Temporal and Spatial Patterns of Barley in Tibet Major Agricultural Areas Based on the Comprehensive Assessment Index of Drought Disaster Risk

doi:10.11924/j.issn.1000-6850.casb20200200107

Abstract

Abstract:

To study the spatiotemporal changes of drought of barley in the main agricultural areas of Tibet, the authors took four risk factors, including the danger of drought disaster, the vulnerability of disaster victims, the vulnerability of disaster, and the ability to prevent and mitigate disaster, and adopted the expert score method and entropy weight method, to determine the weight of each factor to construct a comprehensive assessment model for drought risk and analyze the spatial and temporal pattern of drought disaster. The results showed that: the overall risk of drought disasters was generally low in the middle and high on both sides. The distribution of high-risk areas was relatively scattered. The sub-high-risk areas were mostly concentrated in the marginal zones of the study area. The middle-risk areas were distributed with left-sloping H-shape in parts of Lhasa, Shannan, and Linzhi, while the sub-low-risk and low-risk areas were scattered in Jiacha, Suoxian, and Linzhi stations; and the years with higher risk of drought disaster appeared in 1999, 2005, 2006, 2007, 2009, 2010, 2012, 2014, and 2015. The distribution of drought risk factors for barley in major agricultural areas in Tibet has obvious regional differences and a certain degree of continuity, and the drought trend in the study area and subdivision increases with each year.

Key words: barley, drought, comprehensive risk assessment index, spatiotemporal pattern, entropy weight method

CLC Number:

S423
S512.3

Shi Jiqing, Yang Feiyun, Bian Duo, Zhou Kanshe, Gan Chenlong. Temporal and Spatial Patterns of Barley in Tibet Major Agricultural Areas Based on the Comprehensive Assessment Index of Drought Disaster Risk[J]. Chinese Agricultural Science Bulletin, 2021, 37(2): 80-87.

Figures/Tables 8

站点	Kc	站点	Kc	站点	Kc
普兰	0.81	拉萨	0.75	米林	0.68
日喀则	0.75	墨竹工卡	0.78	昌都	0.67
聂拉木	0.78	尼木	0.74	丁青	0.72
定日	0.74	泽当	0.75	洛隆	0.71
拉孜	0.75	贡嘎	0.75	八宿	0.76
南木林	0.70	隆子	0.76	类乌齐	0.67
江孜	0.75	加查	0.75	左贡	0.71
索县	0.72	林芝	0.69	芒康	0.70
比如	0.77	波密	0.67

地市	趋势产量模拟方程	R²	n	MAPE/%
拉萨	$y ? = 0.064 t 3 - 2.9145 t 2 + 42.798 t + 623.89$	0.83	19	2.72
昌都	$y ? = 0.1028 t 3 - 3.2368 t 2 + 33.425 t + 391.8$	0.82	19	2.32
山南	$y ? = 0.0965 t 3 - 2.8497 t 2 + 27.208 t + 694.47$	0.53	19	2.52
日喀则	$y ? = 0.0839 t 3 - 3.3803 t 2 + 51.169 t + 556.72$	0.95	19	2.09
那曲	$y ? = 0.1039 t 3 - 3.1933 t 2 + 28.398 t + 300.22$	0.73	19	4.29
阿里	$y ? = 0.1224 t 3 - 4.0024 t 2 + 39.895 t + 303.66$	0.39	19	5.56
林芝	$y ? = 0.0845 t 3 - 2.0448 t 2 + 10.944 t + 533.83$	0.43	19	3.14

地市	趋势产量模拟方程	R²	n	MAPE/%
拉萨	$y ? = 0.064 t 3 - 2.9145 t 2 + 42.798 t + 623.89$	0.83	19	2.72
昌都	$y ? = 0.1028 t 3 - 3.2368 t 2 + 33.425 t + 391.8$	0.82	19	2.32
山南	$y ? = 0.0965 t 3 - 2.8497 t 2 + 27.208 t + 694.47$	0.53	19	2.52
日喀则	$y ? = 0.0839 t 3 - 3.3803 t 2 + 51.169 t + 556.72$	0.95	19	2.09
那曲	$y ? = 0.1039 t 3 - 3.1933 t 2 + 28.398 t + 300.22$	0.73	19	4.29
阿里	$y ? = 0.1224 t 3 - 4.0024 t 2 + 39.895 t + 303.66$	0.39	19	5.56
林芝	$y ? = 0.0845 t 3 - 2.0448 t 2 + 10.944 t + 533.83$	0.43	19	3.14

防灾减灾能力因子	权重	防灾减灾能力因子	权重
有效灌溉面积/播种面积a₁	0.22	大中型拖拉机a₅	0.10
旱涝保收面积/播种面积a₂	0.20	生产总值a₆	0.08
小型拖拉机a₃	0.16	农牧民纯收入a₇	0.06
农用运输车a₄	0.13	地方财政收入a₈	0.05

干旱灾害风险因子	熵权
致灾因子危险性a	0.26
承灾体易损性b	0.24
灾损脆弱性c	0.23
防灾减灾能力d	0.27

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