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Institute
- Institut für Umweltwissenschaften und Geographie (82) (remove)
Ice-wedge polygons are widespread periglacial features and influence landscape hydrology and carbon storage. The influence of climate and topography on polygon development is not entirely clear, however, giving high uncertainties to projections of permafrost development. We studied the mid- to late Holocene development of modern ice-wedge polygon sites to explore drivers of change and reasons for long-term stability. We analyzed organic carbon, total nitrogen, stable carbon isotopes, grain size composition and plant macrofossils in six cores from three polygons. We found that ail sites developed from aquatic to wetland conditions. In the mid-Holocene, shallow lakes and partly submerged ice-wedge polygons existed at the studied sites. An erosional hiatus of ca 5000 years followed, and ice-wedge polygons re-initiated within the last millennium. Ice-wedge melt and surface drying during the last century were linked to climatic warming. The influence of climate on ice-wedge polygon development was outweighed by geomorphology during most of the late Holocene. Recent warming, however, caused ice-wedge degradation at all sites. Our study showed that where waterlogged ground was maintained, low-centered polygons persisted for millennia. Ice-wedge melt and increased drainage through geomorphic disturbance, however, triggered conversion into high-centered polygons and may lead to self-enhancing degradation under continued warming.
For bare soil conditions, the most important process driving and initiating splash and interrill erosion is the detachment of soil particles via raindrop impact. The kinetic energy of a rainfall event is controlled by the drop size and fall velocity distribution, which is often directly or indirectly implemented in erosion models. Therefore, numerous theoretical functions have been developed for the estimation of rainfall kinetic energy from available rainfall intensity measurements. The aim of this study is to assess differences inherent in a wide number of kinetic energy-rainfall intensity (KE-I) relations and their role in soil erosion modelling. Therefore, 32 KE-I relations are compared against measured rainfall energies based on optical distrometer measurements carried out at five stations of two substantially different rainfall regimes. These allow for continuous high-resolution (1-min) direct measurements of rainfall kinetic energies from a detailed spectrum of measured drop sizes and corresponding fall velocities. To quantify the effect of different KE-I relations on sediment delivery, we apply the erosion model WATEM/SEDEM in an experimental setup to four catchments of NE-Germany. The distrometer data shows substantial differences between measured and theoretical models of drop size and fall velocity distributions. For low intensities the number of small drops is overestimated by the Marshall and Palmer (1948; MP) drop size distribution, while for high intensities the proportion of large drops is overestimated by the MP distribution. The distrometer measurements show a considerable proportion of large drops falling at slower velocities than predicted by the Gunn and Kinzer (1949) terminal velocity model. For almost all rainfall events at all stations, the KE-I relations predicted higher cumulative kinetic energy sums compared to the direct measurements of the optical distrometers. The different KE-I relations show individual characteristics over the course of rainfall intensity levels. Our results indicate a high sensitivity (up to a range from 10 to 27 t ha(-1)) of the simulated sediment delivery related to different KE-I relations. Hence, the uncertainty associated with KE-I relations for soil erosion modelling is of critical importance.
German football stadiums are well known for their atmosphere. It is often described as 'electrifying,' or 'cracking.' This article focuses on this atmosphere. Using a phenomenological approach, it explores how this emotionality can be understood and how geography matters while attending a match. Atmosphere in this context is conceptualized based on work by as a mood-charged space, neither object- nor subject-centered, but rather a medium of perception which cannot not exist. Based on qualitative research done in the home stadium of Hertha BSC in the German Bundesliga, this article shows that the bodily sensations experienced by spectators during a visit to the stadium are synchronized with events on the pitch and with the more or less imposing scenery. The analysis ofin situdiaries reveals that spectators experience a comprehensive sense of collectivity. The study presents evidence that the occurrence of these bodily sensations is strongly connected with different aspects of spatiality. This includes sensations of constriction and expansion within the body, an awareness of one's location within the stadium, the influence of the immediate surroundings and cognitive here/there and inside/outside distinctions.
