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Daily Streamflow of Argentine Rivers Analysis Using Information Theory Quantifiers.
Micaela Suriano1,2, Leonidas Facundo Caram2, Osvaldo Anibal Rosso3,4
1Departamento de Hidráulica, Facultad de Ingeniería, Universidad de Buenos Aires, Av. Las Heras 2214, Buenos Aires C1127AAR, Argentina.
Entropy (Basel, Switzerland)
|January 22, 2024
Summary
This study uses information theory to analyze Argentine river streamflow, differentiating randomness and chaos. Dam operations and basin size significantly impact river discharge dynamics and predictability.
Area of Science:
- Hydrology
- Information Theory
- Complex Systems Analysis
Background:
- Streamflow time series analysis is crucial for hydrological modeling.
- Understanding the randomness and chaos in river discharge is essential for water resource management.
- Information quantifiers offer novel methods to characterize complex hydrological dynamics.
Purpose of the Study:
- To analyze the temporal evolution of streamflow in Argentine rivers.
- To differentiate degrees of randomness and chaos in daily discharge series using information theory.
- To assess the influence of external factors like dam operations and basin size on streamflow dynamics.
Main Methods:
- Application of permutation entropy to analyze probability distributions of ordinal patterns.
- Calculation of statistical complexity and disequilibrium using Jensen-Shannon divergence.
- Utilizing the complexity-entropy causality plane (CECP) and Shannon entropy with Fisher Information Measure (FIM).
Main Results:
- Daily discharge series exhibit characteristics approximating Gaussian noise, yet natural phenomena present modeling challenges.
- Yacyretá dam operations demonstrably affect streamflow randomness near the dam, with the impact diminishing downstream.
- Basin size modulates streamflow: larger catchments show lower entropy and less noise, while smaller, mountainous basins exhibit higher entropy and lower complexity.
Conclusions:
- The study successfully characterizes daily discharge series behavior in Argentine rivers.
- Information quantifiers provide valuable insights into hydrological system classification and dynamics.
- Findings offer key data for improving hydrological modeling and water resource management strategies.
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