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Trends in flood magnitudes vary across the conterminous USA (CONUS). There have been attempts to identify what controls these regionally varying trends, but these attempts were limited to certain—for example, climatic—variables or to smaller regions, using different methods and datasets each time. Here we attribute the trends in annual maximum streamflow for 4,390 gauging stations across the CONUS in the period 1960–2010, while using a novel combination of methods and an unprecedented variety of potential controlling variables to allow large‐scale comparisons and minimize biases. Using process‐based flood classification and complex networks, we find 10 distinct clusters of catchments with similar flood behavior. We compile a set of 31 hydro‐climatological and land use variables as predictors for 10 separate Random Forest models, allowing us to find the main controls the flood magnitude trends for each cluster. By using Accumulated Local Effect plots, we can understand how these controls influence the trends in the flood magnitude. We show that hydro‐climatologic changes and land use are of similar importance for flood magnitude trends across the CONUS. Static land use variables are more important than their trends, suggesting that land use is able to attenuate (forested areas) or amplify (urbanized areas) the effects of climatic changes on flood magnitudes. For some variables, we find opposing effects in different regions, showing that flood trend controls are highly dependent on regional characteristics and that our novel approach is necessary to attribute flood magnitude trends reliably at the continental scale while maintaining sensitivity to regional controls. Key Points: A wide variety of controls are necessary to explain flood magnitude trends across the United States between 1960 and 2010Climatic changes and land cover conditions are of similar importance for flood magnitude trends at the regional scaleControls on flood trends can have highly nonlinear effects and can have opposing effects in different hydro‐climatological subregions [ABSTRACT FROM AUTHOR]

In some catchments, the distribution of annual maximum streamflow shows heavy tail behavior, meaning the occurrence probability of extreme events is higher than if the upper tail decayed exponentially. Neglecting heavy tail behavior can lead to an underestimation of the likelihood of extreme floods and the associated risk. Partly contradictory results regarding the controls of heavy tail behavior exist in the literature and the knowledge is still very dispersed and limited. To better understand the drivers, we analyze the upper tail behavior and its controls for 480 catchments in Germany and Austria over a period of more than 50 years. The catchments span from quickly reacting mountain catchments to large lowland catchments, allowing for general conclusions. We compile a wide range of event and catchment characteristics and investigate their association with an indicator of the tail heaviness of flood distributions, namely the shape parameter of the GEV distribution. Following univariate analyses of these characteristics, along with an evaluation of different aggregations of event characteristics, multiple linear regression models, as well as random forests, are constructed. A novel slope indicator, which represents the relation between the return period of flood peaks and event characteristics, captures the controls of heavy tails best. Variables describing the catchment response are found to dominate the heavy tail behavior, followed by event precipitation, flood seasonality, and catchment size. The pre‐event moisture state in a catchment has no relevant impact on the tail heaviness even though it does influence flood magnitudes. Plain Language Summary: For each river catchment, we can estimate how likely it is that floods of certain magnitudes occur in that river. This is called a probability distribution. In some rivers, the occurrence of extreme floods is more likely than in others – their probability distribution decays slower and has a so‐called heavy tail. Here, we examine which factors lead to higher probabilities of extreme floods in some rivers compared to others. To this aim, we look at the annual maximum river flows of 480 rivers in Germany and Austria over a period of more than 50 years. As potential factors influencing the likelihood of extreme floods, we analyze characteristics describing the river catchments in general and characteristics describing specific flood events. Using modeling approaches, we find that how a catchment responds to heavy rainfall has the strongest effect on the probability of extremes. A catchment is more likely to experience extreme flooding, if the largest observed floods are characterized by (a) high runoff coefficients, meaning a large share of rainfall becomes direct streamflow and (b) short event time scales, meaning the floods are short but intense. The rainfall itself and the season in which floods usually occur also have an influence. Key Points: Differences between large and small floods are described by a novel slope indicator and are decisive for the emergence of heavy tailsHeavy tail behavior is mainly controlled by the catchment response and event precipitation, and by flood seasonality and catchment areaPre‐event moisture state within a catchment has no noticeable impact on tail heaviness [ABSTRACT FROM AUTHOR]

