The influence of land subsidence on pluvial flooding in Rotterdam

Abstract

In the Netherlands, the Delta Programme aspires to adjust spatial planning climate-proof and water-resilient, in order to be prepared for extreme weather in 2050. To achieve this ambition, municipalities, provinces, regional water authorities and central governments conduct stress tests to map out the vulnerabilities in their areas of authority by no later than 2019. The stress tests comprise four themes: pluvial flooding, drought, heat and floods. In addition, the Delta Programme 2019 acknowledges the mitigation of and adaptation to land subsidence as an important tasking. The municipality of Rotterdam faces the challenge of adding land subsidence as stress test theme and assessing its influence on pluvial flooding. Contrary to the stress test pluvial flooding, no consended methodology exist on how to map out vulnerabilities concerning land subsidence. In addition, only few studies have numerically investigated the spatial-temporal effect of land subsidence on pluvial flooding in urban areas. However, the advent of techniques to measure ground level (LiDAR) and land subsidence (InSAR) and advances in high resolution flood modelling (3Di) enable the numerical modelling of urban pluvial flooding influenced by land subsidence. This research explores the investigation of the influence of land subsidence on pluvial flooding in Rotterdam by supplementing the conducted stress test pluvial flooding with a land subsidence assessment. The conducted stress test pluvial flooding in Rotterdam is based on a 3Di-simulation of standardised rain events, based on a DEM 2016.

To asses the current influence of land subsidence on pluvial flooding, a Digital Elevation Model (DEM) that approximates the sub-neighbourhood Tuinenhoven at design level is created and used as 3Di-input. When comparing 3Di-results based on this design DEM to the stress test pluvial flooding, it becomes clear that the total volume of water during extreme rainfall stored on the streets is not affected by land subsidence. The bathymetry of the DEM does affect the water's distribution however. The Tuinenhoven case-study demonstrates that currently land subsidence increases the severity of the impact of pluvial flooding but that the main cause of pluvial flooding during extreme rainfall is the limited capacity of the drainage system.

Land subsidence in Rotterdam complex. The conducted land subsidence analysis based on an InSAR data-set supports this complexity. It illustrates that the subsidence behaviour of Rotterdam is influenced by foundation type, land use classification, the presence of dredge in the anthropogenic layer and top soil type. This respectively indicates the occurrence of pole rot and shallow foundations, anthropogenic compression and compaction of shallow soft layers caused by loading, landfill subsidence as a result of land fillings that contain dredging spoil and consolidation of the Holocene clay layer as a result of drainage. However, the land subsidence analysis failed to identify location-specific dominant land subsidence processes. This failure was primarily caused by the limitation to only one linear subsidence rate between 2009 and 2014 per point. To demonstrate how land subsidence can be translated to pluvial flooding based on a land subsidence analysis, land use classification was selected as the most dominant influencing factor and used in a linear land subsidence prognosis until 2030. The linear assumptions largely obstructs results to be interpreted location-specific.

The IJsselmonde case-study shows that land subsidence is expected to decrease the passability of roads and decrease the risk per building in the future. These decreases are caused by the fact that roads relatively subside fast and buildings relatively slow. The biggest influence on the risk per building classification is the assumed threshold value per building. Simulated road maintenance results in an increase of the passability of roads and an increase of buildings at risk of water nuisance. The loss of the water-storing function of the road after reconstruction increases the water levels in gardens and puts buildings at an increasing risk.

In conclusion, the most challenging part of investigating the influence of land subsidence on pluvial flooding is the crucial identification of the different occurring land subsidence processes. It is demonstrated that the possibilities with InSAR-data are promising, when used with sufficient competency, although the available InSAR data should be divided in shorter intervals to detect the subsidence rate trends. Land subsidence rate trends are crucial in the identification of land subsidence processes and assessing influences like groundwater variations and increased loading due to maintenance or construction works. When the land subsidence analysis is improved, so will the land subsidence and threshold height per building prognosis. When the relative prognosed decrease of the threshold value per building is improved, it can be quickly assessed whether buildings classified at risk in the stress test pluvial flooding are at future increasing risk during extreme rainfall, without conducting a full 3Di-simulation.