Aerial and surface rivers
(2018)
The abundant evapotranspiration provided by the Amazon forests is an important component of the hydrological cycle, both regionally and globally. Since the last century, deforestation and expanding agricultural activities have been changing the ecosystem and its provision of moisture to the atmosphere. However, it remains uncertain how the ongoing land use change will influence rainfall, runoff, and water availability as findings from previous studies differ. Using moisture tracking experiments based on observational data, we provide a spatially detailed analysis recognizing potential teleconnection between source and sink regions of atmospheric moisture. We apply land use scenarios in upwind moisture sources and quantify the corresponding rainfall and runoff changes in downwind moisture sinks. We find spatially varying responses of water regimes to land use changes, which may explain the diverse results from previous studies. Parts of the Peruvian Amazon and western Bolivia are identified as the sink areas most sensitive to land use change in the Amazon and we highlight the current water stress by Amazonian land use change on these areas in terms of the water availability. Furthermore, we also identify the influential source areas where land use change may considerably reduce a given target sink's water reception (from our example of the Ucayali River basin outlet, rainfall by 5–12 % and runoff by 19–50 % according to scenarios). Sensitive sinks and influential sources are therefore suggested as hotspots for achieving sustainable land–water management.
This paper introduces a novel measure to assess similarity between event hydrographs. It is based on Cross Recurrence Plots and Recurrence Quantification Analysis which have recently gained attention in a range of disciplines when dealing with complex systems. The method attempts to quantify the event runoff dynamics and is based on the time delay embedded phase space representation of discharge hydrographs. A phase space trajectory is reconstructed from the event hydrograph, and pairs of hydrographs are compared to each other based on the distance of their phase space trajectories. Time delay embedding allows considering the multi-dimensional relationships between different points in time within the event. Hence, the temporal succession of discharge values is taken into account, such as the impact of the initial conditions on the runoff event. We provide an introduction to Cross Recurrence Plots and discuss their parameterization. An application example based on flood time series demonstrates how the method can be used to measure the similarity or dissimilarity of events, and how it can be used to detect events with rare runoff dynamics. It is argued that this methods provides a more comprehensive approach to quantify hydrograph similarity compared to conventional hydrological signatures.
Marine Isotope Stage 3 (MIS 3, 57-27 ka) was characterised by numerous rapid climate oscillations (i.e., Dansgaard-Oeschger (D/O-) events), which are reflected in various climate archives. So far, MIS 3 speleothem records from central Europe have mainly been restricted to caves located beneath temperate Alpine glaciers or close to the Atlantic Ocean. Thus, MIS 3 seemed to be too cold and dry to enable speleothem growth north of the Alps in central Europe. Here we present a new speleothem record from Bunker Cave, Germany, which shows two distinct growth phases from 52.0 (+0.8, -0.5) to 50.9 (+0.6, -1.3) ka and 473 (+1.0, -0.6) to 42.8 (+/- 0.9) ka, rejecting this hypothesis. These two growth phases potentially correspond to the two warmest and most humid phases in central Europe during MIS 3, which is confirmed by pollen data from the nearby Eifel. The hiatus separating the two phases is associated with Heinrich stadial 5 (HS 5), although the growth stop precedes the onset of HS 5. The first growth phase is characterised by a fast growth rate, and Mg concentrations and Sr isotope data suggest high infiltration and the presence of soil cover above the cave. The second growth phase was characterised by drier, but still favourable conditions for speleothem growth. During this phase, the delta C-13 values show a significant decrease associated with D/O-event 12. The timing of this shift is in agreement with other MIS 3 speleothem data from Europe and Greenland ice core data. (C) 2018 Elsevier Ltd. All rights reserved.
The management of water resources in a river basin experiencing the expansion of agricultural activities requires a proper understanding of impacts on its hydrologic cycle. This study focused on the analysis of impacts of infield rainwater harvesting (IRWH) and future agricultural expansion as land and water uses change (LWUC) on the hydrologic cycle in the Wami River basin (Tanzania) using the Soil and Water Assessment Tool (SWAT). In the SWAT model, IRWH was implemented by fragmenting rainwater harvesting hydrological response units (HRUs) from cropland HRUs and assigning them as potholes for rainwater impoundment. LWUC was implemented by customizing land cover types and their corresponding model parameters in all original HRUs, and introducing projected water uses in the model. The study thus demonstrated the successful modelling of IRWH and land use change in the SWAT model using HRU fragmentation and customization approaches, respectively. The results indicated that IRWH applications in croplands led to a large increase in evapotranspiration (ET) and the soil water content, and a decrease in percolation, especially in the dry years. However, the average annual streamflow showed negligible changes when IRWH was implemented, even in 50% of current low-coverage croplands in the river basin. Thus, IRWH applications in the river basin are recommended. The results also indicated that LWUC caused huge changes in ET, the soil water content, percolation and the streamflow from the river basin. The average annual streamflow was predicted to decrease by 26% due to LWUC. However, land use change alone without projected water uses was predicted to cause a minor decrease of about 1% in the average annual streamflow. Therefore, further studies on the eco-hydrology of the river basin under various water use scenarios are recommended prior to the expansion of agricultural areas.
