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Towards global scale compound flood risk modeling

  • 22 November, 2022
  • 9:45-11:15
  • VU University Amsterdam, Institute for Environmental Studies (IVM)
  • Philip Ward
  • H. Winsemius

Coastal deltas are prone to flooding due to their low elevation and dense population. Flooding in these areas can occur from several drivers, including pluvial (rainfall excess), fluvial (high river discharge), and coastal (storm surge and waves). However, floods can also occur or be exacerbated from interactions between these drivers, which by itself do not have to be extreme. If these drivers are statistically dependent, their joint likelihood might be misrepresented if dependence is not accounted for. At the global scale, however, flood risk models still analyze each flood driver in isolation. At the local scale, state-of-the-art hydrodynamic models have been developed for compound flooding, but these are not globally applicable. The overall aim of this thesis is therefore, to improve our understanding and modeling capabilities of compound flood risk anywhere globally. Specifically, the objectives are: 1) to identify deltas globally that are prone to compound flooding; and 2) to develop and apply a globally-applicable computational framework for compound flood risk modeling. To improve our understanding of compound flooding at the global scale, I coupled a global riverine flood model with a global tide and surge model to obtain continuously simulated water levels in 3,433 deltas globally. In 19.7% of the deltas, compound flooding is the dominant driver of extreme water levels. These deltas generally have larger surge extremes and are located in basins with faster discharge response to rainfall, and/or flat topography. If compound surge-discharge events are ignored, flood depths are significantly underestimated for 30.7 million out of a total of 332.0 million (9.3%) of the annual expected population exposed to flooding in deltas. To enable high-resolution local compound flood modeling anywhere in the world, I developed two tools: the Iterative Hydrography Upscaling (IHU) algorithm to upscale gridded flow direction data; and the Hydro Model Tools (HydroMT) package to enable transparent and reproducible model setups anywhere in the world. Based on the IHU algorithm, rivers in a coarse-resolution hydrological model are seamlessly connected with rivers in a high-resolution hydrodynamic compound flood model. With HydroMT, a ready-to-use model can be built from (global) datasets, such as topography, landuse and meteorological data, with a single configuration file that describes a sequence of workflows and the datasets used in each workflow. Using these tools, I developed a globally-applicable framework for compound flood hazard modeling. The framework is validated against two historical events in the Sofala province of Mozambique based on satellite-derived flood extents. Compare to a global flood model, the globally-applicable model generally has better skill. Furthermore, it results in more realistic flood depth maps due to better floodplain connectivity and provides a more holistic representation of flood processes as it includes direct coastal and pluvial flooding. However, the resolution of the globally-applicable model is not yet sufficient to capture fine grained channels, which play an important role in the drainage of precipitation, thereby, overestimating pluvial flooding. Finally, I extended the framework with an event-based approach for compound flood risk assessments from pluvial, fluvial, and coastal flood drivers and applied it to the same case-study. Here, rare events cause more impact if accounting for observed dependence between flood drivers compared to independence, e.g. 12% at the 100-year return period. The overall difference in risk of 0.55% in expected annual damage is however small as the physical interaction of drivers for frequent events is small. This thesis contributes to ongoing efforts to better understand and mitigate flood risks at the global scale. The coupled global models can be used to identify deltas prone to compound flooding, whereas the globally-applicable model framework can be used for comprehensive flood risk assessments in deltas.

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Dirk Eilander

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