Non-linear dynamics of United States streamflow dataset

Comprehensive hydrological dataset containing daily, weekly, monthly, quarterly, and annual streamflow time series with corresponding fractal and chaos metrics for three flow regimes (maximum, average, and minimum) for 2899 gauging stations across the United States and Puerto Rico. Time series are available from January 1, 1970, to December 31, 2023, in five temporal resolutions in raw and filtered formats (where negative, zero, and missing data were interpolated). A suite of fractal and chaos metrics is included with data and contains Hurst exponents, detrended fluctuation analysis, multifractality, wavelet transform modulus maxima (with varying bands and modulus methods), sample entropy, recurrence quantification analysis, and Lyapunov exponents. Gauges were grouped via fuzzy C-means clustering into three dynamic-behavior groups, with a matrix of membership probabilities. Gauge metadata including corrected latitudinal and longitudinal coordinates is included. The resulting dataset includes raw and processed time series, computed fractal and chaos metrics, cluster assignments, and location metadata for each station. These data enable researchers and water resources managers to benchmark streamflow dynamics across scales, support the evaluation of hydrological models or resources, perform regional classification, and develop machine-learning applications.

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Publication Details

Journal
Data in Brief
Published
2025-09-23
DOI
https://doi.org/10.1016/j.dib.2025.112092
Primary Topic
Complex Systems and Time Series Analysis
Type
article
Field-Weighted Citation Impact
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article

Non-linear dynamics of United States streamflow dataset

Krzysztof Raczyński, Julyan H. E. Cartwright, Katarzyna Grala
Data in Brief
Complex Systems and Time Series Analysis
article

Non-linear dynamics of United States streamflow dataset

Krzysztof Raczyński, Julyan H. E. Cartwright, Katarzyna Grala
article en

Abstract

Comprehensive hydrological dataset containing daily, weekly, monthly, quarterly, and annual streamflow time series with corresponding fractal and chaos metrics for three flow regimes (maximum, average, and minimum) for 2899 gauging stations across the United States and Puerto Rico. Time series are available from January 1, 1970, to December 31, 2023, in five temporal resolutions in raw and filtered formats (where negative, zero, and missing data were interpolated). A suite of fractal and chaos metrics is included with data and contains Hurst exponents, detrended fluctuation analysis, multifractality, wavelet transform modulus maxima (with varying bands and modulus methods), sample entropy, recurrence quantification analysis, and Lyapunov exponents. Gauges were grouped via fuzzy C-means clustering into three dynamic-behavior groups, with a matrix of membership probabilities. Gauge metadata including corrected latitudinal and longitudinal coordinates is included. The resulting dataset includes raw and processed time series, computed fractal and chaos metrics, cluster assignments, and location metadata for each station. These data enable researchers and water resources managers to benchmark streamflow dynamics across scales, support the evaluation of hydrological models or resources, perform regional classification, and develop machine-learning applications.

Data in BriefVol. 63
Mississippi State University (US)
Openalex Percentile: Top 66%
Complex Systems and Time Series Analysis
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