The Concept of Hazard

The study of hazards sits at the heart of AQA A-Level Physical Geography. Understanding how natural events become hazardous to human populations requires a framework that integrates physical processes with human vulnerability, resilience and perception. This lesson establishes the foundational terminology and models that underpin every subsequent topic in the Hazards module.

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Defining Key Terms

Key Definition: A hazard is a natural event, process or phenomenon that has the potential to cause loss of life, injury, property damage, livelihood disruption, social and economic disruption, or environmental degradation (UNDRR, 2009).

It is essential to distinguish between a natural event and a natural hazard. An earthquake occurring beneath the uninhabited mid-Atlantic Ridge is a natural event; the same magnitude earthquake beneath a densely populated city such as Port-au-Prince is a natural hazard. The distinction rests on the interaction between a physical process and a vulnerable population.

Core Vocabulary

Term	Definition
Hazard	A natural process or event with the potential to cause harm to people and property
Risk	The probability of a hazard occurring and its potential impact on people, property and the environment
Vulnerability	The susceptibility of a community to the impacts of a hazard, determined by social, economic, political and physical factors
Capacity	The ability of a community to anticipate, cope with, resist and recover from a hazard event
Resilience	The ability of a system, community or society to resist, absorb, accommodate and recover from hazard effects in a timely and efficient manner
Disaster	A serious disruption of the functioning of a community that exceeds its capacity to cope using its own resources (UNDRR)
Exposure	The people, property, systems or other elements present in hazard zones that are subject to potential losses

Exam Tip: In any essay on hazards, define your terms precisely at the outset. Examiners reward candidates who distinguish clearly between risk, vulnerability and hazard — these are not interchangeable.

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The Disaster Risk Equation

The relationship between hazard, vulnerability and capacity is expressed in the disaster risk equation, widely attributed to the work of Wisner et al. (2004) in At Risk: Natural Hazards, People's Vulnerability and Disasters:

graph LR
    A["Risk"] === B["(Hazard × Vulnerability) / Capacity"]

Risk = (Hazard × Vulnerability) / Capacity

This equation demonstrates several critical points:

1. Risk is not solely determined by the physical hazard. A magnitude 7.0 earthquake does not automatically produce a disaster — the outcome depends on where and when it strikes and how prepared the population is.
2. Vulnerability amplifies risk. Poverty, poor governance, lack of education, marginalised populations, and inadequate infrastructure all increase vulnerability.
3. Capacity reduces risk. Early warning systems, building codes, emergency plans, education, community organisation and financial reserves all reduce risk.

Applying the Equation: Haiti vs Chile

Factor	Haiti Earthquake (2010, Mw 7.0)	Chile Earthquake (2010, Mw 8.8)
Hazard magnitude	Mw 7.0 (lower energy release)	Mw 8.8 (500× more energy)
Deaths	~100,000–316,000 (government figure disputed; independent estimates are lower)	~525
Vulnerability	Extreme poverty (GDP per capita $670), poor building codes, unstable government, deforestation, dense urban population	Middle-income economy (GDP per capita $12,600), enforced building codes, stable democratic governance
Capacity	Very low — minimal emergency services, no earthquake insurance, limited international connections	High — well-trained emergency response, strict seismic building codes since 1960, earthquake insurance
Outcome	Catastrophic disaster — 1.5 million homeless, infrastructure destroyed	Significant damage but rapid recovery; buildings largely withstood shaking

This comparison illustrates that vulnerability and capacity are often more important than the physical magnitude of the hazard in determining disaster outcomes.

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Types of Hazard

Hazards can be classified in several ways. The AQA specification focuses on three broad categories:

By Physical Process

Category	Examples	Timescale
Tectonic hazards	Earthquakes, volcanic eruptions, tsunamis	Seconds to months (acute events)
Atmospheric hazards	Tropical storms, tornadoes, heatwaves, blizzards	Hours to weeks
Hydrological hazards	Floods, droughts, landslides (triggered by water)	Hours to years
Geomorphological hazards	Avalanches, rockfalls, landslides	Seconds to hours

By Speed of Onset

• Rapid-onset hazards — earthquakes, volcanic eruptions, flash floods, tornadoes. Little or no warning time; immediate impacts.
• Slow-onset hazards — droughts, desertification, sea-level rise, soil erosion. Gradual development; cumulative impacts over months or years.

