Restoring Rivers
Integrating a renaturalised Maas river basin with the cultivated landscape to enhance climate resilience
E.C.J. de Quant (TU Delft - Architecture and the Built Environment)
Kristel Aalbers – Mentor (TU Delft - Architecture and the Built Environment)
N.M.J.D. Tillie – Mentor (TU Delft - Architecture and the Built Environment)
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Abstract
River basins are becoming increasingly vulnerable to climate change. The Maas (Meuse), a rain-fed river, depends on precipitation for its discharge. Changing rainfall patterns are expected to intensify floods due to wetter winters and summer storms, while also increasing water shortages in summer. Historically, the river naturally adapted to extreme changes in discharge, but the engineered, fixed-course river landscape has reduced its resilience and adaptability.
Renaturalisation of the river morphology could restore these natural processes. However, this requires a transformation of the surrounding ecological, agricultural, and urban landscape. Therefore, this thesis investigates how the cultivated landscape can be integrated into a more natural river system in the Noordelijke Maasvallei by 2100, under the most extreme dry and wet scenarios following a systemic design approach. A pattern language defines measures related to renaturalisation, ecology, agriculture, and urbanisation. The maximisation method then identifies the best spatial outcomes per theme as input for the integrated design.
The research led to an integrated design for the Noordelijke Maasvallei, where the Maas has space to flow and sedimentate naturally. This improves the water safety, water quality, and ecological resilience of the area towards 2100. The design applies measures from the pattern language across multiple scales, revealing different possibilities to enhance climate resilience for the river, ecological, agricultural, and urban landscapes. The systemic approach of this research allows for transferability to other contexts. Although this design prioritises renaturalisation and ecological resilience, the focus can be shifted by adjusting the inputs from the maximisation method. Furthermore, the pattern language provides a toolbox with measures that can be used separately and in different contexts. Overall, this thesis demonstrates the potential of restoring rivers to enhance climate resilience when the landscape adapts to the river, rather than forcing the river to fit human needs.