Inland salt meadows are particularly valuable ecosystems, because they support a variety of salt-adapted species (halophytes). They can be found throughout Europe; including the peatlands of the glacial lowlands in northeast Germany. These German ecosystems have been seriously damaged through drainage. To assess and ultimately limit the damages, temporal monitoring of soil salinity is essential, which can be conducted by geoelectrical techniques that measure the soil electrical conductivity. However, there is limited knowledge on how to interpret electrical conductivity surveys of peaty salt meadows. In this study, temporal and spatial monitoring of dissolved salts was conducted in saline peatland soils using different geoelectrical techniques at different scales (1D: conductivity probe, 2D: conductivity cross-sections). Cores and soil samples were taken to validate the geoelectrical surveys. Although the influence of peat on bulk conductivity is large, the seasonal dynamics of dissolved salts within the soil profile could be monitored by repeated geoelectrical measurements. A close correlation is observed between conductivity (similar to salinity) at different depths and temperature, precipitation and corresponding groundwater level. The conductivity distribution between top- and subsoil during the growing season reflected the leaching of dissolved salts by precipitation and the capillary rise of dissolved salts by increasing temperature (similar to evaporation). Groundwater levels below 0.38 cm resulted in very low conductivities in the topsoil, which is presumably due to limited soil moisture and thus precipitation of salts. Therefore, to prevent the disappearance of dissolved salts from the rooting zone, which are essential for the halophytes, groundwater levels should be adjusted to maintain depths of between 20 and 35 cm. Lower groundwater levels will lead to the loss of dissolved salts from the rooting zone and higher levels to increasing dilution with fresh rainwater. The easy-to-handle conductivity probe is an appropriate tool for salinity monitoring. Using this probe with regressions adjusted for sandy and organic substrates (peat and organic gyttja) additional influences on bulk conductivity (e.g. cation exchange capacity, water content) can be compensated for and the correlation between salinity and electrical conductivity is high.
Ferruginous (Fe-rich, SO4-poor) conditions are generally restricted to freshwater sediments on Earth today, but were likely widespread during the Archean and Proterozoic Eons. Lake Towuti, Indonesia, is a large ferruginous lake that likely hosts geochemical processes analogous to those that operated in the ferruginous Archean ocean. The metabolic potential of microbial communities and related biogeochemical cycling under such conditions remain largely unknown. We combined geochemical measurements (pore water chemistry, sulfate reduction rates) with metagenomics to link metabolic potential with geochemical processes in the upper 50 cm of sediment. Microbial diversity and quantities of genes for dissimilatory sulfate reduction (dsrAB) and methanogenesis (mcrA) decrease with increasing depth, as do rates of potential sulfate reduction. The presence of taxa affiliated with known iron- and sulfate-reducers implies potential use of ferric iron and sulfate as electron acceptors. Pore-water concentrations of acetate imply active production through fermentation. Fermentation likely provides substrates for respiration with iron and sulfate as electron donors and for methanogens that were detected throughout the core. The presence of ANME-1 16S and mcrA genes suggests potential for anaerobic methane oxidation. Overall our data suggest that microbial community metabolism in anoxic ferruginous sediments support coupled Fe, S and C biogeochemical cycling.
Climate change, along with socio-economic development, will increase the economic impacts of floods. While the factors that influence flood risk to private property have been extensively studied, the risk that natural disasters pose to public infrastructure and the resulting implications on public sector budgets, have received less attention. We address this gap by developing a two-staged model framework, which first assesses the flood risk to public infrastructure in Austria. Combining exposure and vulnerability information at the building level with inundation maps, we project an increase in riverine flood damage, which progressively burdens public budgets. Second, the risk estimates are integrated into an insurance model, which analyzes three different compensation arrangements in terms of the monetary burden they place on future governments' budgets and the respective volatility of payments. Formalized insurance compensation arrangements offer incentives for risk reduction measures, which lower the burden on public budgets by reducing the vulnerability of buildings that are exposed to flooding. They also significantly reduce the volatility of payments and thereby improve the predictability of flood damage expenditures. These features indicate that more formalized insurance arrangements are an improvement over the purely public compensation arrangement currently in place in Austria.
