought Assessment Standards. 2007. China’s State FloodControl and Drought Relief Headquarters. http://www.aqtd.cn/yjya/HTML/166347.html

[5]Han P, Wang P X, Zhang S Y, Zhu D H. 2010. Droughtforecasting based on the remote sensing data usingARIMA models. Mathematical and ComputerModelling, 51, 1398-1403

[6]Hayes M J. 2006. Drought indices. [2011-5-20]

[7]http://drought.unl.edu/whatis/indices.htmGhulam A, Qin Q, Teyip T, Li Z L. 2007. Modifiedperpendicular drought index (MPDI): a real-time droughtmonitoring method. ISPRS Journal of Photogrammetry& Remote Sensing, 62, 150-164

[8]Liaoning Provincial Department of Water Resources 2007.Extreme Summer Drought of Northwest LiaoningProvince in 2006. Liaoning Science and TechnologyPublishing House, Shenyang, China. (in Chinese)

[9]Logan K E, Brunsell N A, Jones A R, Feddema J J. 2010.Assessing spatiotemporal variability of drought in theU.S. central plains. Journal of Arid Environments, 74,247-255

[10]Mishra A K, Singh V P. 2011. A review of drought modeling.Journal of Hydrology, 403, 157-175

[11]Moreira E E, Coelho C A, Paulo A A, Pereira L S, Mexia J T.2008. SPI-based drought category prediction usingloglinear models. Journal of Hydrology, 354, 116-130

[12]Qi X, Niu Z, Wang B, Wang C. 2006. The Spatio-temporalcharacteristics of drought in China with remote sensingduring 1982-2001 Acta Pedologica Sinica, 43, 376-382(in Chinese)

[13]Quiring S M, Papakryiakou T N. 2003. An evaluation ofagricultural drought indices for the Canadian prairies.Agricultural and Forest Meteorology, 118, 49-62

[14]Rojas O, Vrieling A, Rembold F. 2011, Assessing droughtprobability for agricultural areas in Africa with coarseresolution remote sensing imagery. Remote Sensing ofEnvironment, 115, 343-352

[15]Sawatzky D L, Raines G L, Bonham-Carter G F, Looney C G.2009. SpatialData Modeller (SDM): ArcMAP 9.3geoprocessing tools for spatial data modelling usingweights of evidence, logistic regression, fuzzy logicand neural networks. [2011-5-11] http://arcscripts.esri.com/details.asp?dbid=15341

[16]Song L C, Deng Z Y, Dong A X. 2003. Drought. ChinaMeteorological Press, Beijing. p. 22.Tatli H, Türkes M. 2011. Empirical Orthogonal Functionanalysis of the palmer drought indices. Agriculturaland Forest Meteorology, 151, 981-991

[17]Vogt J V, Somma F. 2000. Drought and Drought Mitigationin Europe. Kluwer, Dordrecht.Wu H, Wilhite D A. 2004. An operational agriculturaldrought risk assessment model for Nebraska, USA.Natural Hazards, 33, 1-21

[18]Yurekli K, Kurunc A. 2006. Simulating agricultural droughtperiods based on daily rainfall and crop waterconsumption. Journal of Arid Environments, 67, 629-640

[19]Zhang J Q. 2004. Risk assessment of drought disaster in themaize-growing region of Songliao Plain, China.Agriculture, Ecosystems and Environment, 102, 133-153

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

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

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 0

编辑推荐

Metrics