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Floods continue to be the leading cause of economic damages and fatalities among natural disasters worldwide. As future climate and exposure changes are projected to intensify these damages, the need for more accurate and scalable flood risk models is rising. Over the past decade, macro-scale flood risk models have evolved from initial proof-of-concepts to indispensable tools for decision-making at global-, nationaland, increasingly, the local-level. This progress has been propelled by the advent of high-performance computing and the availability of global, space-based datasets. However, despite such advancements, these models are rarely validated and consistently fall short of the accuracy achieved by high-resolution local models. While capabilities have improved, significant gaps persist in understanding the behaviours of such macro-scale models, particularly their tendency to overestimate risk. This dissertation aims to address such gaps by examining the scale transfers inherent in the construction and application of coarse macroscale models. To achieve this, four studies are presented that, collectively, address exposure, hazard, and vulnerability components of risk affected by upscaling or downscaling.
The first study focuses on a type of downscaling where coarse flood hazard inundation grids are enhanced to a finer resolution. While such inundation downscaling has been employed in numerous global model chains, ours is the first study to focus specifically on this component, providing an evaluation of the state of the art and a novel algorithm. Findings demonstrate that our novel algorithm is eight times faster than existing methods, offers a slight improvement in accuracy, and generates more physically coherent flood maps in hydraulically challenging regions. When applied to a case study, the algorithm generated a 4m resolution inundation map from 30m hydrodynamic model outputs in 33 s, a 60-fold improvement in runtime with a 25% increase in RMSE compared with direct hydrodynamic modelling. All evaluated downscaling algorithms yielded better accuracy than the coarse hydrodynamic model when compared to observations, demonstrating similar limits of coarse hydrodynamic models reported by others. The substitution of downscaling into flood risk model chains, in place of high-resolution modelling, can drastically improve the lead time of impactbased forecasts and the efficiency of hazard map production. With downscaling, local regions could obtain high resolution local inundation maps by post-processing a global model without the need for expensive modelling or expertise.
The second study focuses on hazard aggregation and its implications for exposure, investigating implicit aggregations commonly used to intersect hazard grids with coarse exposure models. This research introduces a novel spatial classification framework to understand the effects of rescaling flood hazard grids to a coarser resolution. The study derives closed-form analytical solutions for the location and direction of bias from flood grid aggregation, showing that bias will always be present in regions near the edge of inundation. For example, inundation area will be positively biased when water depth grids are aggregated, while volume will be negatively biased when water elevation grids are aggregated. Extending the analysis to effects of hazard aggregation on building exposure, this study shows that exposure in regions at the edge of inundation are an order of magnitude more sensitive to aggregation errors than hazard alone. Among the two aggregation routines considered, averaging water surface elevation grids better preserved flood depths at buildings than averaging of water depth grids. The study provides the first mathematical proof and generalizeable treatment of flood hazard grid aggregation, demonstrating important mechanisms to help flood risk modellers understand and control model behaviour.
The final two studies focus on the aggregation of vulnerability models or flood damage functions, investigating the practice of applying per-asset functions to aggregate exposure models. Both studies extend Jensen’s inequality, a well-known 1906 mathematical proof, to demonstrate how the aggregation of flood damage functions leads to bias. Applying Jensen’s proof in this new context, results show that typically concave flood damage functions will introduce a positive bias (overestimation) when aggregated. This behaviour was further investigated with a simulation experiment including 2 million buildings in Germany, four global flood hazard simulations and three aggregation scenarios. The results show that positive aggregation bias is not distributed evenly in space, meaning some regions identified as “hot spots of risk” in assessments may in fact just be hot spots of aggregation bias. This study provides the first application of Jensen’s inequality to explain the overestimates reported elsewhere and advice for modellers to minimize such artifacts.