The Maghreb region (from Tunisia to Gibraltar) is a key area in the western Mediterranean to study the active tectonics and stress pattern across the Africa-Eurasia convergent plate boundary. In the present study, we compile comprehensive data set of well-constrained crustal stress indicators (from single focal mechanism solutions, formal inversion of focal mechanism solutions, and young geologic fault slip data) based on our and published data analyses. Stress inversion of focal mechanisms reveals a first-order transpression-compatible stress field and a second-order spatial variation of tectonic regime across the Maghreb region, with a relatively stable S-Hmax orientation from east to west. Therefore, the present-day active contraction of the western Africa-Eurasia plate boundary is accommodated by (1) E-W strike-slip faulting with reverse component along the Eastern Tell and Saharan-Tunisian Atlas, (2) a predominantly NE trending thrust faulting with strike-slip component in the Western Tell part, and (3) a conjugate strike-slip faulting regime with normal component in the Alboran/Rif domain. This spatial variation of the present-day stress field and faulting regime is relatively in agreement with the inferred stress information from neotectonic features. According to existing and newly proposed structural models, we highlight the role of main geometrically complex shear zones in the present-day stress pattern of the Maghreb region. Then, different geometries of these major inherited strike-slip faults and its related fractures (V-shaped conjugate fractures, horsetail splays faults, and Riedel fractures) impose their component on the second- and third-order stress regimes. Neotectonic and smoothed present-day stress map (mean S-Hmax orientation) reveal that plate boundary forces acting on the Africa-Eurasia collisional plates control the long wavelength of the stress field pattern in the Maghreb. The current tectonic deformations and the upper crustal stress field in the study area are governed by the interplay of the oblique plate convergence (i.e., Africa-Eurasia), lithosphere-mantle interaction, and preexisting tectonic weakness zones.
The evaluation and verification of landscape evolution models (LEMs) has long been limited by a lack of suitable observational data and statistical measures which can fully capture the complexity of landscape changes. This lack of data limits the use of objective function based evaluation prolific in other modelling fields, and restricts the application of sensitivity analyses in the models and the consequent assessment of model uncertainties. To overcome this deficiency, a novel model function approach has been developed, with each model function representing an aspect of model behaviour, which allows for the application of sensitivity analyses. The model function approach is used to assess the relative sensitivity of the CAESAR-Lisflood LEM to a set of model parameters by applying the Morris method sensitivity analysis for two contrasting catchments. The test revealed that the model was most sensitive to the choice of the sediment transport formula for both catchments, and that each parameter influenced model behaviours differently, with model functions relating to internal geomorphic changes responding in a different way to those relating to the sediment yields from the catchment outlet. The model functions proved useful for providing a way of evaluating the sensitivity of LEMs in the absence of data and methods for an objective function approach.
The evaluation and verification of landscape evolution models (LEMs) has long been limited by a lack of suitable observational data and statistical measures which can fully capture the complexity of landscape changes. This lack of data limits the use of objective function based evaluation prolific in other modelling fields, and restricts the application of sensitivity analyses in the models and the consequent assessment of model uncertainties. To overcome this deficiency, a novel model function approach has been developed, with each model function representing an aspect of model behaviour, which allows for the application of sensitivity analyses. The model function approach is used to assess the relative sensitivity of the CAESAR-Lisflood LEM to a set of model parameters by applying the Morris method sensitivity analysis for two contrasting catchments. The test revealed that the model was most sensitive to the choice of the sediment transport formula for both catchments, and that each parameter influenced model behaviours differently, with model functions relating to internal geomorphic changes responding in a different way to those relating to the sediment yields from the catchment outlet. The model functions proved useful for providing a way of evaluating the sensitivity of LEMs in the absence of data and methods for an objective function approach.
