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- Institut für Umweltwissenschaften und Geographie (68) (remove)
The innovative dual-purpose chicken approach aims at contributing to the transition towards sustainable poultry production by avoiding the culling of male chickens. To successfully integrate sustainability aspects into innovation, goal congruency among actors and clearly communicating the added value within the actor network and to consumers is needed. The challenge of identifying common sustainability goals calls for decision support tools. The objectives of our research were to investigate whether the tool could assist in improving communication and marketing with respect to sustainability and optimizing the value chain organization. Three actor groups participated in the tool application, in which quantitative and qualitative data were collected. The results showed that there were manifold sustainability goals within the innovation network, but only some goals overlapped, and the perception of their implementation also diverged. While easily marketable goals such as ‘animal welfare’ were perceived as being largely implemented, economic goals were prioritized less often, and the implementation was perceived as being rather low. By visualizing congruencies and differences in the goals, the tool helped identify fields of action, such as improved information flows and prompted thinking processes. We conclude that the tool is useful for managing complex decision processes with several actors involved.
The Fram Strait is an area with a relatively low and irregular distribution of diatom microfossils in surface sediments, and thus microfossil records are scarce, rarely exceed the Holocene, and contain sparse information about past richness and taxonomic composition. These attributes make the Fram Strait an ideal study site to test the utility of sedimentary ancient DNA (sedaDNA) metabarcoding. Amplifying a short, partial rbcL marker from samples of sediment core MSM05/5-712-2 resulted in 95.7 % of our sequences being assigned to diatoms across 18 different families, with 38.6 % of them being resolved to species and 25.8 % to genus level. Independent replicates show a high similarity of PCR products, especially in the oldest samples. Diatom sedaDNA richness is highest in the Late Weichselian and lowest in Mid- and Late Holocene samples. Taxonomic composition is dominated by cold-water and sea-ice-associated diatoms and suggests several reorganisations – after the Last Glacial Maximum, after the Younger Dryas, and after the Early and after the Mid-Holocene. Different sequences assigned to, amongst others, Chaetoceros socialis indicate the detectability of intra-specific diversity using sedaDNA. We detect no clear pattern between our diatom sedaDNA record and the previously published IP25 record of this core, although proportions of pennate diatoms increase with higher IP25 concentrations and proportions of Nitzschia cf. frigida exceeding 2 % of the assemblage point towards past sea-ice presence.
Predictability of hydrologic response at the plot and catchment scales: Role of initial conditions
(2004)
This paper examines the effect of uncertain initial soil moisture on hydrologic response at the plot scale (1 m2) and the catchment scale (3.6 km2) in the presence of threshold transitions between matrix and preferential flow. We adopt the concepts of microstates and macrostates from statistical mechanics. The microstates are the detailed patterns of initial soil moisture that are inherently unknown, while the macrostates are specified by the statistical distributions of initial soil moisture that can be derived from the measurements typically available in field experiments. We use a physically based model and ensure that it closely represents the processes in the Weiherbach catchment, Germany. We then use the model to generate hydrologic response to hypothetical irrigation events and rainfall events for multiple realizations of initial soil moisture microstates that are all consistent with the same macrostate. As the measures of uncertainty at the plot scale we use the coefficient of variation and the scaled range of simulated vertical bromide transport distances between realizations. At the catchment scale we use similar statistics derived from simulated flood peak discharges. The simulations indicate that at both scales the predictability depends on the average initial soil moisture state and is at a minimum around the soil moisture value where the transition from matrix to macropore flow occurs. The predictability increases with rainfall intensity. The predictability increases with scale with maximum absolute errors of 90 and 32% at the plot scale and the catchment scale, respectively. It is argued that even if we assume perfect knowledge on the processes, the level of detail with which one can measure the initial conditions along with the nonlinearity of the system will set limits to the repeatability of experiments and limits to the predictability of models at the plot and catchment scales.
