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Research Article

Unveiling the climatic origin of streamflow persistence through multifractal analysis of hydro-meteorological datasets of India

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Pages 290-306 | Received 27 Jan 2022, Accepted 18 Nov 2022, Published online: 16 Jan 2023
 

ABSTRACT

Persistence and multifractality are two fundamental properties of hydrological time series. This study aims at understanding the origin of the Hurst exponent of streamflow time series. Thus, we have obtained streamflow, rainfall, and potential evapotranspiration (PET) time series data pertaining to 101 stations in 17 river basins in India. The persistence and multifractal properties of the time series were estimated using multifractal detrended fluctuation analysis (MFDFA). Results suggest that most of the rainfall time series (85%) exhibit short-term persistence while all the PET time series and 59% of the streamflow time series exhibit long-term persistence. The Hurst exponent exhibited by the river flow series simulated by the dynamic Budyko (DB) model that considers only rainfall and PET as inputs displayed a good agreement with the Hurst exponent of observed streamflow, supporting our hypothesis that climatic factors typically shape the value of the Hurst exponent.

Editor A. Castellarin Associate Editor H. Tyralis

Editor A. Castellarin Associate Editor H. Tyralis

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