By Spatial Extent

• Localised — landslides, tornadoes (path typically < 1 km wide)
• Regional — tropical storms (hundreds of km), river flooding
• Global — supervolcanic eruptions (Toba ~74,000 BP affected global climate), pandemics

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Hazard Perception

How people perceive hazards profoundly influences their responses. The study of hazard perception was pioneered by Gilbert F. White (1945), often called the "father of floodplain management," whose doctoral thesis at the University of Chicago argued that flooding was not simply a natural event but a product of human choices about where to live and build.

Factors Influencing Hazard Perception

Factor	Influence on Perception
Past experience	People who have experienced a hazard tend to take future events more seriously; conversely, long periods without a hazard may breed complacency ("it won't happen to me")
Economic status	Wealthier individuals often have more options for evacuation, insurance and relocation; poorer communities may feel "trapped" and fatalistic
Education	Higher levels of education are associated with greater awareness of hazard risk and more proactive responses
Religion and culture	Some communities interpret hazards as divine punishment or fate, reducing motivation for preparedness (though faith communities also provide powerful support networks)
Level of trust in authorities	Communities that trust scientific warnings and government advice are more likely to evacuate and prepare
Personality and psychology	Some individuals are natural risk-takers; others are highly risk-averse
Media and social media	Media coverage can amplify or diminish perceived risk; social media can spread both accurate warnings and misinformation rapidly

Perception Categories

Geographers commonly identify three broad categories of hazard perception:

1. Fatalism — "Hazards are beyond our control; we accept what comes." Common in communities with repeated exposure and limited resources. Associated with religious or cultural acceptance of natural forces.
2. Adaptation — "We can live with hazards if we modify our behaviour and environment." This is the approach advocated by most hazard managers. Examples include building earthquake-resistant structures and establishing flood defences.
3. Domination — "We can control nature through technology." Associated with large-scale engineering responses such as dam construction, river channelisation and storm surge barriers. Criticised for creating a false sense of security and potentially increasing long-term vulnerability.

Exam Tip: When discussing hazard perception, always link it to specific case studies. For example, many residents of Montserrat's exclusion zone refused to leave despite volcanic warnings because their entire livelihoods were tied to the land. This is not irrational — it is a rational response to a difficult choice between certain economic loss and uncertain physical danger.

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Park's Model (Hazard Response Curve)

Park's Model (Chris Park, 1991) illustrates how a community's quality of life changes over time in response to a hazard event. It is one of the most commonly examined models in the AQA Hazards specification.

graph TD
    subgraph "Park's Hazard Response Model"
        A["Pre-disaster<br/>Normal quality of life"] --> B["Hazard Event<br/>Sudden decline"]
        B --> C["Relief Phase<br/>(hours–days)<br/>Search & rescue,<br/>emergency aid"]
        C --> D["Rehabilitation Phase<br/>(weeks–months)<br/>Restoring services,<br/>temporary housing"]
        D --> E["Reconstruction Phase<br/>(months–years)<br/>Rebuilding, economic recovery"]
    end

The Phases in Detail

Phase	Duration	Characteristics
Pre-disaster	Ongoing	Normal quality of life; level depends on development status. Preparedness measures may be in place.
Hazard event	Minutes to hours	Quality of life drops sharply. Severity depends on magnitude, vulnerability and warning time.
Relief (emergency response)	Hours to days	Search and rescue, emergency shelter, medical care, food and water distribution. Military and international NGOs may assist.
Rehabilitation	Weeks to months	Restoration of essential services (electricity, water, transport), temporary housing, clearing debris, disease prevention.
Reconstruction	Months to years	Rebuilding of infrastructure, housing and the economy. Opportunity to "build back better" — improving resilience.

