Search USGSSearch

USGS · 70189163

Influence of road network and population demand assumptions in evacuation modeling for distant tsunamis

Abstract

Tsunami evacuation planning in coastal communities is typically focused on local events where at-risk individuals must move on foot in a matter of minutes to safety. Less attention has been placed on distant tsunamis, where evacuations unfold over several hours, are often dominated by vehicle use and are managed by public safety officials. Traditional traffic simulation models focus on estimating clearance times but often overlook the influence of varying population demand, alternative modes, background traffic, shadow evacuation, and traffic management alternatives. These factors are especially important for island communities with limited egress options to safety. We use the coastal community of Balboa Island, California (USA), as a case study to explore the range of potential clearance times prior to wave arrival for a distant tsunami scenario. We use a first-in–first-out queuing simulation environment to estimate variations in clearance times, given varying assumptions of the evacuating population (demand) and the road network over which they evacuate (supply). Results suggest clearance times are less than wave arrival times for a distant tsunami, except when we assume maximum vehicle usage for residents, employees, and tourists for a weekend scenario. A two-lane bridge to the mainland was the primary traffic bottleneck, thereby minimizing the effect of departure times, shadow evacuations, background traffic, boat-based evacuations, and traffic light timing on overall community clearance time. Reducing vehicular demand generally reduced clearance time, whereas improvements to road capacity had mixed results. Finally, failure to recognize non-residential employee and tourist populations in the vehicle demand substantially underestimated clearance time.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 33.603056937190075° to 33.609883739325674° latitude; -117.9019045829773° to -117.88405179977417° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Kevin Henry, Nathan J. Wood, Tim G. Frazier. 2016-11-11. Influence of road network and population demand assumptions in evacuation modeling for distant tsunamis. https://doi.org/10.1007/s11069-016-2655-8

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Effects of storm surge exceedance value on overwash and inundation forecasts

Hurricane induced sediment transport and flooding can cause catastrophic damage to coastal communities. Forecasts test our understanding of the drivers of sediment transport and flooding, as well as quantify potential storm effects on coastlines. Real-time availability of forecasts allows emergency response and management decisions to be made with additional information. This study analyzed the skill of probabilistic forecasts of overwash and inundation along the Louisiana coastline from back-to-back Hurricanes Laura and Delta in 2020. To test skill, forecasts were compared with observations of mean water level relative to beach elevations and evidence of overwash and inundation identified in post-storm aerial imagery. We found that probabilistic forecasts accurately identified areas where overwash and inundation were likely to occur. In some cases, forecasts also produced a conservative estimation of overwash and inundation. For the first time, we explored the role of exceedance value in probabilistic forecasts of overwash and inundation and found that choice of exceedance value can influence forecasts. Additionally, we found that waves contributed up to 27% of the mean water level and up to 63% of the extreme water level during Hurricanes Laura and Delta.

Louisiana, Texas

Factors influencing landslide occurrence in low-relief formerly glaciated landscapes: Landslide inventory and susceptibility analysis in Minnesota, USA

In landscapes recently impacted by continental glaciation, landslides may occur where topographic relief has been generated by the drainage of glacial lakes and ensuing post-glacial fluvial network development into unconsolidated glacially derived sediments and exhumed bedrock. To investigate linkages among environmental variables, post-glacial landscape development, and landslides, we created a landslide inventory of nearly 10,000 landslides in five regions of the formerly glaciated low-relief state of Minnesota, USA. Multivariate logistic regression indicates the importance of slope angle, lithology, and the development of stream valleys to landslide distribution. Areas underlain by fine-grained glaciolacustrine and nearshore deposits that are incised by streams are particularly prone to shallow (<1-2 m depth) landslides. Landslides also occur in a wide range of glacial and fluvial deposits, and as rockfall in layered Paleozoic sedimentary rocks in central and southern Minnesota and Precambrian igneous and sedimentary rocks in northeastern Minnesota. Although no more than 1-2% of the studied regions are susceptible to landslides, they can pose risk to life and safety, damage infrastructure, and impact water quality. The combination of recently generated low-relief steep slopes, extensive unconsolidated sediments, and layered sedimentary bedrock make this formerly glaciated landscape more susceptible to landslides than current national-scale models indicate.

Minnesota

Landslide-channel feedbacks amplify channel widening during floods

Channel widening is a major hazard during floods, particularly in confined mountainous catchments. However, channel widening during floods is not well understood and not always explained by hydraulic variables alone. Floods in mountainous regions often coincide with landslides triggered by heavy rainfall, yet landslide-channel interactions during a flood event are not well known or documented. Here we demonstrate with an example from the Great Colorado Flood in 2013, a 1000 year precipitation event, how landslide-channel feedbacks can substantially amplify channel widening and flood risk. We use a combination of DEM differencing, field analysis, and multiphase flow modeling to document landslide-channel interaction during the flood event in which sediment delivered by landslides temporarily dammed the channel before failing and generating substantial channel widening. We propose that such landslide-flood interactions will become increasingly important to account for in flood hazard assessment as flooding and landsliding both increase with extreme rainfall under climate change.

Colorado