Spatio-temporal evolution characteristics of drought in the “Heng-Shao-Lou drought corridor”

doi:10.11755/j.issn.1006-7639(2023)-04-0550

Abstract

Abstract:

Recently, the droughts attack frequently in the Yangtze River basin, resulting in more and more loss. To further improve regional drought risk management and drought resistance capabilities, it is of great significance to conduct research on the spatio-temporal evolution characteristics of drought in typical drought-prone areas. “Heng-Shao-Lou drought corridor” in Hunan Province is a region with most severe droughts, the standardized precipitation index (SPI) dataset based on monthly precipitation data from 33 meteorological stations in this area from 1971 to 2022 is constructed. Citing the case of Shaoyang County, run theory is applied to integrate drought events, and Gumbel-Copula is adopted to construct the joint distribution function of drought duration and severity, then the joint return periods of drought are calculated and the method is extended to the whole study area. On the basis of it, the classification standard of drought grades is established, and the spatial distribution characteristics of drought probability for each level in the whole study area are analyzed. The results show that the peaks of theoretical joint return period of drought duration and severity for the type Ⅰ and type Ⅱ in Shaoyang County are around 97 a and 27 a, respectively, which indicates that the probability of drought events with long duration and high severity is very small and far lower than that of drought events with long duration or high severity, it is a common feature of drought events in research area. Furthermore, the combination of drought duration and severity joint distribution can effectively avoid segmentation of the whole drought event when drought grades are identified by a single variable, and can evaluate the complexity and large-scale impact of drought more accurately. In the past 52 years, the slight drought occurs most frequently in western region of the “Heng-Shao-Lou drought corridor”, while the frequency of severe or extreme drought is low. Extreme drought mainly distributes in Shaoyang County, Shaodong County and Shuangfeng County.

Key words: the Heng-Shao-Lou drought corridor, SPI, run theory, Copula function, joint return periods

摘要：

近年来，长江流域干旱事件频发，干旱灾害造成的损失越来越大，为进一步提升区域干旱灾害风险管理及防旱抗旱能力，开展典型旱区干旱时空演变规律研究具有重要意义。“衡邵娄干旱走廊”是湖南省干旱最严重区域，利用该区域33个气象站1971—2022年逐月降水量构建标准化降水指数（Standardized Precipitation Index，SPI）序列数据集，以邵阳县为示例，应用游程理论整合干旱事件，基于Gumbel-Copula函数构建干旱历时和强度联合分布函数，计算干旱联合重现期并推广至整个研究区域，在此基础上构建干旱等级划分标准，分析整个研究区域各等级干旱概率空间分布特征。主要结论如下：邵阳县Ⅰ型和Ⅱ型干旱历时和强度理论联合重现期峰值分别约97、27 a，表明长历时且高强度干旱事件发生概率很小，远低于长历时或高强度干旱事件发生概率，这是研究区干旱事件的共性。基于干旱历时和强度联合分布组合可有效避免单一变量在识别干旱等级时对干旱事件整体的分割，能够更准确评估干旱的复杂性及大范围影响。近52 a来，“衡邵娄干旱走廊”西部轻旱最频繁，重旱与特旱发生频率低，特旱主要分布在邵阳县、邵东县及双峰县一带。

关键词: 衡邵娄干旱走廊, SPI, 游程理论, Copula函数, 联合重现期

CLC Number:

P462.3

YANG Yang, ZHAO Weiming, HU Yingbing, SHENG Dong, WEI Yongqiang, SHEN Zhigao, TAN Jun. Spatio-temporal evolution characteristics of drought in the “Heng-Shao-Lou drought corridor”[J]. Journal of Arid Meteorology, 2023, 41(4): 550-559.

杨扬, 赵伟明, 胡颖冰, 盛东, 魏永强, 申志高, 谭军. “衡邵娄干旱走廊”干旱时空演变特征分析[J]. 干旱气象, 2023, 41(4): 550-559.

