Regional water systems are being controlled to prevent flood events by different measures, such as water storage, weir management and vegetation maintenance. Vegetation maintenance has a significant effect on flood risk, because the hydraulic roughness decreases after cutting of
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Regional water systems are being controlled to prevent flood events by different measures, such as water storage, weir management and vegetation maintenance. Vegetation maintenance has a significant effect on flood risk, because the hydraulic roughness decreases after cutting of vegetation. Stream restoration is a project in regional water systems, where floodplains are constructed and weirs are removed to recover the ecological value of streams. In streams with floodplains the vegetation is relatively more important because of smaller water depth. Moreover, climate change increases the flood risk, which increases the urgency to investigate the vegetation maintenance strategy.
A vegetation maintenance strategy involves of a cutting frequency, how often and when the vegetation is cut, and a cutting intensity, the percentage of the cross-section that is cut. The aim of this research is to optimize the performance of the vegetation maintenance strategy by consideration of the aspects ‘flood risk’, ‘ecological effects’ and ‘maintenance costs’. The research answers the following question: How can risk-based vegetation maintenance strategy reduce flood risk in a cost-effective way in regional water systems with consideration of ecological effects?
A case study, a recently flooded stream in the south of the Netherlands, is used to answer the research question. The performances of nine selected vegetation maintenance strategies are investigated. Dimensionless performance indicators are designed for the three aspects to assess the total performance of each vegetation maintenance strategy. For the aspect ‘maintenance costs’, data from a water board is retrieved and the aspect ‘ecological effects’ is assessed by a literature study. For the aspect ‘flood risk’, several steps are conducted. The vegetation maintenance strategy is translated into a probability distribution function of roughness coefficients. To that end, use is made of roughness functions including vegetation growth curves and roughness coefficients of the stream. Stochastic modelling of the water level by the hydraulic model Sobek 1D is used to examine the influence of vegetation maintenance on the water levels. A consequence model, the Water Damage Estimator, translates the results of the stochastic modelling step into flood risk. The three performances of the aspects are combined into the total performance of the vegetation maintenance strategy.
The results of the case study show that the timing of cutting has the largest influence on the flood risk, followed by the cutting frequency. The cutting intensity has the smallest influence on the flood risk. For a high performance of ‘maintenance costs’, a low cutting frequency is necessary. For a high ecological value, pattern cutting and cutting in August is important. In conclusion, for streams with floodplains the optimal vegetation maintenance strategy is ‘cutting of the main channel and parts of the floodplains before summer’.
The total performance of the vegetation maintenance strategy can be further optimized by a dynamic maintenance strategy with ‘roughness’ of the stream as maintenance trigger. Hereby, the vegetation maintenance strategy is dependent on the current roughness in spring. Moreover, it is found that the conclusions of the case study can be applied on many other streams in the Netherlands.