Provided for non-commercial research and educational use only.
Not for reproduction or distribution or commercial use.
This article was originally published by IWA Publishing. IWA Publishing recognizes
the retention of the right by the author(s) to photocopy or make single electronic
copies of the paper for their own personal use, including for their own classroom use,
or the personal use of colleagues, provided the copies are not offered for sale and
are not distributed in a systematic way outside of their employing institution.
Please note that you are not permitted to post the IWA Publishing PDF version of
your paper on your own website or your institution’s website or repository.
Please direct any queries regarding use or permissions to firstname.lastname@example.org
Linking drought characteristics to impacts on a spatial
and temporal scale
Christos A. Karavitisa,*, Demetrios E. Tsesmelisa, Nikolaos
A. Skondrasa, Demetrios Stamatakosa, Stavros Alexandrisa,
Vassilia Fassoulia, Constantina G. Vasilakoua, Panagiotis
D. Oikonomoub, Gregor Gregoričc, Neil S. Griggband
Evan C. Vlachosb
Department of Natural Resources Development & Agricultural Engineering, Agricultural University of Athens,
11855 Athens, Greece
*Corresponding author. E-mail: email@example.com
Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, CO 80523, USA
Environmental Agency of the Republic of Slovenia, Ljubljana, Slovenia
Drought is a complex natural phenomenon that lacks a universally accepted definition, thus it is difficult to con-
front holistically. Several efforts have been made towards managing the widespread and catastrophic drought
impacts. In this quest, the concept of vulnerability to drought seems to offer some significant potential. In the pre-
sent attempt, a standardized drought vulnerability index (SDVI) is presented, applied, and spatially visualized
through geostatistical methods on a country scale. Greece, experiencing frequent and intense droughts, was
selected as the study site. In an effort to link drought characteristics to impacts, the index incorporates water
supply information, demand data, the state of the relevant water infrastructure and climatic parameters represented
by the standardized precipitation index. The index showed potential in portraying various vulnerability states and
followed satisfactorily the vulnerability fluctuations in Greece in relation to recorded drought hazard dimensions
and impacts. The SDVI may be considered as a first step for the emergence of an integrated SDVI with multi-
scalar applications in environmental research and decision-making. It is believed that improving techniques in
index formulation may complement more reasonable and acceptable solutions to water challenges posed by
droughts and help avoid a drifting sense of continuous ‘water crises’.
Keywords: Drought impacts; Drought management; Drought vulnerability index; Greece; Spatial
visualization; Standardized precipitation index; Water resources
Water Policy 16 (2014) 1172–1197
© IWA Publishing 2014
Equitable water use and the search for integrated water resources management face continuous
changes in values, and in societal and environmental structural transformations aggravated by exogen-
ous shifts such as climatic anomalies and systemic alterations (Grigg, 1988;World Water Assessment
Programme (WWAP), 2009;Priscoli, 2013). Such fundamental changes have created a context of high
complexity, globalization, turbulence, vulnerability and uncertainty, where decision-making requires re-
examination of the traditional water resources planning and management considerations. Access to ade-
quate water is becoming a highly contested issue, further exacerbated by traditional values and customs,
religious considerations, historical factors and geographical vagaries (Grigg, 1996,2008;Vlachos,
2004;Cancelliere et al., 2005). Furthermore, overpopulation, hyper-urbanization and natural hazards
compound problems associated with stress for water of adequate quality and quantity. Extreme
events such as earthquakes, hurricanes, flood and droughts –often cited as natural hazards –may
leave a legacy of effects and consequences on both environment and societies. Drought is a part of
such largely unpredictable natural hazards, but it seldom comes as a spectacular or sudden onslaught
(Karavitis, 1999b;Vlachos & Braga, 2001;Grigg, 2008). Damage elicited by drought evolves and pro-
pagates, often subtly, over an extended time period. Early on in the literature, drought was also referred
to as an ‘interaction and combination between physical processes and human activities’(Changnon &
Easterling, 1989). Such processes are extremely stochastic in nature and, thus, problematical for reliable
prediction (Karavitis, 1999a;Cancelliere et al., 2005;Mishra & Desai, 2005;Sullivan & Huntingford,
2009;Sullivan, 2011). However, cumulative experience from scientific investigations of recent decades
is indicating that given a certain period of time in a given locale, the occurrence of an uncertain event,
such as a drought, becomes a certainty (Karavitis, 1999a;Zou et al., 2005;Woodhouse et al., 2010).
