Study on the evolutionary characteristics of agricultural drought disasters and the relationship with climatic factors in Yunnan

doi:10.11755/j.issn.1006-7639-2025-01-0021

Abstract

Abstract:

The study of the evolution characteristics of agricultural drought disasters and their relationship with climatic factors can identify the critical periods of the impact of climatic factors on drought disasters, reduce the losses caused by drought disasters effectively, and improve the technology and management level of drought disaster risk assessment. By using agricultural drought disaster data, precipitation, average temperature, and effective irrigation area data, this paper analyzed spatiotemporal distribution characteristics of agricultural drought disasters, studied the relationship between agricultural drought disasters and climatic factors, and constructed a drought disaster assessment model based on multiple climatic factors during the critical periods. The results show that from 1978 to 2022, the agricultural drought disaster-affected rate and disaster-damaged rate in Yunnan both showed a decreasing trend. The decreasing rate was 0.49% and 0.09% per 10 years for the agricultural drought disaster-affected rate and disaster-damaged rate, respectively. The agricultural drought disaster-affected rate and disaster-damaged rate experienced two abrupt changes from 1978 to 2022: an increase from less to more in 2004 and a decrease from more to less in 2013. The drought disaster was relatively severe from 2005 to 2013. The comprehensive drought loss rate in 14 prefectures (cities) was 2%-6% higher than the average from 1996 to 2022. From 2014 to 2022, the severity of agricultural drought disaster was lower than the average level from 1996 to 2022 in most areas in Yunnan. Precipitation in May, average temperature in May, and meteorological drought from January to March and from May to September are crucial climate factors to agricultural drought disaster losses in Yunnan, which impact more significantly than those of similar climatic elements at the annual scale. After 2014, precipitation in May generally decreased, average temperature in May and meteorological drought from January to March and from May to September were intensified. However, the agricultural drought disaster in Yunnan was relatively less severe than the average from 1996 to 2022. The one of important reason was that the number of water conservancy facilities increased, the effective irrigation area increased, and the ability of drought disaster prevention and mitigation was enhanced. Based on multiple climatic factors during the critical period, the fitted model has been built, which has a better estimation of agricultural drought disasters in Yunnan and has a better fitting relationship than that with similar climatic elements at the annual scale.

Key words: Yunnan, agricultural drought disasters, evolutionary characteristics, climate factors, critical impact period

摘要： 研究农业干旱灾害演变特征及其与气候因子的关系，可以明确气候因子影响干旱灾害的关键期，有效减轻干旱灾害造成的损失，对提高干旱灾害风险评估技术和风险管理水平有重要科学意义。本文利用云南农业干旱灾害统计数据、降水、平均气温及有效灌溉面积等数据，首先分析农业干旱灾害时空分布特征，然后研究其与气候因子的关系，探讨干旱灾害变化的可能成因，最后构建基于关键期多气候因子的干旱灾害评估模型。结果表明：1978—2022年云南农业干旱受灾率和成灾率总体呈减小趋势，减小速率分别为0.49%·（10 a）^-1和0.09%·（10 a）^-1，在2004年和2013年左右分别发生了由少到多和由多到少的突变。2005—2013年干旱灾害较为严重，云南有14个州（市）干旱综合损失率比1996—2022年平均偏多2%~6%，2014—2022年全省大部地区农业干旱灾害减轻。云南5月降水、5月平均气温及1—3月和5—9月气象干旱对农业干旱灾害损失至关重要，其影响明显大于年尺度的同类气候要素，是影响云南农业干旱灾害的关键期气候因子。2014年以后，云南5月降水总体偏少、平均气温偏高，1—3月、5—9月气象干旱总体偏强，但农业干旱灾害偏轻，重要原因之一是水利设施增多，有效灌溉面积增加，干旱防灾减灾能力增强。基于关键期多气候因子构建的拟合模型对云南农业干旱灾害估算具有较好的效果，其拟合关系明显好于与年尺度的同类气候要素的关系。

关键词: 云南, 农业干旱灾害, 演变特征, 气候因子, 关键影响期

CLC Number:

P466

ZHOU Jianqin, LI Meng, TAO Yun, DOU Xiaodong, WANG Yuyouting. Study on the evolutionary characteristics of agricultural drought disasters and the relationship with climatic factors in Yunnan[J]. Journal of Arid Meteorology, 2025, 43(1): 21-31.

周建琴, 李蒙, 陶云, 窦小东, 王玉尤婷. 云南农业干旱灾害演变特征及其与气候因子的关系研究[J]. 干旱气象, 2025, 43(1): 21-31.