Climate change perception
(2018)
Climate change and variability have created widespread risks for farmers’ food and livelihood security in the Himalayas. However, the extent of impacts experienced and perceived by farmers varies, as there is substantial diversity in the demographic, social, and economic conditions. Therefore, it is essential to understand how farmers with different resource-endowment and household characteristics perceive climatic risks. This study aims to analyze how farmer types perceive climate change processes and its impacts to gain insight into locally differentiated concerns by farming communities. The present study is based in the Uttarakhand state of Indian Western Himalayas. We examine farmer perceptions of climate change and how perceived impacts differ across farmer types. Primary household interviews with farming households (n = 241) were done in Chakrata and Bhikiyasian tehsil in Uttarakhand, India. In addition, annual and seasonal patterns of historical data of temperature (1951–2013) and precipitation (1901–2013) were analyzed to estimate trends and validate farmers’ perception. Using statistical methods farmer typology was constructed, and five unique farmer types are identified. Majority of respondents across all farmer types noticed a decrease in summer and winter precipitation and an increase in summer temperature. Whereas the perceptions of impacts of climate change diverged across farmer types, as specific farmer types exclusively experienced few impacts. Impact of climatic risks on household food security and income was significantly perceived stronger by low-resource-endowed subsistence farmers, whereas the landless farmer type exclusively felt impacts on the communities social bond. This deeper understanding of the differentiated perception of impacts has strong implications for agricultural and development policymaking, highlighting the need for providing flexible adaptation options rather than specific solutions to avoid inequalities in fulfilling the needs of the heterogeneous farming communities.
Measurements of root-zone soil moisture across spatial scales of tens to thousands of meters have been a challenge for many decades. The mobile application of Cosmic Ray Neutron Sensing (CRNS) is a promising approach to measure field soil moisture noninvasively by surveying large regions with a ground-based vehicle. Recently, concerns have been raised about a potentially biasing influence of local structures and roads. We employed neutron transport simulations and dedicated experiments to quantify the influence of different road types on the CRNS measurement. We found that roads introduce a substantial bias in the CRNS estimation of field soil moisture compared to off-road scenarios. However, this effect becomes insignificant at distances beyond a few meters from the road. Neutron measurements on the road could overestimate the field value by up to 40 % depending on road material, width, and the surrounding field water content. The bias could be largely removed with an analytical correction function that accounts for these parameters. Additionally, an empirical approach is proposed that can be used without prior knowledge of field soil moisture. Tests at different study sites demonstrated good agreement between road-effect corrected measurements and field soil moisture observations. However, if knowledge about the road characteristics is missing, measurements on the road could substantially reduce the accuracy of this method. Our results constitute a practical advancement of the mobile CRNS methodology, which is important for providing unbiased estimates of field-scale soil moisture to support applications in hydrology, remote sensing, and agriculture. Plain Language Summary Measurements of root-zone soil moisture across spatial scales of tens to thousands of meters have been a challenge for many decades. The mobile application of Cosmic Ray Neutron Sensing (CRNS) is a promising approach to measure field soil moisture noninvasively by surveying large regions with a ground-based vehicle. Recently, concerns have been raised about a potentially biasing influence of roads. We employed physics simulations and dedicated experiments to quantify the influence of different road types on the CRNS measurement. We found that the presence of roads biased the CRNS estimation of field soil moisture compared to nonroad scenarios. Neutron measurements could overestimate the field value by up to 40 % depending on road material, width, surrounding field water content, and distance from the road. We proposed a correction function that successfully removed this bias and works even without prior knowledge of field soil moisture. Tests at different study sites demonstrated good agreement between corrected measurements and other field soil moisture observations. Our results constitute a practical advancement of the mobile CRNS methodology, which is important for providing unbiased estimates of field-scale soil moisture to support applications in hydrology, remote sensing, and agriculture.
State variables in lake ecosystems are subject to processes that act on different time scales. The relative importance of each of these processes changes over time, e.g., due to varying constraints of physical, biological, and biogeochemical processes. Correspondingly, continuous automatic measurements at high temporal resolution often reveal intriguing patterns that can rarely be directly ascribed to single processes. In light of the rather complex interplay of such processes, disentangling them requires more powerful methods than researchers have applied up to this point. For this reason, we tested the potential of wavelet coherence, based on the assumption that different processes result in correlations between different variables, on different time scales and during different time windows across the seasons. The approach was tested on a set of multivariate hourly data measured between the onset of an ice cover and a cyanobacterial summer bloom in the year 2009 in the Muggelsee, a polymictic eutrophic lake. We found that processes such as photosynthesis and respiration, the growth and decay of phytoplankton biomass, dynamics in the CO2-carbonate system, wind-induced resuspension of particles, and vertical mixing all occasionally served as dominant drivers of the variability in our data. We therefore conclude that high-resolution data and a method capable of analyzing time series in both the time and the frequency domain can help to enhance our understanding of the time scales and processes responsible for the high variability in driver variables and response variables, which in turn can lay the ground for mechanistic analyses.
