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Effect of vegetation distributions on water levels on the Overijsselse Vecht

Massa, Joeri (2019) Effect of vegetation distributions on water levels on the Overijsselse Vecht.

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Abstract:In the floodplains of the Overijsselse Vecht various types of vegetation can be found. From the 'Vechtvisie' there is a demand for nature restoration and development on the one hand, while on the other hand flood safety must be guaranteed. Changing vegetation means changing the hydraulic resistance, which affects the discharge capacity and the water levels along the Overijsselse Vecht. From the perspective of Regional Water Authority (R.W.A.) Vechtstromen, there is a demand for an instrument that can calculate the impact of the spatial variation in vegetation on water levels. This instrument can be used to determine when and where natural development is permitted and when action is required from a flood point of view. In this study, an existing hydraulic one-dimensional (1D) model was extended to a 1D-2D model. This was done by removing the winter bed from the one-dimensional cross-sections and replacing it with a two-dimensional grid. In this grid it is possible to schematize the spatial variation in a roughness grid. For the winter bed within the study area (the management area of R.W.A. Vechtstromen), vegetation classes have been defined, which are linked to a hydraulic roughness. This hydraulic roughness is used as input for the roughness grid in the model. A sensitivity analysis has been performed for the hydraulic 1D-2D model. This showed that the model is more sensitive to the summer bed resistance than to the winter bed resistance. Furthermore, it appeared that the model, in terms of the winter bed resistance, is particularly sensitive to extremely lower roughness-values (-40%). Finally, it became clear that the downstream boundary condition, a Q-h relation, significantly affects the water levels in the final 10 km of the Overijsselse Vecht in the management area of R.W.A. Vechtstromen. As a result, the calculated water levels in this part of the model are less reliable. With the built 1D-2D model different vegetation scenarios have been simulated. Model runs with an extremely rough scenario and an extremely smooth scenario show that the bandwidth between the peak water levels is in the order of magnitude of 1 m. In addition, the peak of the discharge wave in the rough scenario arrives 21 hours later at the end of the study area. It also showed that the largest differences in water levels and flow velocities between the two scenarios occur in narrower parts of the winter bed. This shows that these narrower sections are more sensitive to roughness changes. In this research the effect of different vegetation data sources, namely the ecotopes map, LGN map and two vegetation maps based on satellite images (2017 and 2018), were compared. The LGN map Highlights • An existing hydraulic 1D model of the Overijsselse Vecht is extended to an 1D-2D model; • Different vegetation data sources are used to describe the floodplain vegetation, which results in considerably large differences in the calculated water levels; • Mixing classes can be a suitable alternative method to classify vegetation, however the mixing classes as defined in this research lead to a large overestimation (15-23 cm) of maximum water levels; • Vegetation perpendicular to the flow direction causes water levels to rise due to the blockage effect; • The discharge capacity of a river increases if wide paths with smooth vegetation are present; • The calculated water levels contain some uncertainties, but the model appears to be suitable for a qualitative exploration of the effects of vegetation distributions on the water levels. v shows the dominant vegetation on a lot, there is no variation within the lot and the less common vegetation types are neglected. As these are often the rougher vegetation species, a structurally lower water level is calculated compared to the model run with the ecotopes map (4-8 cm). The LGN map is not suitable as a data source for this model because of its classification method. There are also considerable differences between the model run with the ecotopes map and the model runs with satellite images, in particular the water levels in the model run with the satellite image of 2017 deviate (4-14 cm compared to the ecotopes map, 3-12 cm compared to the other satellite image). The deviation between the satellite image of 2018 and the ecotopes map is much lower (0-4 cm). Due to the significant differences between the two satellite images and its relative novelty, satellite images do not appear to be a suitable alternative to the ecotopes map at the moment. If the accuracy increases however, this could be a suitable alternative because of frequency of the satellite images. A method in which the lots in the floodplains of the Overijsselse Vecht are assigned a mixing class results in a large overestimation of the water level (15-23 cm). This has to do with the worst-case assumption of the roughness value of a mixing class, where the amount of rough vegetation is rounded up and the roughest type of vegetation (shrubs) is used in the calculation of the roughness mixing class. This roughness value often does not correspond to the actual roughness of a lot. It was also investigated how large the variations within the mixing classes can be, which showed that for the chosen vegetation distributions, the deviation in maximum water level is always within 5 cm. A higher water level only occurs when rough vegetation blocks the flow. This shows that if agreements are made with lot owners about the permitted amount of vegetation, the mixing class method can be used to determine the roughness of a lot, but also gives the owner the freedom to organise the lot. However, it is advisable to define other mixing classes than those used in this study. Different vegetation distributions have been studied with the 1D-2D model. This showed that two aspects must be taken into account if designing the winter bed: (1) the water level rises rapidly if vegetation blocks the flow and (2) the creation of wide flow paths results in higher flow velocities and lower water levels. Vegetation in the river bank does not result in higher maximum water levels as long as there is room for flow paths behind the bank. Rougher vegetation in storage parts of the floodplains barely affects the water levels. The 1D-2D model calculates higher water levels (15 and 50 cm) compared to the 1D model. This difference may be caused by underestimating physical processes (e.g. the lack of a storage part of the winter bed) and the lower winter bed roughness in the 1D model. Around the weirs, the 1D-2D shows a more realistic result, because there are no jumps in the water level. The difference between the two models quickly diminishes in the last kilometer of the area of R.W.A. Vechtstromen, because the water level in the 1D-2D model adapts to the lower water levels in the last part of the model (which is schematized in 1D). Due to the strong influence of the Q-h relation and the uncertainty in the measurement data used in the calibration, there is considerable uncertainty in the water level calculated by the 1D-2D model, which is larger in the downstream part (due to the Q-h relation), but difficult to quantify. It is recommended to validate and if necessary improve the quality of the measurement data. It is also recommended to locate the model boundary further downstream and to extend the 2D grid, so that the transition from 1D-2D to 1D does not take place in the study area. Although a quantitative analysis of the water levels is difficult due to the uncertainties in the model, the model appears to be suitable for a qualitative exploration of the effects of vegetation distributions in the floodplains on the water level of the Overijsselse Vecht.
Item Type:Essay (Master)
Faculty:ET: Engineering Technology
Subject:56 civil engineering
Programme:Construction Management and Engineering MSc (60337)
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