Understanding Disaster Risk Assessment

Mr Takalani Daniel Makananisa, MA (California) USA, MM-PP (Wits)

PhD CandidateSchool of Geography, Archaeology and Environmental Studies

University of the Witwatersrand,Johannesburg

takiemak@yahoo.co.uk

DMISA

09 -10 September 2015

DISASTER RISK REDUCTION CONFERENCE

A new action agenda for Disaster Risk Reduction

1. ABSTRACT

It is now recognised that disasters either associated to hydrological or environmental changes can have widespread impacts, causing not only harm and damage to people’s lives, buildings and infrastructure, but also impairing economic activity. It is argued that these impacts can generate losses for households, businesses and governments and may result in high financial costs which can be catastrophic in nature, aggravating economic and social development. Disaster risk assessment (DRA) is a key performance area (KPA) that plays an overarching role in disaster risk management continuum and that without generalizable risk assessments data, the intentions of multi-sectorial approach for effective risk management are defeated. Despite the impacts of disasters on nature and society, the use of different formulas to quantify disaster risk shows lack of convergence in the conceptualization of variables that constitute disaster risk assessment. This paper therefore, reviews different pieces of work done by prominent disaster risk researchers. Different journal articles were selected using purposive sampling techniques to review the different methods that are currently employed in quantifying disaster risk assessment. The findings suggest that variables used to define disaster risk formulas have complex characteristics resulting to the use of mathematical statistics and risk index approaches interchangeably. Lack of statistical data leads to non- use of probability models but community based risk assessment. The paper maintains that the calculation for disaster risk be defined in terms of prior and post disasters periods. Therefore recommend that Heijmans and Victoria (2001) formula known for including the component capacity be used to estimate disaster risk preparedness. While the Van Westen at al (2008) formula is used to quantify post- disasters for purposes of reconstruction and rehabilitation.

Keywords: Disaster risk assessment, resilience, damage

2. INTRODUCTION

The world is increasingly becoming a disaster prone planet making living with risk so much of a reality. The South Africa and Mozambique floods (2000), USA 9/11 terror attack (2001), Indonesia Tsunami (2004), Caribbean Hurricane (2005), Pakistan earthquake (2005) Haiti and Japan earth quake (2010), Kenya terror attack (2013), Madagascar locusts (2013), West Africa Ebola crisis (2014), Zimbabwe floods (2014), Peru deforestation (2014), Greensburg Kansas in Oklahoma tornados and twisters (2014), Malawi and Mozambican floods(2015), Argentina floods (2015), Indonesia food insecurity ( 2015), USA California Wild Fire (2015), USA Colorado Animas River Spill (2015), China Potassium Cyanide Gas Explosion Inferno (2015), Bangkok Thailand terror attack (2015) are among some of the world-famous disasters which have caused widespread losses of human lives and damages of massive proportion to both infrastructure and environment. The gradual increase of hazard frequency exposes life, property and environment to serious threats from impending disasters. For the world to respond effectively and efficiently to disasters institutional arrangements for disaster management must be refocused and elevated to the proportional level. Similarly resource allocations biased to promote and intensify research in disaster risk management must become a constitutional obligation.

3. BACKGROUND

Disaster risk assessment is comprised of hazard, element-at risk, and vulnerability assessments. These three components have both spatial and non-spatial characteristics. It is therefore essential to integrate endogenic, exogenic and geomorphology sciences to provide hazard, vulnerability indexes and probability curves. Archive studies may also provide the much needed data, which may be essential during observations, measuring and mapping.

MacFarlane (2006) accentuates that the integration of systems such as Geographic Information Systems (GIS) and Remote Sensing stand

mankind a chance for building generalizable data required for effective disaster risk management. Longley et al (2005) and Van Westen (2005) concur that the use of GIS and Remote Sensing can generate inventories of the past hazardous events, the modeling of hazards, and generation of elements at risk database and integration of these data in the modeling of potential losses.

The advancement of GIS algorithms and analysis or modelling techniques are key revolutionary means to analyse risk, hazards, and vulnerability. The integration of Statistics and Geospatial Technology would advance the search for new methodologies which will inform the framework for disaster risk assessment.

4. RESEARCH METHODOLOGY

This is a qualitative study in which results from different studies were synthesized to determine what would be closest to what the totality of studies say on how to aggregate disaster risk. Purposive sampling was used when selection was made to include well known proponents on disaster risk assessment.

The most important aspect of meta-analysis used in this study is the combination of data from two or more studies and also the look for the presence of heterogeneity in the formulation of disaster risk equations. However the only different is secondary data analyzed were not randomly selected.