Figures/Tables 12

Tab.1 The classification standard of meteorological drought composite index

等级	类型	MCI
1	无旱	-0.5<MCI
2	轻旱	-1.0<MCI≤-0.5
3	中旱	-1.5<MCI≤-1.0
4	重旱	-2.0<MCI≤-1.5
5	特旱	MCI≤-2.0

Fig.1 The inter-annual variation of disaster-affected rate and disaster-damaged rate of agricultural drought （a） and their 9-year moving t-test （b） in Yunnan from 1978 to 2022

Tab.2

时段	受灾率	成灾率
1978—2004年	11.28	5.02
2005—2013年	20.11	11.44
2014—2022年	6.10	2.38
1978—2022年	11.88	5.77

Fig.2 The spatial distribution of comprehensive loss rates of agricultural drought in 16 prefectures (cities) of Yunnan during different periods (Unit: %)

Tab.3 The number of years with different levels of agricultural drought disasters and the climate tendency rate of comprehensive loss rate in 16 prefectures （cities） of Yunnan from 1996 to 2022

州（市）	不同程度干旱灾害年数/a			综合损失率气候倾向率/[%·（10 a）^-1]
州（市）	重灾	中灾	轻灾	综合损失率气候倾向率/[%·（10 a）^-1]
昆明	8	2	12	-0.59
昭通	8	3	8	-0.46
曲靖	6	3	12	-0.57
玉溪	10	5	9	0.89
保山	8	7	8	-1.48
楚雄	10	6	3	-1.39
红河	6	7	7	-1.19
文山	6	6	5	-1.28
普洱	8	5	7	-0.07
西双版纳	6	3	4	-1.30
大理	12	5	3	0.78
德宏	1	3	8	0.11
丽江	9	3	8	2.21
怒江	2	1	4	-0.01
迪庆	5	5	5	-0.98
临沧	3	7	14	0.04

Fig.3 The monthly variation of correlation coefficients between disaster-affected rate and disaster-damaged rate of agricultural drought with precipitation and temperature in Yunnan from 1978 to 2022

Fig.4 The monthly variation of correlation coefficients between disaster-affected rate and disaster-damaged rate of agricultural drought and the number of stations of moderate drought and above in Yunnan from 1978 to 2022

Fig.5 Standardized sequences of disaster-affected rate and disaster-damaged rate of agricultural drought，May precipitation，May average temperature，and the number of moderate drought and above stations from January to March and from May to September in Yunnan from 1978 to 2022

Tab.4 Correlation coefficients between the disaster-affected rate and disaster-damaged rate of agricultural drought with May precipitation，May average temperature，and the number of meteorological drought stations from January to March and from May to September in Yunnan during different periods

时段	受灾率与降水	成灾率与降水	受灾率与气温	成灾率与气温	受灾率与干旱站次数	成灾率与干旱站次数
1978—2022年	-0.45^**	-0.38^**	0.46^**	0.40^**	0.63^**	0.58^**
1978—2013年	-0.57^**	-0.48^**	0.67^**	0.59^**	0.71^**	0.65^**
2014—2022年	-0.63	-0.70^*	0.68^*	0.77^*	0.57	0.54

Fig.6 The planting area and the proportion of effectively irrigated area of main crops from 1978 to 2022 (a), the number and capacity of reservoirs in Yunnan from 1987 to 2022 (b)

Tab.5 Correlation parameters of the statistical values and estimated values of the disaster-affected rate and disaster-damaged rate of agricultural drought fitting models based on the temperature，precipitation，the number of meteorological drought stations and effective irrigation area in the whole year and the critical period

时段	气候因子	受灾率			成灾率
时段	气候因子	相关系数	标准误差/%	平均绝对误差/%	相关系数	标准误差/%	平均绝对误差/%
全年	气温	0.11	8.90	6.23	0.17	5.68	3.62
	降水	0.35^*	8.40	5.60	0.27	5.56	3.44
	干旱站次数	0.48^***	7.85	5.52	0.43^**	5.20	3.39
	综合因子	0.53^***	7.61	5.57	0.48^**	5.06	3.38
关键期	气温	0.46^**	7.97	5.57	0.40^**	5.28	3.46
	降水	0.45^**	7.99	5.54	0.37^*	5.35	3.22
	干旱站次数	0.63^***	6.93	4.90	0.57^***	4.70	3.09
	综合因子	0.69^***	6.51	4.69	0.61^***	4.58	2.99

Fig.7 The inter-annual variation of the statistical values and estimated values of disaster-affected rate （a） and disaster-damaged rate （b） of agricultural drought by fitting models based on the multi-factors in the whole year and the critical period

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