An exceptionally strong stationary planetary wave with Zonal Wavenumber 1 led to a sudden stratospheric warming (SSW) in the Southern Hemisphere in September 2019. Ionospheric data from European Space Agency's Swarm satellite constellation mission show prominent 6-day variations in the dayside low-latitude region at this time, which can be attributed to forcing from the middle atmosphere by the Rossby normal mode "quasi-6-day wave" (Q6DW). Geopotential height measurements by the Microwave Limb Sounder aboard National Aeronautics and Space Administration's Aura satellite reveal a burst of global Q6DW activity in the mesosphere and lower thermosphere during the SSW, which is one of the strongest in the record. The Q6DW is apparently generated in the polar stratosphere at 30-40 km, where the atmosphere is unstable due to strong vertical wind shear connected with planetary wave breaking. These results suggest that an Antarctic SSW can lead to ionospheric variability through wave forcing from the middle atmosphere.
Plain Language Summary: A sudden stratospheric warming (SSW) is an extreme wintertime polar meteorological phenomenon occurring mostly over the Arctic region. Studies have shown that Arctic SSW can influence the entire atmosphere. In September 2019, a rare SSW event occurred in the Antarctic region, providing an opportunity to investigate its broader impact on the whole atmosphere. We present observations from the middle atmosphere and ionosphere during this event, noting unusually strong wave activity throughout this region. Our results suggest that an Antarctic SSW can have a significant impact on the whole atmosphere system similar to those due to Arctic events.
Flood risk management in Germany follows an integrative approach in which both private households and businesses can make an important contribution to reducing flood damage by implementing property-level adaptation measures. While the flood adaptation behavior of private households has already been widely researched, comparatively less attention has been paid to the adaptation strategies of businesses. However, their ability to cope with flood risk plays an important role in the social and economic development of a flood-prone region. Therefore, using quantitative survey data, this study aims to identify different strategies and adaptation drivers of 557 businesses damaged by a riverine flood in 2013 and 104 businesses damaged by pluvial or flash floods between 2014 and 2017. Our results indicate that a low perceived self-efficacy may be an important factor that can reduce the motivation of businesses to adapt to flood risk. Furthermore, property-owners tended to act more proactively than tenants. In addition, high experience with previous flood events and low perceived response costs could strengthen proactive adaptation behavior. These findings should be considered in business-tailored risk communication.
Rain fall-runoff response in temperate humid headwater catchments is mainly controlled by hydrolo gical processes at the hillslope scale. Applied tracer experiments with fluore scent dye and salt tracers are well known tools in groundwater studies at the large scale and vadose zone studies at the plot scale, where they provide a means to characterise subsurface flow. We extend this approach to the hillslope scale to investigate saturated and unsaturated flow path s concertedly at a forested hill slope in the Austrian Alps. Dye staining experiments at the plot scale revealed that crack s and soil pipe s function as preferential flow path s in the fine-textured soils of the study area, and these preferenti al flow structures were active in fast subsurface transport of tracers at the hillslope scale. Breakthrough curves obtained under steady flow conditions could be fitted well to a one-dimensional convection-dispersion model. Under natural rain fall a positive correlation of tracer concentrations to the transient flows was observed. The results of this study demon strate qualitative and quantitative effects of preferential flow feature s on subsurface stormflow in a temperate humid headwater catchment. It turn s out that , at the hill slope scale, the interaction s of structures and processes are intrinsically complex, which implies that attempts to model such a hillslope satisfactorily require detailed investigation s of effective structures and parameters at the scale of interest.
This review analyzes the potential role and long-term effects of field perennial polycultures (mixtures) in agricultural systems, with the aim of reducing the trade-offs between provisioning and regulating ecosystem services. First, crop rotations are identified as a suitable tool for the assessment of the long-term effects of perennial polycultures on ecosystem services, which are not visible at the single-crop level. Second, the ability of perennial polycultures to support ecosystem services when used in crop rotations is quantified through eight agricultural ecosystem services. Legume-grass mixtures and wildflower mixtures are used as examples of perennial polycultures, and compared with silage maize as a typical crop for biomass production. Perennial polycultures enhance soil fertility, soil protection, climate regulation, pollination, pest and weed control, and landscape aesthetics compared with maize. They also score lower for biomass production compared with maize, which confirms the trade-off between provisioning and regulating ecosystem services. However, the additional positive factors provided by perennial polycultures, such as reduced costs for mineral fertilizer, pesticides, and soil tillage, and a significant preceding crop effect that increases the yields of subsequent crops, should be taken into account. However, a full assessment of agricultural ecosystem services requires a more holistic analysis that is beyond the capabilities of current frameworks.
