River flooding is among the most destructive of natural hazards globally, causing widespread loss of life, damage to infrastructure and economic deprivation. Societies are currently under increasing threat from such floods, predominantly from increasing exposure of people and assets in flood‐prone areas, but also as a result of changes in flood magnitude, frequency, and timing. Accurate flood hazard and risk assessment are therefore crucial for the sustainable development of societies worldwide. With a paucity of hydrological measurements, evidence from the field offers the only insight into truly extreme events and their variability in space and time. Historical, botanical, and geological archives have increasingly been recognized as valuable sources of extreme flood event information. These different archives are here reviewed with a particular focus on the recording mechanisms of flood information, the historical development of the methodological approaches and the type of information that those archives can provide. These studies provide a wealthy dataset of hundreds of historical and palaeoflood series, whose analysis reveals a noticeable dominance of records in Europe. After describing the diversity of flood information provided by this dataset, we identify how these records have improved and could further improve flood hazard assessments and, thereby, flood management and mitigation plans. This article is categorized under: Science of Water > Water Extremes Engineering Water > Planning Water Science of Water > Methods

Extreme hydrologic responses following wildfires can lead to floods and debris flows with costly economic and societal impacts. Process-based hydrologic and geomorphic models used to predict the downstream impacts of wildfire must account for temporal changes in hydrologic parameters related to the generation and subsequent routing of infiltration-excess overland flow across the landscape.However, we lack quantitative relationships showing how parameters change with time-since-burning, particularly at the watershed scale. To assess variations in bestfit hydrologic parameters with time, we used the KINEROS2 hydrological model to explore temporal changes in hillslope saturated hydraulic conductivity (K sh ) and channel hydraulic roughness (n c ) following a wildfire in the upper Arroyo Seco watershed (41.5 km 2 ), which burned during the 2009 Station fire in the San Gabriel Mountains, California, USA. This study explored runoff-producing storms between 2008 and 2014 to infer watershed hydraulic properties by calibrating the model to observations at the watershed outlet. Modelling indicates K sh is lowest in the first year following the fire and then increases at an average rate of approximately 4.2 mm/h/year during the first 5 years of recovery. The estimated values for K sh in the first year following the fire are similar to those obtained in previous studies on smaller watersheds (<1.5 km 2 ) following the Station fire, suggesting hydrologic changes detected here can be applied to lower-order watersheds. Hydraulic roughness, n c , was lowest in the first year following the fire, but increased by a factor of 2 after 1 year of recovery. Post-fire observations suggest changes in n c are due to changes in grain roughness and vegetation in channels. These results provide quantitative constraints on the magnitude of fire-induced hydrologic changes following severe wildfires in chaparral-dominated ecosystems as well as the timing of hydrologic recovery.

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Earthquake occurrence rates in some parts of the Central United States have been elevated for a number of years; this increase has been widely attributed to deep wastewater injection associated with oil and gas activities. This induced seismicity has caused damage to buildings and infrastructure and substantial public concern. In March 2016, the U.S. Geological Survey (USGS) published its first earthquake ground motion hazard model that accounts for the elevated seismicity, producing a one-year forecast encompassing both induced and natural earthquakes. To assess the potential impact of the elevated seismicity on buildings and the public, this paper quantifies forecasted risks of (1) building collapse and (2) the falling of nonstructural building components by combining the 2016 USGS hazard model with fragility curves for generic modern code-compliant buildings. The assessment shows significant increases in both types of risk compared to that caused by noninduced earthquakes alone; the magnitude of the increases varies from a few times to more than 100 times, depending on location, building period (which is correlated to building height), alternatives for the hazard model, and type of risk of interest. For exploratory purposes only, we also estimate revised values of the risk-targeted ground motion that are currently used for designing buildings.