At the end of last year, the KNW determined the Bachelor's and Master's Thesis Awards 2024. KNW is the independent knowledge(s) network in the water sector. They offer water professionals, companies and organisations a unique platform, with plenty of opportunities for knowledge sharing, inspiration and meeting. The nominees were students from the University of Twente, Windesheim University of Applied Sciences, Rotterdam University of Applied Sciences and The Hague University of Applied Sciences. The students presented their thesis with a poster, after which the jury announced the winners. The award ceremony was held during the KNW Autumn Congress: Sustainable Doing!
First prize: Bram Denkers (UT) - Flow-Vegetation Interactions at Vegetated River Banks.
Second prize: Joep Witteman (UT) - Assessing the hydraulic conductivity of the seepage-reducing measure 'Sand Bentonite'.
Third prize: Luuk van Laar (UT) - Two data-driven approaches for predicting bed levels in 3D for the Waal River.
Flow-Vegetation Interactions at Vegetated River Banks
Bram Denkers
"In my thesis, I investigated the influence of riparian vegetation on turbulent flows in streams. While the effect of riparian vegetation has often been studied in flume experiments under ideal conditions, the question remains how transferable these findings are to natural conditions with more complex morphology and vegetation patterns. To explore this, we conducted flow measurements in the Dinkel with various vegetation types. The results showed a well-defined shear stress layer at the edges, accompanied by large-scale turbulent structures. Semi-empirical equations from the literature predicted flow velocities and shear stresses reasonably well in some areas, but less accurately near the vegetation boundary. This highlights the importance of further research and the modelling challenges in natural river systems."
Assessing the hydraulic conductivity of the seepage-reducing measure 'Sand Bentonite'
Joep Witteman
"How can a canal with a permeable bottom lose its water? At the Twente Canal, this was addressed by applying a Sand-Bentonite Mixture (SBM) to the canal bed. This solution raised the question of whether SBM could be used in other environments. My thesis reveals that the mixture settles through coarse layers, increases the pH of surrounding water, and in water with increased salinity, shrinkage is accelerated, leading to the formation of (temporary) cracks. These findings enhance the understanding of the potential influence of environmental factors on the effectiveness of the mixture as a seepage control measure."
Figure 1: Overview of large-scale test setup. Figure 2: Settling of the SBM through the coarse layer.
Two data-driven approaches for predicting bed levels in 3D for the Waal River
Luuk van Laar
"My research focused on predicting 3D bed levels for the Waal River by developing and comparing two data-driven approaches. My self-developed dune migration model proved to be more accurate than the machine learning model TrajGRU, which produced blurred predictions despite improvements. The dune migration model had a smaller error in bed-level predictions and more accurate predictions on the location of the river dune peaks. Future research could focus more on the dune migration model by better incorporating vertical changes in bed levels."