The magnitudes of river floods in Europe have been observed to change, but their alignment with changes in the spatial coverage or extent of individual floods has not been clear. We analyze flood magnitudes and extents for 3,872 hydrometric stations across Europe over the past five decades and classify each flood based on antecedent weather conditions. We find positive correlations between flood magnitudes and extents for 95% of the stations. In central Europe and the British Isles, the association of increasing trends in magnitudes and extents is due to a magnitude‐extent correlation of precipitation and soil moisture along with a shift in the flood generating processes. The alignment of trends in flood magnitudes and extents highlights the increasing importance of transnational flood risk management. Plain Language Summary: If multiple rivers flood at the same time because of large‐scale rainfall, the resulting damage can exceed the capacities of disaster recovery and insurance companies. We find that events with a large spatial coverage or extent tend to be associated with above average magnitudes of the flooding level. During 1960–2010 flood extents increased in central Europe and the British Isles but decreased in Eastern Europe. These trends are caused by changes in flood generation processes due to a changing climate. If these trends persist into the future, the combination of stronger floods and larger extents is likely to increase the flood risk substantially. Key Points: Flood magnitudes and extents are correlated across EuropeBoth have increased in central Europe and the British Isles but decreased in Eastern EuropeThese trends are driven by regional changes in flood generation [ABSTRACT FROM AUTHOR]

The generation of extreme flood events is influenced by a multitude of parameters that interact in complex ways. To understand their temporal and spatial relationships as well as changes in this system we need adequate tools. We therefore use multilayer complex networks and extreme event statistics to discover and interpret relationships between flood influencing parameters (e.g. precipitation, catchment wetness, discharge). Complex networks have formerly been successfully used for climatic and hydrological representations. A multilayer approach enables us to find inter-relationships between the different influences. We use non-linear similarity measures to generate the network connections. By analysis of variations of the network appearance and metrics with time, we can reconstruct temporal changes in the underlying processes. We are investigating several hundred river gauges across Europe over a timeframe of 70 years. [ABSTRACT FROM AUTHOR]

Highlights • First high-resolution data from a creepmeter array collocated with seismometers. • Monitored faults are highly susceptible to dynamically triggered shallow slip. • Far-field triggering relates to surface waves, near-field triggering to body waves. • Large earthquakes can trigger shallow slip events over distances of 103–105 km. • Triggered shallow slip scales with seismic energy density. Abstract The M w = 8.8 Maule Earthquake of February 27, 2010, remotely triggered minor surface displacement along the Atacama Fault System in Northern Chile located 1500–1800 km from the epicenter. Here we present evidence that surface displacement events recorded by the IPOC (Integrated Plate Boundary Observatory in N-Chile) Creepmeter Array are related to earthquakes on the underlying subduction zone interface or to large earthquakes around the world. Our observations document dynamic triggering of shallow slip on faults in a forearc setting. Continuous monitoring revealed that up to 30 displacement events per year occur on the monitored fault segments, >90% of them triggered by earthquakes in the near or far field synchronous to the passage of the seismic wave. We can clearly attribute far field triggering to the passage of the surface wave and near field triggering to the passage of the body wave. The most distant triggered displacement event monitored occurred after the 2011, M w = 9.0 Tohoku-Oki Earthquake located 16 468 km away following the passage of large amplitude SS waves. Comparing the triggered displacement events with other triggered phenomena like seismicity, volcanic eruptions, hydrological changes as well as with data from the California Creepmeter Array we find that the seismic energy density appropriately describes a magnitude–distance scaling relationship of slip triggering. Finally, the observed surface displacement is found to not occur by continuous creep, but rather through nearly exclusively discrete displacement events. [ABSTRACT FROM AUTHOR]