Understanding the hydrologic connectivity between kettle holes and shallow groundwater, particularly in reaction to the highly variable local meteorological conditions, is of paramount importance for tracing water in a hydro(geo)logically complex landscape and thus for integrated water resource management. This article is aimed at identifying the dominant hydrological processes affecting the kettle holes' water balance and their interactions with the shallow groundwater domain in the Uckermark region, located in the north-east of Germany. For this reason, based on the stable isotopes of oxygen (delta O-18) and hydrogen (delta H-2), an isotopic mass balance model was employed to compute the evaporative loss of water from the kettle holes from February to August 2017. Results demonstrated that shallow groundwater inflow may play the pivotal role in the processes taking part in the hydrology of the kettle holes in the Uckermark region. Based on the calculated evaporation/inflow (E/I) ratios, most of the kettle holes (86.7%) were ascertained to have a partially open, flow-through-dominated system. Moreover, we identified an inverse correlation between E/I ratios and the altitudes of the kettle holes. The same holds for electrical conductivity (EC) and the altitudes of the kettle holes. In accordance with the findings obtained from this study, a conceptual model explaining the interaction between the shallow groundwater and the kettle holes of Uckermark was developed. The model exhibited that across the highest altitudes, the recharge kettle holes are dominant, where a lower ratio of E/I and a lower EC was detected. By contrast, the lowest topographical depressions represent the discharge kettle holes, where a higher ratio of E/I and EC could be identified. The kettle holes existing in between were categorized as flow-through kettle holes through which the recharge takes place from one side and discharge from the other side.
Quantifying the extremeness of heavy precipitation allows for the comparison of events. Conventional quantitative indices, however, typically neglect the spatial extent or the duration, while both are important to understand potential impacts. In 2014, the weather extremity index (WEI) was suggested to quantify the extremeness of an event and to identify the spatial and temporal scale at which the event was most extreme. However, the WEI does not account for the fact that one event can be extreme at various spatial and temporal scales. To better understand and detect the compound nature of precipitation events, we suggest complementing the original WEI with a “cross-scale weather extremity index” (xWEI), which integrates extremeness over relevant scales instead of determining its maximum.
Based on a set of 101 extreme precipitation events in Germany, we outline and demonstrate the computation of both WEI and xWEI. We find that the choice of the index can lead to considerable differences in the assessment of past events but that the most extreme events are ranked consistently, independently of the index. Even then, the xWEI can reveal cross-scale properties which would otherwise remain hidden. This also applies to the disastrous event from July 2021, which clearly outranks all other analyzed events with regard to both WEI and xWEI.
While demonstrating the added value of xWEI, we also identify various methodological challenges along the required computational workflow: these include the parameter estimation for the extreme value distributions, the definition of maximum spatial extent and temporal duration, and the weighting of extremeness at different scales. These challenges, however, also represent opportunities to adjust the retrieval of WEI and xWEI to specific user requirements and application scenarios.
Compound weather events may lead to extreme impacts that can affect many aspects of society including agriculture. Identifying the underlying mechanisms that cause extreme impacts, such as crop failure, is of crucial importance to improve their understanding and forecasting. In this study, we investigate whether key meteorological drivers of extreme impacts can be identified using the least absolute shrinkage and selection operator (LASSO) in a model environment, a method that allows for automated variable selection and is able to handle collinearity between variables. As an example of an extreme impact, we investigate crop failure using annual wheat yield as simulated by the Agricultural Production Systems sIMulator (APSIM) crop model driven by 1600 years of daily weather data from a global climate model (EC-Earth) under present-day conditions for the Northern Hemisphere. We then apply LASSO logistic regression to determine which weather conditions during the growing season lead to crop failure. We obtain good model performance in central Europe and the eastern half of the United States, while crop failure years in regions in Asia and the western half of the United States are less accurately predicted. Model performance correlates strongly with annual mean and variability of crop yields; that is, model performance is highest in regions with relatively large annual crop yield mean and variability. Overall, for nearly all grid points, the inclusion of temperature, precipitation and vapour pressure deficit is key to predict crop failure. In addition, meteorological predictors during all seasons are required for a good prediction. These results illustrate the omnipresence of compounding effects of both meteorological drivers and different periods of the growing season for creating crop failure events. Especially vapour pressure deficit and climate extreme indicators such as diurnal temperature range and the number of frost days are selected by the statistical model as relevant predictors for crop failure at most grid points, underlining their overarching relevance. We conclude that the LASSO regression model is a useful tool to automatically detect compound drivers of extreme impacts and could be applied to other weather impacts such as wildfires or floods. As the detected relationships are of purely correlative nature, more detailed analyses are required to establish the causal structure between drivers and impacts.
