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Watershed Planning within a Quantitative Scenario Analysis Framework
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A Cross-Reconstruction Method for Step-Changed Runoff Series to Implement Frequency Analysis under Changing

Jiantao Yang1, Hongbo Zhang1,2, Chongfeng Ren1,2

  • 1School of Environmental Science and Engineering, Chang'an University, Xi'an 710054, China.

International Journal of Environmental Research and Public Health
|November 10, 2019
PubMed
Summary
This summary is machine-generated.

Hydrological data stationarity is disrupted by environmental changes. A new cross-reconstruction (CR) method combined with empirical mode decomposition (EMD) expands limited hydrological data for reliable frequency analysis.

Keywords:
EMDdata expansionenvironmental changefrequency analysishydrologystationarity

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Area of Science:

  • Hydrology
  • Environmental Science
  • Data Science

Background:

  • Hydrological data stationarity is increasingly compromised globally due to environmental changes.
  • This non-stationarity challenges traditional hydrologic designs and threatens water resource projects.
  • Existing methods struggle with small datasets in step-changed hydrological series.

Purpose of the Study:

  • To introduce and validate the cross-reconstruction (CR) method for hydrological frequency analysis.
  • To address data limitations in step-changed runoff series by expanding small sample sizes.
  • To provide more reliable statistical insights for hydrological designs under non-stationary conditions.

Main Methods:

  • Utilized empirical mode decomposition (EMD) to process hydrological data.
  • Applied the proposed cross-reconstruction (CR) method for data expansion on step-changed runoff series.
  • Analyzed runoff records from three gauges in western China as case studies.

Main Results:

  • The CR method effectively expands small sample runoff data, meeting capacity requirements for frequency analysis.
  • Expanded data demonstrated statistics closer to the potential data population compared to measured data alone.
  • The approach proved advantageous for data expansion in small-sample runoff datasets.

Conclusions:

  • The CR method is suitable for frequency analysis of step-changed hydrological records.
  • It serves as a tool to construct hydrological probability distributions under varying environmental conditions.
  • This method can support water resource management policy-making by providing robust data analysis.