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Lecture

geog 312 unit 1.docx

21 Pages
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Department
Geography
Course Code
GEOG 312
Professor
Maggie Squires

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What are Natural Hazards? -natural hazards are events associated w/ normal biogeophysical phenomena that may cause harm to humans, such as death, injury, or loss of home, property or income -natural hazards are limited to inhabited areas, that is, to vulnerable human settlements & societies -reasons that humans may be the path of hazards include: -our need for resources provided by hazards such as fertile soils in vicinity of volcanoes, water supply (large rivers) in areas prone to flooding -our preference for scenic lanscapes such as cliffs overlooking ocean (which may be susceptible to landslides) & sandy beaches (which may be susceptible to flooding & erosion) -most natural hazards are initiated or mediated by weather: -initiated—hurricanes, floods, tornadoes -mediated—ash dispersal, landslides, slab avalanches -BC hazards of sufficient size, depth, or displacement to cause damage or disruption include fire, earthquake, tsunami, flooding, landslide, avalanche, & severe weather, such as wind & snow storms -of 179 documented natural hazard events in the Vancouver area most were: -floods caused by rain storms (24 events) -landslides (22 events) -windstorms (11 events) -forest fires (8 events) -snowstorms (7 events) -hazardous events resulting in most deaths include: -Spanish flu, 1918 -heat wave, 1936 -polio outbreak, 1950s -in BC, most events causing numerous casualties took place in early 1900 & involved avalanches & landslides triggered by development activities -in last 20 years a number of storms, landslides, & avalanches have each resulted in >5 deaths Location Date Approx Deaths Type Egypt & Syria 1201 1.1 million EQs Europe & beyond 1347-1350 25 million Bubonic Plague Western 16 -18 century XX million American Indians Hemisphere due to disease carried from Europe India 1769 10 million Famine/drought 1876-1879 9 million Famine/drought 1935 3.4 million Floods World wide 1918-19 50+ million influenza 1958-61 20 million Famine/drought Africa 1981-84 X million Famine/drought North Korea 1995-98 3 million Famine/floods Prediction -probability analysis—predicting where, how large, & when an event may occur based on historic/geologic data, combined w/ computer simulations to fill in data gaps -forecasting—new monitoring technologies, including satellite-based sensors, provide real-time data on current conditions, which may indicate an event (flooding, earthquake, volcanic eruption) is imminent -for most natural hazards, large magnitude events are infrequent & small magnitude events are frequent: M = Fe -x M=magnitude, F=frequency, e=natural logarithm, x=constant -return interval vs flood (discharge) magnitude for the Red River exemplifies that small magnitude events occur as frequently as annually (recurrence interval is one year) & that large magnitude events occur every ten to one hundred years -the terms used to describe the magnitude-frequency relation are recurrence interval (or return period), this is the time btwn events of a particular magnitude, eg, a 100 year flood is a large magnitude event that occurs for a give data set on average every 100 years -however, it’s possible to have two or more (or no) floods of this magnitude in any 100 year period -some simple math: Recurrence interval Probability of occurrence % chance of occurrence 100 1 in 100 1 50 1 in 50 2 25 1 in 25 4 10 1 in 10 10 5 1 in 5 20 2 1 in 2 50 -forecasting is based on real time monitoring -some examples are: -foreshocks may forecast an earthquake -deformation may forecast a volcanic eruption -snowmelt & rain may forecast a flood -heavy precipitation may forecast a landslide -seafloor earthquakes may forecast a tsunami -predicting—probability of occurrence for some period of time (1 to 1000 years) based on knowledge of the past (eg, discharge return intervals) coupled w/ current understanding of causes & precursors -forecasting—based on real time detection of precursor signals; vastly improved w/ GPS satellite (hours, days, months in advance) -warning—based on real time monitoring of an unfolding event; for ex, tsunami modeling, based on quick retrieval & analysis of ground shaking data, which may be only mins in the vicinity of an earthquake (nearfield) to hours at more distant locations (farfield) Vulnerability -vulnerability is the expected deg of impact of a hazard of particular magnitude & reflects capacity of individuals & groups to anticipate, cope w/, resist, & recover from impact of a geophysical event -the impact level of an event is more often related to human vulnerability than to event magnitude -impact may be expressed in terms of: -# of fatalities -cost to repair damage to buildings, facilities & services -revenue loss due to reduction in economic activity -longer term effects, such as disease, political unrest, &/or psychological distress Deaths from natural hazards (1991 -2005) Eruptions Floods Earthquakes and tsunamis Storms Droughts Slides -some ex of