Probabilistic assessment of drought impacts on wheat yield in south-eastern Australia

被引:8
|
作者
Xiang, Keyu [1 ,2 ]
Wang, Bin [2 ]
Liu, De Li [2 ,3 ]
Chen, Chao [4 ]
Waters, Cathy [5 ]
Huete, Alfredo [1 ]
Yu, Qiang [6 ]
机构
[1] Univ Technol Sydney, Fac Sci, Sch Life Sci, POB 123,Broadway, Sydney, NSW 2007, Australia
[2] Wagga Wagga Agr Inst, NSW Dept Primary Ind, Wagga Wagga, NSW 2650, Australia
[3] Univ New South Wales, Climate Change Res Ctr, Sydney, NSW 2052, Australia
[4] CSIRO Agr & Food, Private Bag 5,PO, Wembley, WA 6913, Australia
[5] NSW Dept Primary Ind, Dubbo, NSW 2830, Australia
[6] Northwest A&F Univ, State Key Lab Soil Eros & Dryland Farming Loess Pl, Yangling 712100, Shaanxi, Peoples R China
关键词
Wheat yield; Drought index; Copula -based function; Yield loss probability; Drought threshold; CROP YIELD; PROJECTED CHANGES; RISK-ASSESSMENT; UNITED-STATES; CLIMATE; DEPENDENCE; SCALES; CHINA; STUBBLE; TRENDS;
D O I
10.1016/j.agwat.2023.108359
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
A risk-based approach is more meaningful to quantify the effects of drought on crop yield given the randomness nature of past drought events, compared to the deterministic approach. However, the majority of these proba-bilistic studies are conducted at national or global scale to assess the yield loss probability under given drought conditions. There is still a lack of research combining droughts and crop yields in a probabilistic way at a local scale. Moreover, it is unclear how drought threshold triggering yield loss at a given conditional probability will vary in dryland cropping regions. Here, we used wheat yield data from 66 shires in New South Wales (NSW) wheat belt and meteorological data from 986 weather stations. A copula-based probabilistic method was developed to explore the yield loss probability to various drought conditions. We investigated the drought threshold under a given yield loss probability using the constructed copula function. We found that SPEI-6 in October was the optimal drought index to represent detrended wheat yield variation as this period covered the main growth stages of winter wheat in the study region. Our results show that as the severity of drought increased, the wheat yield loss probability also increased. Yield loss probability varied among the study shires, mainly due to the various climate conditions of each region. The drought threshold in subregion 1 (the north-west) was highest, followed by subregion 2 (the southwest) and subregion 3 (the eastern), indicating that wheat yield in subregion 1 was more sensitive to drought. The findings could provide important direction and benchmarks for stakeholders in evaluating the agricultural impact of drought, especially in those drought prone areas. We expect that the methodological framework developed here can be extended to other dryland areas to provide helpful information to growers, risk management policy makers and agricultural insurance evaluators.
引用
收藏
页数:11
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