5. LITERATURE REVIEW

Hazard, resilience, vulnerability, loss, exposure, capacity, and damage are among the prominently used terms to conceptualize disaster risk assessment. By definition and as cited by Van Westen (2008) and UN-ISDR (2004), an hazard can be considered as natural or human caused phenomenon that may cause injury, loss of life, damage to property and environment. In measuring hazard, Van Westen (2008) accentuated that hazard has probability of occurrence within a specified period of time

and within a given area, and has a measurable intensity. Furthermore Van Westen (2008) is of the view that hazards are analyzed by using quantitative tools to measure the probability and the intensity or severity of the impact, meaning that hazards can be measured by determining the probability of occurrence and its intensity in a given period. Furthermore computational data analysis can be used to determine the size of the area of hazard spread. Van Westen (2008) further argues that hazard quantification is also dependent on factors such as the size and the characteristics of the study area, and that the available data and resources are necessary to inform the level of accuracy when risk is calculated.

Birkmann (2006) and Bank (2003) define vulnerability as a multidimensional process of assessment which takes into account physical, social, economic, environmental, institutional and human factors. According to Okuyama and Chang (2004) vulnerability is estimated using indicators such as physical, social, economic and environmental, which are evaluated qualitatively by assigning weights and combining them with special multi criteria evaluation. Vulnerability curves or fragility curves are relative curves which show the percentage of property value damaged. These curves provide the probability for a particular group of elements at risk to fall within a feasible regions of a certain damage stage (e.g. slight, moderate, complete, and destruction), and whether human lives could be estimated for injury, homelessness and casualties. Calvi et al. (2006) for example argues that vulnerability can be estimated or measured using vulnerability tables only when there is a need to measure relation between hazard intensity and the degree of damage for a group of elements at risk. Resilience on the other hand is defined as a response system to either internal or external factors which includes the degree of risk reduction and recovery time (Tobbin 1999). Kulig (2000) is of the view that resilience is a process which encompasses risk protective factors used by communities in response to threats. Closely connected to the concept of resilience is disaster capacity management which in essence is the manner in which

individuals and local communities cope with disasters. Heijmans and Victoria (2001) argue that capacity is the survivor’s skills, resources and strength that supplement the strategies to self-organize and to cope.According to Van Weston (2008) disaster damage can either be tangible or intangible. Damage estimation can be determined by assessing elements at risk. It is important to classify elements at risk in order to cost them in line with their characteristics. Van Westen (2008) further indicates that damage impacts different elements at risk in different ways, which require that risk of different sectors be calculated separately from the other. Montaya (2003) and Mc Call (2008) argue that to determine elements at risk, GIS maps can be used, where there is no data and that digitized data maps can be derived from analogue maps while Arc Pad can be used to map elements at risk. Montoya (2003) and McCall (2008) accentuate that to determine people at risk, population distribution from census data could be used to determine the population and that characteristics of building such as structural type, construction materials, and compliance to building codes, maintenance and age of the building can be used to determine anticipated damage injury or death in the event of risk occurrence. Grossi et al (2005) accentuates that since the late 1980s, loss estimation has been carried out initially from the early days of insurance and as a results, computer based catastrophe modeling came to existence to advance information technology and GIS in the calculation of disaster risk. The RADIUS (Risk Assessment tool for Diagnosis of Urban Areas against Seismic Disasters) methods for loss estimation was invented to perform aggregated loss estimations to estimate the number damaged building, causalities and injured people RADIUS (1999)

5.1 HAZARD RISK ASSESSMENT

Hazard is a potentially damaging physical event, phenomenon of human activity that may cause loss of life or injury, property damage, social and economic disruptions or environmental degradation UN-ISDR, 2004. Overtime communities develop ways and means to strengthen their resilience against the sorts of hazards which confronted them over a period of time. Ronan and Johnson (2005) emphasize that the construct of resilience has a bearing on first and foremost communities knowing their priority hazards and risks associated. Heijmans and Victoria (2001) define risk as Risk = (Hazard × Vulnerability) / Manageability or

Capacity denoted by R = (H × V) / C

The formulas that are used to calculate disaster risk are themselves a reflection of how different researchers in disaster risk assessment perceive the disaster risk. What seems interesting is that almost every one of them agrees on two things which are (a) a risk exists only if there is vulnerability to the hazard posed by a natural event and (b) that risk can be calculated if first and foremost hazard is identified and then assesses to obtain the extent of its magnitude or size

IUGS (1997) express disaster risk as Risk = Probability × Consequence……………1

The International Union of Geological Sciences (IUGS) uses mathematical statistics approach based upon the analysis of observed natural disasters for over a long period of time by calculating risk in the form of a product of the probability of occurrence of a hazardous event and the consequences of such an event for receptors (the magnitude of impact resulting from realization of the hazard). Risk is expressed as (IUGS, 1997)

ISDR (2004) define disaster risk as: Risk = Hazard × Exposure × Vulnerability…2

The United Nation International Strategy for Disaster Reduction (ISDR) gives a picture that to determine disaster risk a product of three variables which are hazard frequency, level of exposure and level of vulnerability resulting on the degree of exposure.