Figures/Tables 12

Fig.1 The distribution of geographic location， terrain elevation and meteorological stations in the Heng-Shao-Lou drought corridor

Tab.1 Classification standard of drought grades based on SPI

等级	类型	SPI
1	无旱	>-0.5
2	轻旱	（-1.0， -0.5]
3	中旱	（-1.5， -1.0]
4	重旱	（-2.0， -1.5]
5	特旱	≤-2.0

Tab.2 Statistics of drought events in Shaoyang County during 1971-2022

类型	SPI-1		游程理论整合
类型	发生频次	发生频率/%	发生频次	发生频率/%
无旱	399	70.8	360	76.9
轻旱	79	14.0	59	12.6
中旱	48	8.5	29	6.2
重旱	22	3.9	13	2.7
特旱	16	2.8	7	1.5

Tab.3 The characteristic variables statistics of duration and severity of drought events in Shaoyang County during 1971-2022

特征量	干旱历时/月	干旱强度
均值	1.89	1.94
方差	1.67	2.24
1/4中位数	1.00	0.85
中位数	1.00	1.36
3/4中位数	2.00	2.52

Fig.2 Distribution of duration （a） and severity （b） of drought events and their fitting curves in Shaoyang County during 1971-2022

Tab.4 The joint distribution function of duration and severity of drought events based on different types of Copula functions and goodness-of-fit test in Shaoyang County during 1971-2022

Copula函数类型	联合分布函数	θ拟合参数	$d 2$
Gumbel-Copula	$e - - l n H s 1 / θ + - l n G d 1 / θ θ$	2.199 2	0.011
Clayton-Copula	$H s - θ + G d - θ - 1 - 1 / θ$	2.175 0	0.019
Frank-Copula	$- 1 θ l n 1 + e - θ H s - 1 e - θ G d - 1 e - θ - 1$	7.215 3	0.018

Tab.4 The joint distribution function of duration and severity of drought events based on different types of Copula functions and goodness-of-fit test in Shaoyang County during 1971-2022

Copula函数类型	联合分布函数	θ拟合参数	$d 2$
Gumbel-Copula	$e - - l n H s 1 / θ + - l n G d 1 / θ θ$	2.199 2	0.011
Clayton-Copula	$H s - θ + G d - θ - 1 - 1 / θ$	2.175 0	0.019
Frank-Copula	$- 1 θ l n 1 + e - θ H s - 1 e - θ G d - 1 e - θ - 1$	7.215 3	0.018

Fig.3 The joint distribution density （a） and cumulative probability （b） of drought events based on Gumbel-Copula function in Shaoyang County during 1971-2022

Fig.4 The joint return periods of drought events for the type Ⅰ （a） and type Ⅱ （b） in Shaoyang County during 1971-2022

Fig.5 Distribution of joint return periods of drought events for the type Ⅰ （a） and type Ⅱ （b） in Shaoyang County during 1971-2022 （Unit： a）

Tab.5 The classification standard of drought grades based on joint return period of drought duration and severity in the Heng-Shao-Lou drought corridor

干旱类型	干旱重现期/a	干旱历时/月，强度	累积概率/%
轻旱	0~1	$D ≤ 3, S ≤ 2.5$	（30.78， 100.00）
中旱	>1~2	$3 < D ≤ 5,2.5 < S ≤ 3.5$	（13.43， 30.78]
重旱	>2~6	$5 < D ≤ 8,3.5 < S ≤ 5.0$	（4.80， 13.43]
特旱	>6	$D > 8, S > 5.0$	（0.00， 4.80]

Tab.5 The classification standard of drought grades based on joint return period of drought duration and severity in the Heng-Shao-Lou drought corridor

干旱类型	干旱重现期/a	干旱历时/月，强度	累积概率/%
轻旱	0~1	$D ≤ 3, S ≤ 2.5$	（30.78， 100.00）
中旱	>1~2	$3 < D ≤ 5,2.5 < S ≤ 3.5$	（13.43， 30.78]
重旱	>2~6	$5 < D ≤ 8,3.5 < S ≤ 5.0$	（4.80， 13.43]
特旱	>6	$D > 8, S > 5.0$	（0.00， 4.80]

Tab.6 Statistics of drought events in the Heng-Shao-Lou drought corridor during 1971-2022

干旱类型	游程理论整合		干旱历时和强度联合重现期
干旱类型	干旱频数	干旱频率/%	干旱频数	干旱频率/%
轻旱	1 375	53.2	1 788	69.2
中旱	751	29.1	448	17.3
重旱	312	12.1	223	8.6
特旱	145	5.6	124	4.8

Fig.6 Spatial distribution of drought frequency for different types in the Heng-Shao-Lou drought corridor during 1971-2022 （Unit： %）（a） slight drought，（b） moderate drought，（c） severe drought，（d） extreme drought

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