We use the Detrended Cross-Correlation Analysis (DCCA) to investigate theinfluence of sun activity represented by sunspot numbers on one of the climateindicators, specifically rivers, represented by river flow fluctuation forDaugava, Holston, Nolichucky and French Broad rivers. The MultifractalDetrended Cross-Correlation Analysis (MF-DXA) shows that there exist somecrossovers in the cross-correlation fluctuation function versus time scale ofthe river flow and sunspot series. One of these crossovers corresponds to thewell-known cycle of solar activity demonstrating a universal property of thementioned rivers. The scaling exponent given by DCCA for original series atintermediate time scale, $(12-24)\leq s\leq 130$ months, is $\lambda =1.17\pm0.04$ which is almost similar for all underlying rivers at$1\sigma$confidence interval showing the second universal behavior of riverrunoffs. To remove the sinusoidal trends embedded in data sets, we apply theSingular Value Decomposition (SVD) method. Our results show that there exists along-range cross-correlation between the sunspot numbers and the underlyingstreamflow records. The magnitude of the scaling exponent and the correspondingcross-correlation exponent are $\lambda\in (0.76, 0.85)$ and$\gamma_{\times}\in(0.30, 0.48)$, respectively. Different values for scalingand cross-correlation exponents may be related to local and external factorssuch as topography, drainage network morphology, human activity and so on.Multifractal cross-correlation analysis demonstrates that all underlyingfluctuations have almost weak multifractal nature which is also a universalproperty for data series. In addition the empirical relation between scalingexponent derived by DCCA and Detrended Fluctuation Analysis (DFA), $\lambda\approx(h_{\rm sun} + h_{\rm river})/2$ is confirmed.
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