Skip to content
naulon
Not checkedNot checked for notices yet.

A driving force analysis method for drought-flood abrupt alternation events

Li Wang, Zhe Yuan, Xiaoliang Shi and 3 more

Ecological Informatics · 2025

doi:10.1016/j.ecoinf.2025.103214 (opens in a new tab)

We email you when a new notice or a question about this paper appears.

Abstract

Drought-Flood Abrupt Alternation (DFAA) events are complex hydrometeorological disasters that have become increasingly frequent under global warming, posing significant threats to socio-economic systems and the ecological stability. This study applies the Standardized Weighted Average Precipitation (SWAP) index to identify DFAA events at a daily scale in the middle and lower reaches of the Yangtze River Basin (MLRYRB) from 2001 to 2022. Additionally, a method is proposed to analyze the driving factors of DFAA and quantify the spatial distribution of dominant contributors. The results indicate that: (1) in the MLRYRB, DFAA events lasted up to 50 days and occurred 7 to 10 times in total, with the highest frequency in southern Shaanxi, central Hubei, central Anhui, and southern Jiangxi; (2) the areas affected by DTF and FTD events decreased at rates of 0.43/a and 0.62/a, respectively. DTF events were predominantly moderate in intensity, while FTD events were mostly slight; (3) the key factors driving drought-flood alternation included convective precipitation (CP), total cloud cover (TCC), top net solar radiation (TNSR), 2-m temperature (TEM), and relative humidity (RH). Regions dominated by RH and TEM accounted for 44.62 % and 30.22 % of the study area, respectively, mainly in Hubei, Hunan, Jiangxi, and Anhui. These findings offer a scientific basis for developing disaster prevention and mitigation strategies in the region.

Abstract licence: CC BY-NC-ND

References70

    40 more references, whose wording the paper’s licence keeps private.

    All 70 references

    Reads

    Read by people on this page

    None yet.

    Checked or read by AI through naulon

    None yet.

    A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

    Are you an author?

    Is this your paper?

    Claim it to add your note and be paid when agents cite it. Free.