Changes in long-term properties and natural cycles of the Danube river level and flow induced by damming

In this paper we assessed changes in scaling properties of the river Danube level and flow data, associated with building of Djerdap/Iron Gates hydrological power plants positioned on the border of Romania and Serbia. We used detrended fluctuation analysis (DFA), wavelet transform spectral analysis (WTS) and wavelet modulus maxima method (WTMM) to investigate time series of measurements from hydrological stations in the vicinity of dams and in the area of up to 480 km upstream from dams, and time series of simulated NOAA-CIRES 20th Century Global Reanalysis precipitation data for the Djerdap/Iron Gates region. By comparing river dynamics during the periods before and after construction of dams, we were able to register changes in scaling that are different for recordings from upstream and from downstream (from dams) areas. We found that damming caused appearance of human-made or enhancement of natural cycles in the small time scales region, which largely influenced the change in temporal scaling in downstream recording stations. We additionally found disappearance or decline in the amplitude of large-time-scale cycles as a result of damming, which changed the dynamics of upstream data. The most prominent finding of our paper is a demonstration of a complete or partial loss of annual cycles in the upstream stations' data that stems from the operation of the artificial water reservoir and extends as far as 220 km from dams. We discussed probable sources of such found changes in scaling, aiming to provide explanations that could be of use in future environmental assessments. (C) 2020 Elsevier B.V. All rights reserved.

Automated summary

This study assessed the changes in scaling properties of the river Danube level and flow data associated with the construction of hydrological power plants. The results showed different scaling changes in upstream and downstream areas, with artificial reservoir operations leading to the disappearance of annual cycles in the upstream data.