Association between climate indices, aridity index, and rainfed crop yield in northeast of Iran

被引:152
作者
Bannayan, Mohammad [1 ]
Sanjani, Sarah [1 ]
Alizadeh, Amin [1 ]
Lotfabadi, S. Sadeghi [1 ]
Mohamadian, Azadeh [2 ]
机构
[1] Ferdowsi Univ Mashhad, Fac Agr, Mashhad, Iran
[2] Climatol Res Inst, Climatol Atmospher Disasters Grp, Mashhad, Iran
关键词
Crop yield variability; Climate indices; Weather variability and agriculture; Rainfed crop production; SEA-SURFACE TEMPERATURE; SOUTHERN OSCILLATION; ATLANTIC OSCILLATION; ARCTIC OSCILLATION; DROUGHT; VARIABILITY; PATTERNS; ENSO; PREDICTABILITY; PRECIPITATION;
D O I
10.1016/j.fcr.2010.04.011
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Agricultural drought occurs when there is a deficit in soil water supply to crops. Severe drought limits crop water availability and reduces yield. Rainfed crop production is very vulnerable to drought conditions and farmers in northeast of Iran who heavily depend on their rainfed cereals production usually suffer from drought occurrence. Based on history, any severe drought resulted in severe financial problems and forced the affected farmers to move to cities in search of alternative jobs. Any possibility to enable the farmers to mitigate or adapt to drought is highly required. In this study, the relationship between aridity index (AI) and detrended crop yield (1985-2005) of selected crops (wheat and barley) and the influence of three climate indices (AO, NAO and NINO-3.4) were assessed for Khorasan province in northeast of Iran. All associations were assessed at annual, seasonal (wet and dry seasons) and monthly scale considering both concurrent and lag correlations (1-year and 2-year lag). Our results indicated a significant correlation (P < 0.05) between the AI and crops yield mostly in central Khorasan province. Our study also showed that correlation coefficient between AI and barley yield was stronger than AI and wheat yield across all study locations. Seasonal (wet) AI showed significant correlation with crops yield. These results demonstrated that, in some areas of Khorasan, drought is one of the key causes of interannual yield variability. We also observed a significant association between NAO and NINO-3.4 with AI. Precipitation is one of the components of AI, so AI response to NAO and NINO-3.4 can be related to the observed association between this index and precipitation. It seems that these indices could be useful tools to monitor drought patterns and subsequent yield variability in some regions of Khorasan province. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:105 / 114
页数:10
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