Thesis colloquium Serge Versluis

In a research on the development of leaf habitats in small lowland streams a laboratory experiment has been set up to monitor the development under different flow conditions.
For this pictures were taken and have been analysed to develop a basic model to represent the habitat development.

Organisator Hydrology and Quantitative Water Management

wo 11 september 2013 15:00 tot 16:30

Locatie Lumen, building number 100
Droevendaalsesteeg 3a
6708 PB Wageningen
+31 317 481 700
Zaal/kamer Lumen 2

Laboratory experiments on the development of leave habitats in lowland streams

Part of stream restoration natural causes of hydraulic roughness, such as bank and floodplain vegetation, are often recommended for enhancing the variability in stream bed morphology and improving habitat development. Little is known on the development of leaf habitat in small lowland streams, therefore this research focused on identifying the critical flow velocities for leaf habitat. Based on experience, the assumption is often made that leaves are sensitive to peak discharges in water systems. Here, we performed laboratory experiments focussing on leaf habitat dynamics under different flow conditions. The photogrammetric showed that exponential patterns were visible in the development of a leaf habitat over time under constant flow conditions. Due to variability that was assumed to be of neglect able influence, as sand transport under these conditions caused variability in the results and difficulties with setting up a model. An exponential model with two variables had been set up based on the measurement data. The model showed promising results however the model where enough results showed that the model has potential. As the model consistently underestimated the measurements up to 4 hours and overestimated during the remainder of the measurements and the variables for the different fitted conditions showed similar values. Follow-up experiments, under more controlled conditions with no sediments and obstacles, could provide the required data to improve the model and predict habitat development more accurately.