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\begin{document}

\title{Multiscale Persistence in Rainfall and Streamflow: Role of Rainfall and
Catchment Characteristics}



\author[1]{Pankaj Dey}%
\author[1]{P.P. Mujumdar}%
\affil[1]{Indian Institute of Science}%


\vspace{-1em}



  
  \date{May 25, 2024}


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\begin{abstract}
Hydrologic persistence is a unique property that explains the temporal
clustering of extreme events such as floods and droughts. It influences
the inter-arrival times of these extreme events and helps in
understanding the mechanism of their return periods. In this work, the
influence of rainfall amount and changing patterns of dry and wet spells
on persistence of their joint behaviour is investigated at multiple time
scales through estimation of Hurst Exponent (H) using Detrended
Fluctuation Analysis (DFA) and Detrended Cross-Correlation Analysis
(DCCA) at MOPEX (Model Parameter Estimation Project) catchments in
United States. The effect of catchment size on the persistence of
streamflow at multiple temporal scales is also analyzed. The results of
the analyses suggest that the state of persistence of joint behavior of
streamflow and rainfall is neither affected by rainfall amount nor by
the changing patterns of the dry and wet spells. However, the state of
persistence of rainfall is affected by the patterns of dry and wet
spells of observed rainfall. The results also suggest that catchment
area has a significant effect on the persistence of rainfall as there
exists a statistically significant correlation between catchment area
and H estimated at multiple time scales. Overall, the study finds that
catchment acts as a filter that transforms rainfall with low or no
persistence to streamflow with higher persistence manifested by
different catchment characteristics at multiple spatio-temporal scales.%
\end{abstract}%



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