Thus, a drought vulnerability approach has gained ground in the context of such an emerging frame-
work. In the upcoming paradigm, the global temperature increase, even by a small fraction, may
disrupt the natural balance of the world’s climate and thus may result in changes of the water cycle
inter-components (Vairavamoorthy et al., 2008). According to the Intergovernmental Panel on Climate
Change (IPCC) (2007,2013), droughts are expected to increase in frequency, intensity and duration in
various regions worldwide, including the subtropics and mid-latitudes such as the Mediterranean area.
However, Sheffield et al. (2012) reported that the increases in global drought patterns have been over-
estimated and there has been little change over the past 60 years. Either way, drought contingency plans
should always be in place. The Mediterranean region, cradle of many civilizations and springboard of
life for many populations, may once again become a focal point of interest and concern. Expanding
populations, metropolitan concentrations along its meandering coasts, industrialization, modernization,
escalating tourism, and competing and conflicting demands on scarce water supplies make for a highly
complex socio-economic environment. The salubrious climate, fragile lands, historically contestational
socio-political forces and a vulnerable ecosystem: all have been converging towards a challenging con-
text of concern and crisis. Such a context is further exacerbated by forces of globalization and by the
rapidity of change. In this emerging framework, the drought vulnerability approach has gained signifi-
cant ground as an essential management tool. In the present attempt, a standardized precipitation index
(SPI)-based standardized drought vulnerability index (SDVI) was developed and presented on a country
scale. Greece, as part of the Mediterranean region, has been selected as a case study for the index appli-
cation and demonstration.
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–1197 1173
2. Drought and vulnerability
The drought phenomenon poses ubiquitous obstacles for systematic planning and management
responses. One source of difficulty arises from the fact that the concept of this natural hazard remains
ambiguous and elusive, since it tries to incorporate physical processes as well as highly complex inter-
actions with the surrounding environment. Furthermore, catastrophic and widespread drought impacts
prompt strong demands for immediate and effective management actions. Such demands for action
become quite problematic when drought management responses have to be applied to already stressed
environments (Drought Management, 1986;Karavitis, 1999b;Mishra & Desai, 2005;Andreu et al.,
2006;Barraque et al., 2008). Drought is a frequent event that occurs in a number of regions worldwide
regardless of their usual climatic conditions (Yevjevich et al., 1983;Grigg, 1996;Karavitis, 1999b;
Bordi et al., 2006;Eriyagama et al., 2009;Karavitis et al., 2012a,b). Drought depends on antecedent
conditions and its characteristics display great spatial and temporal variability. The severity of the recent
US drought has received extensive media coverage (Grigg, 2014). The phenomenon always attracts both
public and interdisciplinary scientific attention, since it causes a plethora of social, economic and
environmental impacts (Yevjevich et al., 1983;Karavitis, 1992;Rossi et al., 1992;Wilhite et al.,
2000;Cancelliere et al., 2005;Sheffield et al., 2012). Hagman (1984), in one of the early drought
impacts reports, pointed out that drought is a complex natural event affecting human activities more
than any other natural hazard. Commenting more recently, Bruce (1994),Easterling et al. (2000) and
Ding et al. (2010) also report that droughts have caused losses that are counted in billions (10
US dollars worldwide.