GTZ (2002) define disaster risk as:

Disaster Risk = Hazard × Vulnerability…….3

In equation 3 GTZ (German Gessellschaft für Technische Zusammenarbeit) calculate disaster risk as the product of the two factors, hazard and vulnerability. According to Wisner, et al (2006) and Heijmans and Victoria (2001) most literature express the formula to calculate Disaster Risk as: Risk = Hazard × Vulnerability

According to Van Westen et al (2008) to quantify disaster risk, loss should also be estimated as a resultant element. The risk quantification approach aims at expressing risk in quantitative terms as probabilities and frequencies of expected loss. The analysis of loss takes into consideration loss of function like electricity load shedding, tangible losses in monetary terms (replacement value) and also intangible losses such as lives and injuries, and environment quality.

In trying to understand risk assessment, Geo Scientists led by Van Westen came to a conclusion that to calculate risk the generally used formula of the product of hazard and vulnerability must include amount to aggregate disaster risk Van Westen et al (2005, 2008)

Van Westen at al (2005) Risk = Ʃ [Hazard × Vulnerability × Amount]………..4

The Van Westen formula deduce that to calculate risk the product of hazard, vulnerability and amount should be found. The formula is based on the framework which takes into consideration the environmental factors, triggering factors, hazard inventory and elements at risk.

Figure A: Van Westen et al (2005) Framework based on the use of GIS for multi-hazard risk assessment.

The multi-hazard risk assessment framework in fig . A , above shows that :-

Black A of the multi-hazard framework is composed of datasets for maps, triggering factors and elements at risk. Block B deals with susceptibility assessment for endogenic and exogenic empirical factors. The data is divided into two parts, one for modeling hazard initial areas and the other for modeling potential of spread of endogenic and exogenic empirical factors.

Block C of the multi-hazard framework deals with assessment of hazard magnitude and frequency of the probabilities that a given area will be affected given the intensity and probability of time taken for hazard to occur and magnitude.

Block D is vulnerability assessment which indicates approaches such as vulnerability curves, vulnerability matrix used for integrating elements at risk. In Block E block specific risks are calculated for different situations related to hazard type, intensity, triggering events and types of elements at risk. The integration is both qualitative and quantitative.

Block F of the multi-hazard framework deals with the quantitative risk approach for which the results are plotted for risk curves, and expected curves against the probability of occurrence for each hazard. For each hazard, all unknowns generate two loss curves one for maximum and the other for minimum losses on each return period of triggering events or associated probability.

Block G of the multi-hazard framework deals with hazard index and vulnerability index. The last block in the multi-hazard assessment is Block H, which deals with the use of the gathered hazard data for risk reduction projects, planning and development, education, warning and environmental management.

5.2 INTEGRATED DISASTER RISK EQUATIONS

Term Definition FormulaPr

ior

Dis

aste

rs

Occ

urre

nce

HAZARD ASSESSMENT

PRIOR DISASTER (PREPAREDNESS)

(Management and Mitigation)

Heijmans and Victoria (2001)R = (H × V) / C\MRisk Resilience (Rr) = Hazard × Vulnerability/Capacity

R(r) =( H×V)/C

Post

Dis

aste

r O

ccur

renc

e

RISK ASSESSMENT

( POST DISASTER (RECONSTRUCTION )

(Reconstruction and Rehabilitation)

IUGS (1997)Risk = Probability × Consequences

ISDR (2004)Risk = Hazard × Exposure × Vulnerability

Wisner (2006)Risk = Hazard × Vulnerability

Van Westen et al (2008)Risk = Ʃ[ Hazard × Vulnerability × Amount]

Proposed Formula

D(r) = H × V × D(e)

Table 1 Hazard risk assessment for preparedness and reconstruction

6. CONCLUSION

The study contends that there is a disjuncture or an inverse relationship between the perceptions that disasters are as old as mankind and level of study and research in disaster risk science. The intricacies of the relationship between disaster risk management and development require integration of various science disciplines to demystify the misconceptions and advancement of hazard risk assessment approaches.

The reality of living with hazard risk is becoming more concrete than otherwise perceived differently due to the perceptions such as certain types of hazards are restricted to certain geographical regions. This perception or hypothesis needs to be tested further as it trivializes and narrows the potential to understand that hazard initial point and potential scale of hazard spread overtime may expose elements at risk that are miles and miles away.

For mankind to continue in its journey, innovative ways to live with disaster risk must be intensified. This is more than ever, a joint responsibility for researchers, academic institutions, government, private sectors and non-governmental organizations.

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