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Multicomponent assessment of the impact of hydropower cascade on fish metrics. | LitMetric

The water sector is one of the priority areas of the European Union; therefore, legislation encourages the development of methods to protect the river ecosystem. The key to this is the characterization of the river's physical features with respect to ecological quality. Rivers are a complex system in which geomorphic conditions, hydrological regime, and ecological indicators interact. The group of hydropower plants (HPPs) that forms a hydropower cascade disturbs the natural continuity of river system components. Analysis of the spatial and temporal alterations in the river environment is important for understanding the potential impact of the hydropower cascade on ecological indicators. In a current study, the multicomponent assessment was used to evaluate the impact of the hydropower cascade of five HPPs on fish metrics as ecological indicators in the case study Varduva River. The research involved field surveys to collect hydrological data in highly affected ungauged river to estimate indicators of hydrologic alterations under HPPs operation, use of Unmanned Aerial Vehicles and digital photogrammetry to map geomorphic units, fish sampling to estimate composition of fish species and guilds, and fish habitat availability modelling based on the collected data and the conditional habitat suitability criteria using the MesoHABSIM modelling approach. Results revealed that the technical characteristics of HPPs determined their individual operation mode, which had a crucial impact on the hydrologic alterations of the river and, together with the distance between the dams, on the variation of fish metrics in the hydropower cascade. The intensive operation of the hydropower cascade created adverse effects for intolerant fish but was advantageous for tolerant fish species. The proposed HPP multimetric correlated with the fish metrics and showed similar tendencies between HPPs as habitat integrity index (IH), derived from MesoHABSIM modelling.

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http://dx.doi.org/10.1016/j.scitotenv.2023.167541DOI Listing

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