Effect of instructions on damage estimates from single photographs.

1965 ◽  
Vol 49 (4) ◽  
pp. 289-294
Author(s):  
Lee W. Gregg ◽  
Richard Been
Keyword(s):  
Damage Estimates

A Critical Look at the Use of Design Spectrum Shape for Seismic Risk Assessment

2012 ◽  
Vol 28 (4) ◽  
pp. 1711-1721
Author(s):  
Emrah Erduran ◽  
Conrad Lindholm
Keyword(s):  
Numerical Simulations ◽  
Response Spectra ◽  
Ground Motion Prediction Equations ◽  
Ground Motion Prediction ◽  
Design Spectrum ◽  
Spectrum Shape ◽  
Actual Spectrum ◽  
Building Typology ◽  
Actual Response ◽  
Damage Estimates

The effects of using design spectrum shape over actual response spectra on earthquake damage estimates has been investigated. A series of numerical simulations were conducted to estimate the expected damage. The simulations were conducted with four different spectral shapes, two different ground-motion prediction equations (GMPEs) and three different soil classes. As a result of the numerical simulations, it was observed that the use of design spectrum shape leads to over- or underestimation of damage estimates relative to those obtained from the actual spectrum computed using GMPE. The damage estimates were observed to be sensitive to the selected design spectrum shape, the GMPE used to compute the spectral values, the soil type, and the fundamental period of the building typology. It was also observed that Eurocode- and IBC-type design spectrum shapes led to significantly different damage estimates compared to one another.

scholarly journals A framework for global river flood risk assessments

2013 ◽  
Vol 17 (5) ◽  
pp. 1871-1892 ◽  
Author(s):  
H. C. Winsemius ◽  
L. P. H. Van Beek ◽  
B. Jongman ◽  
P. J. Ward ◽  
A. Bouwman
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Hydrological Model ◽  
Flood Hazard ◽  
Probability Distributions ◽  
Flood Routing ◽  
Risk Assessments ◽  
First Case ◽  
Impact Models ◽  
Damage Estimates

Abstract. There is an increasing need for strategic global assessments of flood risks in current and future conditions. In this paper, we propose a framework for global flood risk assessment for river floods, which can be applied in current conditions, as well as in future conditions due to climate and socio-economic changes. The framework's goal is to establish flood hazard and impact estimates at a high enough resolution to allow for their combination into a risk estimate, which can be used for strategic global flood risk assessments. The framework estimates hazard at a resolution of ~ 1 km2 using global forcing datasets of the current (or in scenario mode, future) climate, a global hydrological model, a global flood-routing model, and more importantly, an inundation downscaling routine. The second component of the framework combines hazard with flood impact models at the same resolution (e.g. damage, affected GDP, and affected population) to establish indicators for flood risk (e.g. annual expected damage, affected GDP, and affected population). The framework has been applied using the global hydrological model PCR-GLOBWB, which includes an optional global flood routing model DynRout, combined with scenarios from the Integrated Model to Assess the Global Environment (IMAGE). We performed downscaling of the hazard probability distributions to 1 km2 resolution with a new downscaling algorithm, applied on Bangladesh as a first case study application area. We demonstrate the risk assessment approach in Bangladesh based on GDP per capita data, population, and land use maps for 2010 and 2050. Validation of the hazard estimates has been performed using the Dartmouth Flood Observatory database. This was done by comparing a high return period flood with the maximum observed extent, as well as by comparing a time series of a single event with Dartmouth imagery of the event. Validation of modelled damage estimates was performed using observed damage estimates from the EM-DAT database and World Bank sources. We discuss and show sensitivities of the estimated risks with regard to the use of different climate input sets, decisions made in the downscaling algorithm, and different approaches to establish impact models.

scholarly journals Visual evidence, damage estimates, and timeline analysis (Appendix H-M)

2005 ◽  
Author(s):  
William M Pitts ◽  
Kathryn M Butler ◽  
Valentine Junker
Keyword(s):  
Visual Evidence ◽  
Timeline Analysis ◽  
Damage Estimates

Environmental Damage and its Impacts on Inequality and Poverty: Applications to Brazil and Costa Rica

2007 ◽  
pp. 68
Author(s):  
Mariano Torras
Keyword(s):  
Sensitivity Analysis ◽  
Costa Rica ◽  
Environmental Damage ◽  
Distribution Data ◽  
Ecological Distribution ◽  
Poverty Measures ◽  
Damage Estimates

Accounting for environmental damage is relevant to how one measures the extent and severity of inequality and poverty, and the question of ecological distribution - how the costs associated with environmental damage are distributed across the population - is critical. Following Khan’s (1997) study on Bangladesh, I use environmental damage estimates to adjust inequality and poverty measures for Brazil and Costa Rica. Unlike Khan, I test for different assumptions regarding the ecological distribution. Provisional results indicate that inequality and poverty are understated, and that, under certain assumptions, both worsened in Costa Rica during the 1980s, contrary to what conventional statistics suggest. Want of reliable ecological distribution data, however, suggests that sensitivity analysis around competing assumptions may be preferable to conventional indicators.

Fall-out: Some Measurements and Damage Estimates

1955 ◽  
Vol 11 (6) ◽  
pp. 213-216
Author(s):  
A. H. Rosenfeld ◽  
E. J. Story ◽  
S. D. Warshaw
Keyword(s):  
Damage Estimates

scholarly journals Analysis of Damage Caused by Hydrometeorological Disasters in Texas, 1960–2016

Geosciences ◽  
2018 ◽  
Vol 8 (10) ◽  
pp. 384 ◽  
Author(s):  
Srikanto Paul ◽  
Hatim Sharif
Keyword(s):  
Model Simulation ◽  
Metropolitan Statistical Area ◽  
Property Damage ◽  
Change Models ◽  
Severe Thunderstorms ◽  
Major Disaster ◽  
Increasing Trend ◽  
Per Capita ◽  
The Impact ◽  
Damage Estimates

Property damages caused by hydrometeorological disasters in Texas during the period 1960–2016 totaled $54.2 billion with hurricanes, tropical storms, and hail accounting for 56%, followed by flooding and severe thunderstorms responsible for 24% of the total damages. The current study provides normalized trends to support the assertion that the increase in property damage is a combined contribution of stronger disasters as predicted by climate change models and increases in urban development in risk prone regions such as the Texas Gulf Coast. A comparison of the temporal distribution of damages normalized by population and GDP resulted in a less statistically significant increasing trend per capita. Seasonal distribution highlights spring as the costliest season (March, April and May) while the hurricane season (June through November) is well aligned with the months of highest property damage. Normalization of property damage by GDP during 2001–2016 showed Dallas as the only metropolitan statistical area (MSA) with a significant increasing trend of the 25 MSAs in Texas. Spatial analysis of property damage per capita highlighted the regions that are at greater risk during and after a major disaster given their limited economic resources compared to more urbanized regions. Variation in the causes of damage (wind or water) and types of damage that a “Hurricane” can produce was investigated using Hazus model simulation. A comparison of published damage estimates at time of occurrence with simulation outputs for Hurricanes Carla, 1961; Alicia, 1983; and Ike, 2008 based on 2010 building exposure highlighted the impact of economic growth, susceptibility of wood building types, and the predominant cause of damage. Carla and Ike simulation models captured less than 50% of their respective estimates reported by other sources suggesting a broad geographical zone of damage with flood damage making a significant contribution. Conversely, the model damage estimates for Alicia are 50% higher than total damage estimates that were reported at the time of occurrence suggesting a substantial increase in building exposure susceptible to wind damage in the modeled region from 1983 – 2010.

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