Geoscience Reference
In-Depth Information
15.1
Introduction
A natural disaster, by definition, is
some rapid
,
instantaneous
or
profound impact of
the natural environment upon the socio-economic system
(Alexander
1993
).
Cyclones, tornadoes, hurricanes, landslides, earthquakes, tsunamis, volcanic
eruptions, and floods are among the natural phenomena ravaging our planet each
year, causing immense loss of life as well as suffering. The number of natural
disasters and the sizes of the populations affected by such events have been growing
(Schultz et al.
1996
; Nagurney and Qiang
2009
). Scientists are warning that we can
expect more frequent extreme weather events in the future. For instance, tropical
cyclones—which include hurricanes in the US—are expected to be stronger as a
result of global warming (Sheppard
2011
; Borenstein
2012
).
The amount of damage and loss following a disaster depends on the vulnerability
of the affected region, and on its ability to respond (and recover) in a timely manner,
also referred to as
resilience
. Disasters are believed to occur when hazards meet
vulnerability (Blaikie et al.
1994
). Hence, being prepared against potential disasters
leads to reduced vulnerability and a lower number of fatalities. As the institutional
experts say: “during a natural disaster, one has only two options: to become a
victim, or to become a responder” (Alvendia-Quero
2012
). Thus, viable resiliency
against natural disasters has to be achieved and sustained not only by the cognizant
organizations, from governmental to humanitarian ones, and private enterprises, but
also by individuals.
Disasters necessarily affect regions and pose challenges in all phases of disaster
management. Vivid examples of disasters such as Hurricane Katrina in August
2005, the Haiti earthquake in January 2010, Fukushima in March 2011, Superstorm
Sandy in October 2012, and tropical cyclone Haiyan in November 2013 have
challenged researchers, practitioners, as well as policy-makers and other decision-
makers and have yielded multidisciplinary approaches to models, methods, and
techniques with major contributors being from regional science (cf. West and Lenze
1994
; Israelevich et al.
1997
; Rose et al.
1997
; Okuyama et al.
1999
; Cho
et al.
2001
; Okuyama
2004
; Rose and Liao
2005
; Ham et al.
2005
; Greenberg
et al.
2007
; Grubesic et al.
2008
; Reggiani and Nijkamp
2009
; Nagurney and Qiang
2009
; Rose
2009
, among others). Background on the quantification of the economic
impacts of disasters under risk and uncertainty can be found in the topic by Dacy
and Kunreuther (
1969
) (see also Kunreuther (
1967
)) with an updated treatment in
Kunreuther and Michel-Kerjan (
2012
) and with a critique of the former book by
Okuyama (
2003
).
The complexity of disaster relief supply chains, in turn, originates from
several inherent factors. The associated large demands for relief products pose
challenges to the logistics planning authorities (Lin
2010
) with the level of uncer-
tainty adding to the complexity. According to Beamon and Kotleba (
2006
), there
may exist irregularities in the size, the timing, and the location of relief product
demand patterns. In addition, disaster-driven supply chains are, typically,
formed as incident-responsive ones with temporary configurations of disparate
resources. Commercial supply chains, on the other hand, often involve supplierbuyer