The co-occurrence of warm spells and droughts can lead to detrimental socio-economic and ecological impacts, largely surpassing the impacts of either warm spells or droughts alone. We quantify changes in the number of compound warm spells and droughts from 1979 to 2018 in the Mediterranean Basin using the ERA5 data set. We analyse two types of compound events: 1) warm season compound events, which are extreme in absolute terms in the warm season from May to October and 2) year-round deseasonalised compound events, which are extreme in relative terms respective to the time of the year. The number of compound events increases significantly and especially warm spells are increasing strongly – with an annual growth rates of 3.9 (3.5) % for warm season (deseasonalised) compound events and 4.6 (4.4) % for warm spells –, whereas for droughts the change is more ambiguous depending on the applied definition. Therefore, the rise in the number of compound events is primarily driven by temperature changes and not the lack of precipitation. The months July and August show the highest increases in warm season compound events, whereas the highest increases of deseasonalised compound events occur in spring and early summer. This increase in deseasonalised compound events can potentially have a significant impact on the functioning of Mediterranean ecosystems as this is the peak phase of ecosystem productivity and a vital phenophase.
Mediterranean ecosystems are particularly vulnerable to climate change and the associated increase in climate anomalies. This study investigates extreme ecosystem responses evoked by climatic drivers in the Mediterranean Basin for the time span 1999–2019 with a specific focus on seasonal variations as the seasonal timing of climatic anomalies is considered essential for impact and vulnerability assessment. A bivariate vulnerability analysis is performed for each month of the year to quantify which combinations of the drivers temperature (obtained from ERA5-Land) and soil moisture (obtained from ESA CCI and ERA5-Land) lead to extreme reductions in ecosystem productivity using the fraction of absorbed photosynthetically active radiation (FAPAR; obtained from the Copernicus Global Land Service) as a proxy.
The bivariate analysis clearly showed that, in many cases, it is not just one but a combination of both drivers that causes ecosystem vulnerability. The overall pattern shows that Mediterranean ecosystems are prone to three soil moisture regimes during the yearly cycle: they are vulnerable to hot and dry conditions from May to July, to cold and dry conditions from August to October, and to cold conditions from November to April, illustrating the shift from a soil-moisture-limited regime in summer to an energy-limited regime in winter. In late spring, a month with significant vulnerability to hot conditions only often precedes the next stage of vulnerability to both hot and dry conditions, suggesting that high temperatures lead to critically low soil moisture levels with a certain time lag. In the eastern Mediterranean, the period of vulnerability to hot and dry conditions within the year is much longer than in the western Mediterranean. Our results show that it is crucial to account for both spatial and temporal variability to adequately assess ecosystem vulnerability. The seasonal vulnerability approach presented in this study helps to provide detailed insights regarding the specific phenological stage of the year in which ecosystem vulnerability to a certain climatic condition occurs.
How to cite.
Vogel, J., Paton, E., and Aich, V.: Seasonal ecosystem vulnerability to climatic anomalies in the Mediterranean, Biogeosciences, 18, 5903–5927, https://doi.org/10.5194/bg-18-5903-2021, 2021.
