<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The study was conducted from 2000 to 2003 in the tailwater of the Drzewieckie Lake, an artificial reservoir in Central Poland. Short-term peaks in water flow were generated for the purpose of the operation of a whitewater slalom canoeing track built just downstream of the dam. In 2002, the reservoir was drawn down. The patterns in habitat samples were recognized with a Kohonen’s unsupervised artificial neural network (SOM). The SOM spatial gradient was stronger than the SOM temporal gradient, which shows that the removal of the studied dam did not have a destructive impact on habitats’ features, as shown in other studies, and that the patchy nature of the riverbed has been maintained. The complete emptying of the Drzewieckie Lake took place at the beginning of the vegetation season, which allowed plants to cover the exposed bottom of the reservoir and, consequently, reduce the downstream flow of organic matter accumulated there. Patterns in the displacement of aquatic macrophytes, inorganic substratum and different fractions of particulate organic matter are discussed. The amount of dissolved oxygen decreased because of the lack of intensive water discharge from the reservoir into the river, which would result in high water turbulence. Results of this study are important for planning the ecologically sound dam removals.</p>
</abstract>

The study was conducted from 2000 to 2003 in the tailwater of the Drzewieckie Lake, an artificial reservoir in Central Poland. Short-term peaks in water flow were generated for the purpose of the operation of a whitewater slalom canoeing track built just downstream of the dam. In 2002, the reservoir was drawn down. The patterns in habitat samples were recognized with a Kohonen’s unsupervised artificial neural network (SOM). The SOM spatial gradient was stronger than the SOM temporal gradient, which shows that the removal of the studied dam did not have a destructive impact on habitats’ features, as shown in other studies, and that the patchy nature of the riverbed has been maintained. The complete emptying of the Drzewieckie Lake took place at the beginning of the vegetation season, which allowed plants to cover the exposed bottom of the reservoir and, consequently, reduce the downstream flow of organic matter accumulated there. Patterns in the displacement of aquatic macrophytes, inorganic substratum and different fractions of particulate organic matter are discussed. The amount of dissolved oxygen decreased because of the lack of intensive water discharge from the reservoir into the river, which would result in high water turbulence. Results of this study are important for planning the ecologically sound dam removals.

Tailwater habitat stability after dam removal and return to a natural hydrological regime

Department of Ecology and Vertebrate Zoology

Oceanological and Hydrobiological Studies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The study was conducted from 2000 to 2003 in the tailwater of the Drzewieckie Lake, an artificial reservoir in Central Poland. Short-term peaks in water flow...

Tailwater habitat stability after dam removal and return to a natural hydrological regime

Online veröffentlicht: 30. Sept. 2015

Seitenbereich: 410 - 425

Eingereicht: 15. Dez. 2014

Akzeptiert: 30. Apr. 2015

DOI: https://doi.org/10.1515/ohs-2015-0038

Schlüsselwörter
dam reservoir, impoundment, river restoration, temporary renaturisation, environmental parameters, hydropeaking, Kohonen artificial neural network, self-organizing map (SOM)

© 2015 Faculty of Oceanography and Geography, University of Gdańsk, Poland

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Tailwater habitat stability after dam removal and return to a natural hydrological regime

Online veröffentlicht: 30. Sept. 2015

Seitenbereich: 410 - 425

Eingereicht: 15. Dez. 2014

Akzeptiert: 30. Apr. 2015

DOI: https://doi.org/10.1515/ohs-2015-0038

Schlüsselwörterdam reservoir, impoundment, river restoration, temporary renaturisation, environmental parameters, hydropeaking, Kohonen artificial neural network, self-organizing map (SOM)

© 2015 Faculty of Oceanography and Geography, University of Gdańsk, Poland

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
dam reservoir, impoundment, river restoration, temporary renaturisation, environmental parameters, hydropeaking, Kohonen artificial neural network, self-organizing map (SOM)