Methods

Fig. 2:

Fig. 1:

to address this gap

The main aim

In order to deal with the spatial heterogeneity of climate factors, we use K-Means clustering method to discretized climate factor data.

Extreme precipitation indicators

large-scale climate factor data

(1) to analyze the temporal and spatial trends of extreme precipitation events in ANC; (2) to quantify the impact of large-scale climate factors on EPEs using GDM; and (3) to explore the main influencing mechanisms of extreme precipitation timing in ANC.

as an extension of previous research

ollowing previous research (Brunner et al., 2019; Kang et al., 2023; Tosunoglu et al., 2020; Vittal et al., 2015), in the extraction of flood characteristics, the annual maximum peak is sampled, while the identification of flood duration is achieved through the utilization of the base flow curve (Figure S1 in Supporting Information S1).

previous studies have mostly focused on univariate flood magnitude characteristics, such as flood peak or volume,

大于 25%或小于 75%的为不可接受范围

Richer (1996)提出了一种衡量人类活动对流量改变程度的评价方法，同样也是基于 IHA 评价指标，选定一段待研究的年份具体公式如下

GSW 层和 STSWM 的年度地表水频率图用于揭示地表水时空动态

Bias correction methods can not account for all aspects of bias. Choices made in the seasonal window of bias correction will preserve GCM signals for the time period of bias correction (e.g., a 30-day window), but may not at longer timescales