Thousands of glacier lakes have been forming behind natural dams in high mountains following glacier retreat since the early 20th century. Some of these lakes abruptly released pulses of water and sediment with disastrous downstream consequences. Yet it remains unclear whether the reported rise of these glacier lake outburst floods (GLOFs) has been fueled by a warming atmosphere and enhanced meltwater production, or simply a growing research effort. Here we estimate trends and biases in GLOF reporting based on the largest global catalog of 1,997 dated glacier-related floods in six major mountain ranges from 1901 to 2017. We find that the positive trend in the number of reported GLOFs has decayed distinctly after a break in the 1970s, coinciding with independently detected trend changes in annual air temperatures and in the annual number of field-based glacier surveys (a proxy of scientific reporting). We observe that GLOF reports and glacier surveys decelerated, while temperature rise accelerated in the past five decades. Enhanced warming alone can thus hardly explain the annual number of reported GLOFs, suggesting that temperature-driven glacier lake formation, growth, and failure are weakly coupled, or that outbursts have been overlooked. Indeed, our analysis emphasizes a distinct geographic and temporal bias in GLOF reporting, and we project that between two to four out of five GLOFs on average might have gone unnoticed in the early to mid-20th century. We recommend that such biases should be considered, or better corrected for, when attributing the frequency of reported GLOFs to atmospheric warming.
Root water uptake is an essential process for terrestrial plants that strongly affects the spatiotemporal distribution of water in vegetated soil. Fast neutron tomography is a recently established non-invasive imaging technique capable to capture the 3D architecture of root systems in situ and even allows for tracking of three-dimensional water flow in soil and roots. We present an in vivo analysis of local water uptake and transport by roots of soil-grown maize plants—for the first time measured in a three-dimensional time-resolved manner. Using deuterated water as tracer in infiltration experiments, we visualized soil imbibition, local root uptake, and tracked the transport of deuterated water throughout the fibrous root system for a day and night situation. This revealed significant differences in water transport between different root types. The primary root was the preferred water transport path in the 13-days-old plants while seminal roots of comparable size and length contributed little to plant water supply. The results underline the unique potential of fast neutron tomography to provide time-resolved 3D in vivo information on the water uptake and transport dynamics of plant root systems, thus contributing to a better understanding of the complex interactions of plant, soil and water.
The sensitivity of fluvial systems to tectonic and climatic boundary conditions allows us to use the geomorphic and stratigraphic records as quantitative archives of past climatic and tectonic conditions. Thus, fluvial terraces that form on alluvial fans and floodplains as well as the rate of sediment export to oceanic and continental basins are commonly used to reconstruct paleoenvironments. However, we currently lack a systematic and quantitative understanding of the transient evolution of fluvial systems and their associated sediment storage and release in response to changes in base level, water input, and sediment input. Such knowledge is necessary to quantify past environmental change from terrace records or sedimentary deposits and to disentangle the multiple possible causes for terrace formation and sediment deposition. Here, we use a set of seven physical experiments to explore terrace formation and sediment export from a single, braided channel that is perturbed by changes in upstream water discharge or sediment supply, or through downstream base-level fall. Each perturbation differently affects (1) the geometry of terraces and channels, (2) the timing of terrace cutting, and (3) the transient response of sediment export from the basin. In general, an increase in water discharge leads to near-instantaneous channel incision across the entire fluvial system and consequent local terrace cutting, thus preserving the initial channel slope on terrace surfaces, and it also produces a transient increase in sediment export from the system. In contrast, a decreased upstream sediment-supply rate may result in longer lag times before terrace cutting, leading to terrace slopes that differ from the initial channel slope, and also lagged responses in sediment export. Finally, downstream base-level fall triggers the upstream propagation of a diffuse knickzone, forming terraces with upstream-decreasing ages. The slope of terraces triggered by base-level fall mimics that of the newly adjusted active channel, whereas slopes of terraces triggered by a decrease in upstream sediment discharge or an increase in upstream water discharge are steeper compared to the new equilibrium channel. By combining fillterrace records with constraints on sediment export, we can distinguish among environmental perturbations that would otherwise remain unresolved when using just one of these records.
