Moving boulders in flash floods and estimating flow conditions using boulders in ancient deposits

Boulders moving in flash floods cause considerable damage and casualties. More and bigger boulders move in flash floods than predicted from published theory. The interpretation of flow conditions from the size of large particles within flash flood deposits has, until now, generally assumed that the velocity (or discharge) is unchanging in time (i.e. flow is steady), or changes instantaneously between periods of constant conditions. Standard practice is to apply theories developed for steady flow conditions to flash floods, which are however inherently very unsteady flows. This is likely to lead to overestimates of peak flow velocity (or discharge). Flash floods are characterised by extremely rapid variations in flow that generate significant transient forces in addition to the mean‐flow drag. These transient forces, generated by rapid velocity changes, are generally ignored in published theories, but they are briefly so large that they could initiate the motion of boulders. This paper develops a theory for the initiation of boulder movement due to the additional impulsive force generated by unsteady flow, and discusses the implications.     

Evaluating Lost Person Behavior Models

US wilderness search and rescue consumes thousands of person‐hours and millions of dollars annually. Timeliness is critical: the probability of success decreases substantially after 24 hours. Although over 90% of searches are quickly resolved by standard “reflex” tasks, the remainder require and reward intensive planning. Planning begins with a probability map showing where the lost person is likely to be found. The MapScore project described here provides a way to evaluate probability maps using actual historical searches. In this work we generated probability maps the Euclidean distance tables in (Koester 2008 ), and using Doke's ( 2012 ) watershed model. Watershed boundaries follow high terrain and may better reflect actual barriers to travel. We also created a third model using the joint distribution using Euclidean and watershed features. On a metric where random maps score 0 and perfect maps score 1, the Euclidean distance model scored 0.78 (95%CI: 0.74–0.82, on 376 cases). The simple watershed model by itself was clearly inferior at 0.61, but the Combined model was slightly better at 0.81 (95%CI: 0.77–0.84).     

Spatial exposure aspects contributing to vulnerability and resilience assessments of urban critical infrastructure in a flood and blackout context

Blackouts aggravate the situation during an extreme river-flood event by affecting residents and visitors of an urban area. But also rescue services, fire brigades and basic urban infrastructure such as hospitals have to operate under suboptimal conditions. This paper aims to demonstrate how affected people, critical infrastructure, such as electricity, roads and civil protection infrastructure are intertwined during a flood event, and how this can be analysed in a spatially explicit way. The city of Cologne (Germany) is used as a case study since it is river-flood prone and thousands of people had been affected in the floods in 1993 and 1995. Components of vulnerability and resilience assessments are selected with a focus of analysing exposure to floods, and five steps of analysis are demonstrated using a geographic information system. Data derived by airborne and spaceborne earth observation to capture flood extent and demographic data are combined with place-based information about location and distance of objects. The results illustrate that even fire brigade stations, hospitals and refugee shelters are within the flood scenario area. Methodologically, the paper shows how criticality of infrastructure can be analysed and how static vulnerability assessments can be improved by adding routing calculations. Fire brigades can use this information to improve planning on how to access hospitals and shelters under flooded road conditions.