This work sits at the fringe: its nearest neighbors in the archive study solar cycles, solar tidal rhythms, space weather, and forecasts that account for the cycle. But almost no one links solar activity directly to water discharge in a specific continental river. Data have already accumulated on the Sun's influence on rainfall in Asia, Africa, and Mexico, as well as on the link between cloud cover and cosmic rays. This article takes the next step: instead of rainfall, it uses an integrated measure, river discharge, which averages precipitation, evaporation, and infiltration over a vast area.
The authors took daily discharge measurements of the Parana at the gauging station in the city of Corrientes, 900 km from the mouth, from 1904 onward. The river's hydrological year runs from September to August, so they built series over those intervals. For solar activity, they used the international sunspot number and the Wang et al. reconstruction of solar irradiance (energy flux). They removed trends with a low-pass filter with a 50-year cutoff and smoothed the solar cycle with an 11-year moving average. Correlations were tested with the parametric Student's t-test and the nonparametric random-phase test.
On the multi-decadal scale, the Parana's flow and sunspot number move almost in sync: Pearson correlation coefficient r=0.78, significance above 99.99% by t-test and 99.6% by the random-phase test. With the irradiance reconstruction, the correlation is slightly lower, r=0.69. The link with galactic cosmic rays (via neutron count at Climax) and the aa geomagnetic index was weaker, pointing to a more direct irradiance effect rather than a cloud-mediated mechanism. On short timescales, after subtracting the 11-year smoothing, flow correlates strongly with the El Nino 1+2 index (r=0.65, significance >99.99%). The discharge peaks of 1982 and 1997 coincide with exceptional El Nino events.
Unlike neighboring studies that examine solar cycles in themselves or their influence on the atmosphere on a global scale, this article ties the solar signal to a specific water body of continental scale. It shows that solar activity changes not only temperature or average precipitation but also the regional distribution of moisture: in southeastern South America, high solar activity coincides with wetter conditions, whereas in East Africa and the Yucatan it coincides with droughts. This underscores that the solar influence on climate is not globally uniform but redistributes moisture through atmospheric circulation.
The topic could develop toward combining solar indices and El Nino indices in statistical models for discharge forecasting. If the correlations hold on independent data, it may become possible to warn of floods months or years in advance. It would also be promising to test whether climate models with prescribed solar forcing reproduce the observed link to river discharge in this region.
The result directly concerns hydrology, climatology, and natural-hazard forecasting. It could be useful for planning agriculture, hydropower, and navigation in the Parana basin.
Test the robustness of the correlations on independent periods and for other rivers in the region, such as the Iguazu. Build a forecasting model that combines the solar index and El Nino, and evaluate its skill on retrospective data.
For hydrology, a key unresolved problem is separating the contributions of natural variability (solar, oceanic) and anthropogenic climate change to river flow regimes. This work shows that on multi-decadal timescales, the solar signal can be comparable to the trend caused by other factors, and it must be accounted for in attributing changes.
During the 1997 flood, 180,000 square kilometers were under water, an area larger than Greece. Some 125,000 people had to be evacuated, and 25 died.