Aim This study investigates taxonomic and phylogenetic diversity in diatom genera to evaluate assembly rules for eukaryotic microbes across the Siberian tree line. We first analysed how phylogenetic distance relates to taxonomic richness and turnover. Second, we used relatedness indices to evaluate if environmental filtering or competition influences the assemblies in space and through time. Third, we used distance-based ordination to test which environmental variables shape diatom turnover. Location Yakutia and Taymyria, Russia: we sampled 78 surface sediments and a sediment core, extending to 7,000 years before present, to capture the forest-tundra transition in space and time respectively. Taxon Arctic freshwater diatoms. Methods We applied metabarcoding to retrieve diatom diversity from surface and core sedimentary DNA. The taxonomic assignment binned sequence types (lineages) into genera and created taxonomic (abundance of lineages within different genera) and phylogenetic datasets (phylogenetic distances of lineages within different genera). Results Contrary to our expectations, we find a unimodal relationship between phylogenetic distance and richness in diatom genera. We discern a positive relationship between phylogenetic distance and taxonomic turnover in spatially and temporally distributed diatom genera. Furthermore, we reveal positive relatedness indices in diatom genera across the spatial environmental gradient and predominantly in time slices at a single location, with very few exceptions assuming effects of competition. Distance-based ordination of taxonomic and phylogenetic turnover indicates that lake environment variables, like HCO3- and water depth, largely explain diatom turnover. Main conclusion Phylogenetic and abiotic assembly rules are important in understanding the regional assembly of diatom genera across lakes in the Siberian tree line ecotone. Using a space-time approach we are able to exclude the influence of geography and elucidate that lake environmental variables primarily shape the assemblies. We conclude that some diatom genera have greater capabilities to adapt to environmental changes, whereas others will be putatively replaced or lost due to the displacement of the Arctic tundra biome under recent global warming.
Land degradation and water availability in semi-arid regions are interdependent challenges for management that are influenced by climatic and anthropogenic changes. Erosion and high sediment loads in rivers cause reservoir siltation and decrease storage capacity, which pose risk on water security for citizens, agriculture, and industry. In regions where resources for management are limited, identifying spatial-temporal variability of sediment sources is crucial to decrease siltation. Despite widespread availability of rigorous methods, approaches simplifying spatial and temporal variability of erosion are often inappropriately applied to very data sparse semi-arid regions. In this work, we review existing approaches for mapping erosional hotspots, and provide an example of spatial-temporal mapping approach in two case study regions. The barriers limiting data availability and their effects on erosion mapping methods, their validation, and resulting prioritization of leverage management areas are discussed.
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 presence of impermeable surfaces in urban areas hinders natural drainage and directs the surface runoff to storm drainage systems with finite capacity, which makes these areas prone to pluvial flooding. The occurrence of pluvial flooding depends on the existence of minimal areas for surface runoff generation and concentration. Detailed hydrologic and hydrodynamic simulations are computationally expensive and require intensive resources. This study compared and evaluated the performance of two simplified methods to identify urban pluvial flood-prone areas, namely the fill–spill–merge (FSM) method and the topographic wetness index (TWI) method and used the TELEMAC-2D hydrodynamic numerical model for benchmarking and validation. The FSM method uses common GIS operations to identify flood-prone depressions from a high-resolution digital elevation model (DEM). The TWI method employs the maximum likelihood method (MLE) to probabilistically calibrate a TWI threshold (τ) based on the inundation maps from a 2D hydrodynamic model for a given spatial window (W) within the urban area. We found that the FSM method clearly outperforms the TWI method both conceptually and effectively in terms of model performance.
Identifying urban pluvial flood-prone areas is necessary but the application of two-dimensional hydrodynamic models is limited to small areas. Data-driven models have been showing their ability to map flood susceptibility but their application in urban pluvial flooding is still rare. A flood inventory (4333 flooded locations) and 11 factors which potentially indicate an increased hazard for pluvial flooding were used to implement convolutional neural network (CNN), artificial neural network (ANN), random forest (RF) and support vector machine (SVM) to: (1) Map flood susceptibility in Berlin at 30, 10, 5, and 2 m spatial resolutions. (2) Evaluate the trained models' transferability in space. (3) Estimate the most useful factors for flood susceptibility mapping. The models' performance was validated using the Kappa, and the area under the receiver operating characteristic curve (AUC). The results indicated that all models perform very well (minimum AUC = 0.87 for the testing dataset). The RF models outperformed all other models at all spatial resolutions and the RF model at 2 m spatial resolution was superior for the present flood inventory and predictor variables. The majority of the models had a moderate performance for predictions outside the training area based on Kappa evaluation (minimum AUC = 0.8). Aspect and altitude were the most influencing factors on the image-based and point-based models respectively. Data-driven models can be a reliable tool for urban pluvial flood susceptibility mapping wherever a reliable flood inventory is available.