We applied coarse spectral analysis to more than 2 decades of daily near-surface water temperature (WT) measurements from Muggelsee, a shallow polymictic lake in Germany, to systematically characterize patterns in WT variability from daily to yearly temporal scales. Comparison of WT with local air temperature indicates that the WT variability patterns are likely attributable to both meteorological forcing and internal lake dynamics. We identified seasonal patterns of WT variability and showed that WT variability increases with increasing Schmidt stability, decreasing Lake number and decreasing ice cover duration, and is higher near the shore than in open water. We introduced the slope of WT spectra as an indicator for the degree of lake mixing to help explain the identified temporal and spatial scales of WT variability. The explanatory power of this indicator in other lakes with different mixing regimes remains to be established.
Whereas ecosystem service research is increasingly being promoted in science and policy, the utilisation of ecosystem services knowledge remains largely underexplored for regional ecosystem management. To overcome the mere generation of knowledge and contribute to decision-making, scientists are facing the challenge of articulating specific implications of the ecosystem service approach for practical land use management. In this contribution, we compare the results of participatory mapping of ecosystem services with the existing management plan for the Pentland Hills Regional Park (Scotland, UK) to inform its future management plan. By conducting participatory mapping in a workshop with key stakeholders (n = 20), we identify hotspots of ecosystem services and the landscape features underpinning such hotspots. We then analyse to what extent these landscape features are the focus of the current management plan. We found a clear mismatch between the key landscape features underpinning the provision of ecosystem services and the management strategy suggested. Our findings allow for a better understanding of the required focus of future land use management to account for ecosystem services.
The paleo-Loppa High in the SW Barents Sea is a ridge structure, which developed during the late Paleozoic when the earliest phase of the Atlantic rifting between Greenland and Norway occurred. The southwest of the Barents Sea, located at the northern margin of Pangaea during the Carboniferous and Permian, was characterized by a structural style of half-graben geometries. The northward drift of the northern Pangaea triggered changes in regional climatic conditions that are reflected in the preserved sedimentary deposits. 2D/3D seismic combined with well and core data were used to define depositional seismic sequences and to understand the stratigraphic evolution of the paleo-Loppa High during the late Paleozoic. Based on the geometry of the defined seismic sequences and the character of observed sedimentary facies, a paleogeographic reconstruction of the key stages in the paleo-Loppa High evolution is also proposed and discussed in relation to local tectonic, global sea-level oscillations, and climatic changes. A total of seven seismic sequences, ranging from clastic-dominated to transitional elastic-carbonate sedimentation followed by an evaporitic drawdown phase, then shifting to carbonate-dominated sequences and finally capped by silica- and chert-dominated deposits, have been defined and represent the infill evolution of the paleo-Loppa High. Tectonics processes associated with the rifting are the principal controls in the 3-D morphology of the defined sequences. Sea-level fluctuations and climate changes have modified the biotic evolution and were responsible of the small-scale features inside each sequence. A renewed interest, in the study of the late Paleozoic sedimentary deposits of the paleo-Loppa High, has been manifested due to the recent discoveries of hydrocarbons in the Gohta and Alta prospects.
Today, more than half of the world’s population lives in urban areas. With a high density of population and assets, urban areas are not only the economic, cultural and social hubs of every society, they are also highly susceptible to natural disasters. As a consequence of rising sea levels and an expected increase in extreme weather events caused by a changing climate in combination with growing cities, flooding is an increasing threat to many urban agglomerations around the globe.
To mitigate the destructive consequences of flooding, appropriate risk management and adaptation strategies are required. So far, flood risk management in urban areas is almost exclusively focused on managing river and coastal flooding. Often overlooked is the risk from small-scale rainfall-triggered flooding, where the rainfall intensity of rainstorms exceeds the capacity of urban drainage systems, leading to immediate flooding. Referred to as pluvial flooding, this flood type exclusive to urban areas has caused severe losses in cities around the world. Without further intervention, losses from pluvial flooding are expected to increase in many urban areas due to an increase of impervious surfaces compounded with an aging drainage infrastructure and a projected increase in heavy precipitation events. While this requires the integration of pluvial flood risk into risk management plans, so far little is known about the adverse consequences of pluvial flooding due to a lack of both detailed data sets and studies on pluvial flood impacts. As a consequence, methods for reliably estimating pluvial flood losses, needed for pluvial flood risk assessment, are still missing.
