Efficiently designing sustainable urban drainage systems
Exploring trade-offs between 1D and 1D2D urban drainage models in sustainable flood-resilient design: A heuristic approach combining both models
J.S. Overbeek (TU Delft - Civil Engineering & Geosciences)
Job van der Werf – Mentor (TU Delft - Sanitary Engineering)
T.A. Bogaard – Graduation committee member (TU Delft - Surface and Groundwater Hydrology)
Patrick Smit – Graduation committee member (Witteveen+Bos)
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Abstract
Climate
change increases the likelihood of extreme rainfall events, while ongoing
urbanization leads to greater surface imperviousness. Together, these trends
result in more frequent and severe urban flooding. Sustainable Urban Drainage
Systems (SUDS) are implemented to enhance the resilience of urban drainage
infrastructure and mitigate urban flooding. Among the available modelling
approaches, coupling a one-dimensional (1D) sewer system model with a two-dimensional
(2D) surface model (1D2D) is considered the most accurate method to assess urban
flooding. However, the practical application of 1D2D models in the design of
SUDS is limited by their high computational requirements. In comparison, a 1D
urban drainage model demands significantly less computational power, allowing
for many more simulation iterations to be completed within the same timeframe. This
study investigates the trade-offs between 1D and 1D2D models in the design of
SUDS for flood prevention. It proposes a heuristic approach that integrates
both a 1D and a 1D2D model (method 1). This approach aims to leverage the speed
of the 1D model and the accuracy of the 1D2D model to optimize SUDS design. The
methodology was applied to an urban drainage model of Bloemendaal, the
Netherlands. To evaluate the efficiency of the proposed method, its results
were compared to those obtained using a second approach that relies solely on
the 1D2D model (method 2). Method 1 was more effective than method 2 in
reducing the number of flooded buildings. Specifically, method 1 achieved the
greatest reduction in areas affected by higher flood levels (>0.30 m), while
method 2 was more effective at decreasing the area exposed to lower flood levels
(>0.10 m). Method 1 may assist decision makers in selecting and implementing
SUDS more effectively for flood prevention, ultimately leading to more
resilient urban drainage systems. Future research could expand method 1 to
incorporate additional benefits of SUDS, enabling a multi-objective design
approach.