In total, this dissertation investigates the complex ways aggregation and disaggregation influence the behaviour of risk models, focusing on the scale-transfers underpinning macro-scale flood risk assessments. Extending a key finding of the flood hazard literature to the broader context of flood risk, this dissertation concludes that all else equal, coarse models overestimate risk. This dissertation goes beyond previous studies by providing mathematical proofs for how and where such bias emerges in aggregation routines, offering a mechanistic explanation for coarse model overestimates. It shows that this bias is spatially heterogeneous, necessitating a deep understanding of how rescaling may bias models to effectively reduce or communicate uncertainties. Further, the dissertation offers specific recommendations to help modellers minimize scale transfers in problematic regions. In conclusion, I argue that such aggregation errors are epistemic, stemming from choices in model structure, and therefore hold greater potential and impetus for study and mitigation. This deeper understanding of uncertainties is essential for improving macro-scale flood risk models and their effectiveness in equitable, holistic, and sustainable flood management.
Current climate warming is affecting arctic regions at a faster rate than the rest of the world. This has profound effects on permafrost that underlies most of the arctic land area. Permafrost thawing can lead to the liberation of considerable amounts of greenhouse gases as well as to significant changes in the geomorphology, hydrology, and ecology of the corresponding landscapes, which may in turn act as a positive feedback to the climate system. Vast areas of the east Siberian lowlands, which are underlain by permafrost of the Yedoma-type Ice Complex, are particularly sensitive to climate warming because of the high ice content of these permafrost deposits. Thermokarst and thermal erosion are two major types of permafrost degradation in periglacial landscapes. The associated landforms are prominent indicators of climate-induced environmental variations on the regional scale. Thermokarst lakes and basins (alasses) as well as thermo-erosional valleys are widely distributed in the coastal lowlands adjacent to the Laptev Sea. This thesis investigates the spatial distribution and morphometric properties of these degradational features to reconstruct their evolutionary conditions during the Holocene and to deduce information on the potential impact of future permafrost degradation under the projected climate warming. The methodological approach is a combination of remote sensing, geoinformation, and field investigations, which integrates analyses on local to regional spatial scales. Thermokarst and thermal erosion have affected the study region to a great extent. In the Ice Complex area of the Lena River Delta, thermokarst basins cover a much larger area than do present thermokarst lakes on Yedoma uplands (20.0 and 2.2 %, respectively), which indicates that the conditions for large-area thermokarst development were more suitable in the past. This is supported by the reconstruction of the development of an individual alas in the Lena River Delta, which reveals a prolonged phase of high thermokarst activity since the Pleistocene/Holocene transition that created a large and deep basin. After the drainage of the primary thermokarst lake during the mid-Holocene, permafrost aggradation and degradation have occurred in parallel and in shorter alternating stages within the alas, resulting in a complex thermokarst landscape. Though more dynamic than during the first phase, late Holocene thermokarst activity in the alas was not capable of degrading large portions of Pleistocene Ice Complex deposits and substantially altering the Yedoma relief. Further thermokarst development in existing alasses is restricted to thin layers of Holocene ice-rich alas sediments, because the Ice Complex deposits underneath the large primary thermokarst lakes have thawed completely and the underlying deposits are ice-poor fluvial sands. Thermokarst processes on undisturbed Yedoma uplands have the highest impact on the alteration of Ice Complex deposits, but will be limited to smaller areal extents in the future because of the reduced availability of large undisturbed upland surfaces with poor drainage. On Kurungnakh Island in the central Lena River Delta, the area of Yedoma uplands available for future thermokarst development amounts to only 33.7 %. The increasing proximity of newly developing thermokarst lakes on Yedoma uplands to existing degradational features and other topographic lows decreases the possibility for thermokarst lakes to reach large sizes before drainage occurs. Drainage of thermokarst lakes due to thermal erosion is common in the study region, but thermo-erosional valleys also provide water to thermokarst lakes and alasses. Besides these direct hydrological interactions between thermokarst and thermal erosion on the local scale, an interdependence between both processes exists on the regional scale. A regional analysis of extensive networks of thermo-erosional valleys in three lowland regions of the Laptev Sea with a total study area of 5,800 km² found that these features are more common in areas with higher slopes and relief gradients, whereas thermokarst development is more pronounced in flat lowlands with lower relief gradients. The combined results of this thesis highlight the need for comprehensive analyses of both, thermokarst and thermal erosion, in order to assess past and future impacts and feedbacks of the degradation of ice-rich permafrost on hydrology and climate of a certain region.