Therefore, this thesis investigates how pluvial flood losses to private households can be reliably estimated, based on an improved understanding of the drivers of pluvial flood loss. For this purpose, detailed data from pluvial flood-affected households was collected through structured telephone- and web-surveys following pluvial flood events in Germany and the Netherlands.
Pluvial flood losses to households are the result of complex interactions between impact characteristics such as the water depth and a household’s resistance as determined by its risk awareness, preparedness, emergency response, building properties and other influencing factors. Both exploratory analysis and machine-learning approaches were used to analyze differences in resistance and impacts between households and their effects on the resulting losses. The comparison of case studies showed that the awareness around pluvial flooding among private households is quite low. Low awareness not only challenges the effective dissemination of early warnings, but was also found to influence the implementation of private precautionary measures. The latter were predominately implemented by households with previous experience of pluvial flooding. Even cases where previous flood events affected a different part of the same city did not lead to an increase in preparedness of the surveyed households, highlighting the need to account for small-scale variability in both impact and resistance parameters when assessing pluvial flood risk.
While it was concluded that the combination of low awareness, ineffective early warning and the fact that only a minority of buildings were adapted to pluvial flooding impaired the coping capacities of private households, the often low water levels still enabled households to mitigate or even prevent losses through a timely and effective emergency response.
These findings were confirmed by the detection of loss-influencing variables, showing that cases in which households were able to prevent any loss to the building structure are predominately explained by resistance variables such as the household’s risk awareness, while the degree of loss is mainly explained by impact variables.
Based on the important loss-influencing variables detected, different flood loss models were developed. Similar to flood loss models for river floods, the empirical data from the preceding data collection was used to train flood loss models describing the relationship between impact and resistance parameters and the resulting loss to building structures. Different approaches were adapted from river flood loss models using both models with the water depth as only predictor for building structure loss and models incorporating additional variables from the preceding variable detection routine.
The high predictive errors of all compared models showed that point predictions are not suitable for estimating losses on the building level, as they severely impair the reliability of the estimates. For that reason, a new probabilistic framework based on Bayesian inference was introduced that is able to provide predictive distributions instead of single loss estimates. These distributions not only give a range of probable losses, they also provide information on how likely a specific loss value is, representing the uncertainty in the loss estimate.
Using probabilistic loss models, it was found that the certainty and reliability of a loss estimate on the building level is not only determined by the use of additional predictors as shown in previous studies, but also by the choice of response distribution defining the shape of the predictive distribution. Here, a mix between a beta and a Bernoulli distribution to account for households that are able to prevent losses to their building’s structure was found to provide significantly more certain and reliable estimates than previous approaches using Gaussian or non-parametric response distributions.
The successful model transfer and post-event application to estimate building structure loss in Houston, TX, caused by pluvial flooding during Hurricane Harvey confirmed previous findings, and demonstrated the potential of the newly developed multi-variable beta model for future risk assessments. The highly detailed input data set constructed from openly available data sources containing over 304,000 affected buildings in Harris County further showed the potential of data-driven, building-level loss models for pluvial flood risk assessment.
In conclusion, pluvial flood losses to private households are the result of complex interactions between impact and resistance variables, which should be represented in loss models. The local occurrence of pluvial floods requires loss estimates on high spatial resolutions, i.e. on the building level, where losses are variable and uncertainties are high.
Therefore, probabilistic loss estimates describing the uncertainty of the estimate should be used instead of point predictions. While the performance of probabilistic models on the building level are mainly driven by the choice of response distribution, multi-variable models are recommended for two reasons:
First, additional resistance variables improve the detection of cases in which households were able to prevent structural losses.
Second, the added variability of additional predictors provides a better representation of the uncertainties when loss estimates from multiple buildings are aggregated.
This leads to the conclusion that data-driven probabilistic loss models on the building level allow for a reliable loss estimation at an unprecedented level of detail, with a consistent quantification of uncertainties on all aggregation levels. This makes the presented approach suitable for a wide range of applications, from decision support in spatial planning to impact- based early warning systems.