A precise, unambiguous definition of drought remains elusive (Yevjevich et al., 1983;Karavitis,
1992,1999a;Grigg, 1996;Wilhite, 1997;Cancelliere et al., 2005;Karavitis et al., 2012a,b;Shatanawi
et al., 2013). One source of confusion in devising an objective definition may be that drought implies a
variety of things to various professionals according to the specialized field of study (meteorology,
hydrology, water resources, agriculture, etc.). A second problem is elicited because the definition of
drought is strongly related to the geographical, hydrological, geological, historical and cultural traits
of a given locale. A third factor is the difficulty in modifying existing drought terminology according
to updated techniques and practices (Drought Management, 1986;Salas, 1986;Grigg & Vlachos, 1990;
Karavitis, 1992,1999a;Karavitis et al., 2012a,b). However, drought is usually defined as a precipi-
tation deficit over an extended period of time (National Drought Policy Commission (NDPC), 2000;
Cancelliere et al., 2005;Wilhite et al., 2006;Eriyagama et al., 2009). Drought might be also defined
as ‘a usually unexpected and unpredicted time period of abnormal dryness which affects water
supply’(Grigg, 1988). Central to this quest, a general definition of drought may evolve. Thus, a broader
and possibly more operational definition of drought may be ‘the state of adverse and wide spread hydro-
logical, environmental, social and economic impacts due to less than generally anticipated water
quantities’(Karavitis, 1992,1999a). Such water deficiencies may primarily originate from precipitation
decreases, usually accompanied by physical and/or management inefficiencies in water supply systems,
most of the time, over a large area. It is believed that such a drought definition may lead towards linking
drought characteristics such as duration and frequency to impacts and then estimating the vulnerability
of an area to drought. In this regard, various concepts have been used to exemplify the prevailing con-
fusion among terms, which signify ‘dry environments’or water deficiencies. Early on, Vlachos (1982)
presented four different terms that are important for some initial separation among the types of water
deficiencies in relation to anthropogenic interventions, which are refined and elucidated in Figure 1.
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–11971174
Hence, further developing such terms it may be noted that: aridity is referred to as a permanent natural
condition, representing a stable climatic feature of a given region. Drought may be understood as a tem-
porary mostly climatic phenomenon, regular and/or unpredicted. Water shortage is associated mainly
with small areas of water deficiency created usually by human activities. Finally, desertification is prin-
cipally a man-made phenomenon altering significantly the ecological regime. It has been suggested that
all the above terms and definitions associated with dryness may be considered as a part of a larger pro-
cess named: ‘xerasia’(Figure 1). The boundaries among these four categories are gradual depicting their
interdependencies and complex nature signifying, for example, that a drought may also have not only
natural but also some anthropogenic connections. Nevertheless, whatever the term and the overall con-
text, drought should be associated with its impacts at a given locale. Such association including special
technological, economic and societal traits may estimate the area’s vulnerability to various ‘drought’
Drought has short- and long-range (usually cumulative) impacts in virtually all types of activities
related to water, economy and society. Two methodological approaches may be underlined in order
to study and assess drought impacts. In the first one, the impact approach, a climatic event (drought)
operates on a certain ‘exposure unit’(activity) producing an impact. This is a cause and effect approach.
The second one, the interaction approach, suggests that various processes (physical, economic or
societal) may influence the ‘exposure unit’and the impacts are embedded and interrelated to the
‘exposure unit’. In other words, environment, policies, economy and society combined negatively on
a given activity may create a crisis. In recent decades, the interaction approach started to be considered
as more realistic by presenting the impacts as ‘orders of interactions’(Wilhite et al., 1987;Karavitis,
1992;Grigg, 1996). In this regard, a classic first broad categorization of impacts was in a series of
first-, second- and third-order impacts (Changnon & Easterling, 1989). First-order impacts are associ-
ated with changes related to the hydrologic cycle (i.e. precipitation, runoff, stream flow and
groundwater). Second-order ones usually influence human activities such as agriculture, industry,
Fig. 1. The ‘Xerasia’processes matrix (adapted from Vlachos, 1982;Karavitis, 1992).
