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February 19, 2026SHILAP Revista de lepidopterologíaOpen Access

An Efficient Global Automatic Threshold Detection Algorithm for Large‐Scale Flood Distribution Analysis

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Authors

JGJiaojiao GouCMChiyuan MIAOJHJinlong Hu

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Overview

Demonstrates an algorithm that efficiently detects optimal flood thresholds, suggesting improved risk reduction methods.

Key Points

  • The aim is to identify optimal thresholds for flood distribution analysis using a novel algorithm.
  • Proposed a threshold detection method using Shuffled Complex Evolution optimization algorithm.
  • Conducted goodness of fit and Anderson-Darling tests at 10 river gauge stations in China.
  • Applied method across 380 stations in the Eastern Monsoon Region of China.
  • Identified optimal thresholds ranging from 0.14 m³/s to 49,062.53 m³/s, with a median of 293.55 m³/s.
  • Proposed method reduced bias in fitting generalized Pareto models compared to fixed thresholds.
  • High-flow thresholds varied significantly between wet and arid regions, indicating environmental influences.

Cite This Study

Gou et al. (2026) studied this question.

synapsesocial.com/papers/6996a7a5ecb39a600b3ed769https://doi.org/10.1029/2024wr039398
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