Identifying drought events in Beijing-Tianjin region using three-dimensional approach

丽娜·托库; 门宝辉; 刘楠; 吕行

doi:10.11660/slfdxb.20241105

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Identifying drought events in Beijing-Tianjin region using three-dimensional approach

更新时间：2026-07-22

- Identifying drought events in Beijing-Tianjin region using three-dimensional approach
- Journal of Hydroelectric Engineering Vol. 43, Issue 11, (2024)
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- DOI：10.11660/slfdxb.20241105
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- Online First：25 November 2024，
  
  Published：2024
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丽娜·托库, 门宝辉, 刘楠, et al. Identifying drought events in Beijing-Tianjin region using three-dimensional approach[J]. Journal of Hydroelectric Engineering, 2024, 43(11).
DOI：

丽娜·托库, 门宝辉, 刘楠, et al. Identifying drought events in Beijing-Tianjin region using three-dimensional approach[J]. Journal of Hydroelectric Engineering, 2024, 43(11). DOI： 10.11660/slfdxb.20241105.

摘要

京津区域经济发达、人口密集，对干旱事件造成的伤害更加敏感。干旱事件的频发给京津区域社会经济和水安全保障带来挑战。本文基于三维视角的干旱识别方法，从经度、纬度和时间中提取连续的干旱事件，利用京津地区的标准化植被指数（SVCI）对其干旱事件进行识别；根据持续时间、面积占比和强度来量化干旱事件；利用Copula函数进行频率分析和重现期计算。结果表明：本文采用SVCI进行三维识别的干旱事件基本符合文献记载的事件，结果是合理可靠的；在1982—2020年京津区域共识别出干旱事件48场，其中持续3个月及以上的干旱有34场；三维Copula函数可以考虑更多干旱特征因子，较二维Copula有拟合优势。

Abstract

The Beijing-Tianjin region

economically developed and densely populated

is highly vulnerable to drought events

which poses a challenge to its socio-economic development and water security. This paper presents a method for identifying droughts using a three-dimensional approach that considers longitude

latitude

and time

and an application of the Standardized Vegetation Index (SVCI) to detection of the drought events in this region. We quantify the events based on duration

area share

and intensity

and examine their frequencies and return periods using the Copula function. The results show the drought events identified using SVCI align with those recorded in literature

indicating the results of this study are reliable. In the study region

totally 48 drought events occurred from 1982 to 2020

with 34 lasting three months or longer. Compared to its two-dimensional version

the three-dimensional Copula function is more effective in fitting the joint distributions of drought variables in the region

considering more factors for better fitting.

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