EQ & tsunami fatalities: -2003—EQ, Bam, Iran, 43,000 fatalities -2004—EQ, tsunami, Indian Ocean, 250,000 fatalities -2005—EQ, Kashmir, 80,000 fatalities -2008—EQ, China, 88,000 fatalities -2010—EQ, Haiti, 220,000 fatalities -vulnerability of a place is a func of potential exposure to a hazardous event & in turn is linked w/ socio-politico-economic factors, & cultural, land-use, population density, & ecological attributes -natural disasters are usually products of socio-politico-economic regimes, rather than natural hazard, eg, volcanic ash hazard in European air space is a func of dependence on air travel, & famine hazard in the African Horn is a func of geo- political circumstance -conditions that shape vulnerability or the potential for impacts: -personal—individual age/ gender/ education/ cultural-socio-ecological conditions, perception, experience may influence individual risk -economic—economic conditions (wealth) may dictate options -structural—building quality (material, codes) may affect impact -political—political conditions may limit -institutional—local, state, or national gov’ts affect outcomes through policy & enforcement -global economic interconnectedness & interdependence lead to global impacts of local events, eg, disruption of world oil supply after Hurricane Katrina -hazardous events may take individuals by surprise—not only for want of instrumental warnings & education but also b/c a human life & written & instrumental records of past few centuries span too little time to provide experience & perspective on full potential for disaster -large populous countries are disproportionately poor—high vulnerability due to high population density & poverty -affluent countries have disproportionately few ppl—low vulnerability due to low population density & better mitigation & preparation -on other hand, wealth can increase vulnerability, due to technological dependence in an interdependent & interconnected world (eg, complex transportation & communication networks) -increasing wealth may also correspond w/ change in perception of risk, that is, how benefits are weighed against potential losses, eg, low insurance rates may entice movement into hazardous areas -wealth=greater preparedness, mitigation & more capacity to get out of harm’s way -Hurricane Charley, Florida, 2004, caused relatively few casualties -poverty=more attention to provision of basic food & shelter than to mitigation, & less capacity to get out of harm’s way -Hurricane Katrina, Louisana—1 of the 5 deadliest hurricanes in US history -in 1999 earthquake in Marmara Sea area, Turkey, where a culture of corruption increased impact, saw the town of Golcuk (right) experience: -17,000 dead -15% of buildings collapsed -widespread power outages -due to lack of: -building code enforcement -infrastructure quality -zoning enforcement Risk -concept of risk involves weighing benefits vs potential loss: risk= func of hazard & vulnerability -hazard=the likelihood or probability that a natural hazard will occur at sufficient magnitude to impact a particular location -vulnerability=potential exposure of ppl, assets, goods, social & economic activities etc to harm -as an ex, the insurance industry calculates risk & potential losses & sets pricing by: -forecasting the likelihood of catastrophic events for 10,000 years, using data & statistical models for a particular location -generating annual exceedance probabilities (the inverse of recurrence intervals) of potentially damaging events -computing cost of repairs/rebuilding for a particular catastrophic event, using vulnerability & financial models -creating lsos probability distributions for a particular location -statistical models are used to fill in data gaps & extend record -geophysicists use same statistical methods as insurance risk analysts to assess hazard probability -Geist & Parsons (below) are interested in probability of occurrence of large magnitude tsunami at particular locations along eastern edge of Pacific Ocean -for this cumulative probability distribution for an earthquake data set, probability of magnitude (M) 7 event is 1 or one/y, probability of M 9 event is 0.001 or 1/1000y Calculating Risk A1 A2 B1 B2 -here, cumulative probability for tsunami run-up, ranging from 0.1m to 10m shows: -probability of 0.1m (A1) is about 0.1 (A2) (1/10y) -probability of 10m (B1) is about 0.01 (B2) (1/100y) -probability of 0.1 may be referred to as 10% annual exceedance probability event, & probability of 0.01 as a 1% exceedance probability, & so on -that is, an event w/ 0.1 probability has a 10% chance of being equaled or exceeded every 10 years, or an event w/ 0.01 probability has 1% chance of being equaled or exceeded every 100 years Hazard Mapping - probabilities for a # of coastal locations can be used to create hazard maps, such as the one at the right, this shows magnitude of tsunami run-up (size of circle) that could take place up & down the coast over a 150 year period, for earthquakes occurring in diff locations (colour of circle) -this hazard map shows annual probability of a = >1m run up, based on analysis of real data for an entire coas
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