Three Possible Recovery Trajectories

The model shows that recovery can follow one of three paths:

1. Return to the same level — quality of life recovers to the pre-disaster norm. No lessons learned, no improvement.
2. Build back better — quality of life exceeds the pre-disaster level. Improved building codes, better infrastructure, stronger governance. Example: Japan after the 2011 Tōhoku earthquake invested heavily in upgraded tsunami defences and relocated some communities to higher ground.
3. Downward spiral — quality of life never fully recovers. Successive hazard events compound vulnerability. Example: Haiti, where the 2010 earthquake was followed by a cholera outbreak, Hurricane Matthew (2016), and the 2021 earthquake — each event eroding recovery from the last.

Key Point: Park's Model is a simplification. In reality, recovery is rarely a smooth curve — it is characterised by setbacks, inequalities (different groups recover at different rates), and political decisions that may accelerate or hinder recovery.

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The Pressure and Release (PAR) Model

The Pressure and Release Model was developed by Wisner, Blaikie, Cannon and Davis (1994; updated 2004) in their influential book At Risk. It provides a framework for understanding why disasters occur by examining the root causes, dynamic pressures and unsafe conditions that make communities vulnerable.

graph LR
    subgraph "Progression of Vulnerability"
        A["Root Causes<br/>• Limited access to power<br/>• Ideologies<br/>• Economic systems<br/>• Colonial legacy"] --> B["Dynamic Pressures<br/>• Rapid urbanisation<br/>• Deforestation<br/>• Decline in soil quality<br/>• Lack of training<br/>• Arms expenditure"]
        B --> C["Unsafe Conditions<br/>• Fragile buildings<br/>• Dangerous locations<br/>• Unprotected infrastructure<br/>• Low income<br/>• No social safety nets"]
    end
    C --> D["DISASTER"]
    E["Natural Hazard<br/>• Earthquake<br/>• Flood<br/>• Volcanic eruption<br/>• Storm"] --> D

Key Insights from the PAR Model

• Disasters are NOT natural. The hazard is natural, but the disaster is a product of human vulnerability. This is a fundamental paradigm shift from viewing disasters as "acts of God."
• Root causes are often distant in time and space from the disaster itself. Colonial exploitation, unequal trade relationships, and political marginalisation create the conditions for vulnerability decades or centuries before the hazard event.
• Dynamic pressures translate root causes into vulnerability. Rapid urbanisation in LICs, for example, forces people to build on flood-prone land or unstable slopes because they cannot afford safe housing.
• Unsafe conditions are the immediate expressions of vulnerability. These are the tangible factors that determine whether people survive a hazard event: the strength of their buildings, their proximity to the hazard, their income, their access to warnings.

Exam Tip: The PAR Model is excellent for 20-mark essays that ask "To what extent are disasters the result of human rather than natural factors?" Use it to argue that vulnerability is socially constructed, then balance with examples where even well-prepared societies are overwhelmed by extreme physical events (e.g., the 2011 Tōhoku tsunami exceeded Japan's engineered defences).

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Hazard Management: The Hazard Management Cycle

The hazard management cycle describes the continuous process of planning for and responding to hazards:

graph TD
    A["Mitigation<br/>Reducing risk before<br/>the event"] --> B["Preparedness<br/>Planning, training,<br/>warning systems"]
    B --> C["Response<br/>Emergency actions<br/>during/after the event"]
    C --> D["Recovery<br/>Rebuilding and<br/>rehabilitation"]
    D --> A

Phase	Examples
Mitigation	Land-use planning, building codes, flood defences, reforestation, insurance schemes
Preparedness	Emergency drills, early warning systems, stockpiling emergency supplies, public education campaigns
Response	Evacuation, search and rescue, emergency medical care, temporary shelters, food and water distribution
Recovery	Rebuilding infrastructure, restoring services, psychological support, economic stimulus, reviewing and improving future plans

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Summary

• A hazard is a natural process with the potential to cause harm; it becomes a disaster when it exceeds a community's capacity to cope
• The disaster risk equation (Risk = Hazard × Vulnerability / Capacity) shows that risk depends on human factors as much as physical ones
• Hazard perception varies with experience, wealth, education, culture and personality, and shapes how communities respond
• Park's Model illustrates the phases of response and recovery, with three possible trajectories
• The PAR Model demonstrates that vulnerability is socially constructed through root causes, dynamic pressures and unsafe conditions
• Effective hazard management follows a continuous cycle of mitigation, preparedness, response and recovery