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–1197 1175
urban users and transportation. Finally, third-order impacts may be understood as adaptations to first-
and second-order impacts (i.e. income losses, adjustments in life style and rationing). Such impact dis-
tinctions are extremely important so as to produce a drought management methodology. At the same
time, drought impacts should be categorized according to a concise and comprehensive framework.
Thus, any classification scheme becomes crucial, since it may lead towards potential drought responses
in an implementable decision-making process.
In general, the impact’s magnitude on an area is affected by the density of human activities, needs,
demands, level of socio-economic structure and the environmental linkages (Eriyagama et al., 2009).
The 2012 drought in the USA produced severe hydrological, economic, environmental and social impacts
and may be classified as the worst since the 1930s Dust Bowl (Grigg, 2014). During the 1989–1990 great-
est drought on record for Greece, the impacts were devastating, as losses escalated to about 1.5 billion
) USD in 1990 prices (Karavitis, 1992,1999b). Wu et al. (2011) provide a short but quite explanatory
description of drought impacts emphasizing the great losses, mostly economic, that occur during such an
event, while Ding et al. (2010) provide a more detailed one of the drought economic impacts. Impacts
trigger the societal responses to drought. The more holistic the responses, the more effective the drought
mitigation may be. Hence, integrated water resources management (IWRM) should be used as the general
context for comprehensive drought management approaches. The articulation of marks and threshold
drought conditions can measure progress, performance and products of such management approaches
(Grigg, 1996,2008;Karavitis, 1999a;Vlachos & Braga, 2001). The major challenge for any drought miti-
gation policy in order to confront the impacts may be the development of comprehensive and effective
drought management schemes. Such schemes should be based on proactive strategies incorporating
pre-drought planning, drought responses and post-drought activities (Grigg & Vlachos, 1990,1993;Kar-
avitis, 1992,1999a;Karavitis et al., 2012a,b). If impacts are anticipated, then a responses plan may be set
in advance. The core of a scheme for a drought responses plan may be composed from short- and long-
range responses. Short-term responses should be initiated and terminated according to the drought dur-
ation, while long-term ones should be designed and implemented in advance of a drought event. Thus,
impacts should be anticipated both spatially and temporally and initiate management interventions on cer-
tain vulnerability thresholds. In other words responses may also lead to impact classification.
An image of a comprehensive management scheme is presented in Figure 2. Given such consider-
ations, a drought responses plan should be classified in the following parts (Yevjevich et al., 1983;
Grigg & Vlachos, 1990,1993;Grigg, 1996;Karavitis 1992,1999a,2012): Supply augmentation
measures. Such measures should examine all the potential water supply resources for the area. They
should already be in place before a drought (base and emergency supply). Perhaps with the exception
of water purchases, systems supply augmentation should be avoided during the drought as a crisis man-
agement action. The existing system designed after long-range planning should be capable of operating
under drought conditions according to contingency plans; it should also be well maintained and
improved in order to minimize the losses: Demand management/reduction measures. These responses
should aim towards water consumption patterns according to conservation principles. The long-term
measures should be in place according to proactive planning (legal measures, zoning/land use, landscape
changes, agricultural changes such as changing to less water consumptive crops, irrigation scheduling,
etc.). The short-term measures should be initiated during and terminated after the drought (water restric-
tions, reduction of uses, pricing, etc.). The implementation and enforcement framework for demand
reduction measures should also be in place (economic, legal and institutional). All in all, such measures
should be implemented orderly and timely according to contingency plans; and finally Impact
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–11971176
minimization. Such responses should concentrate on anticipatory strategies, relief and recovery
measures. The framework for such responses should already be in place (economic, legal and adminis-
trative). Spread of drought risk, damage recovery and compensation should be some of the measures
considered, according to a drought master plan.
In order for any responses to be applied, existing problems unquestionably must be resolved about the
onset, the areal extent and the severity of a drought. In this quest drought index methods may be used.
These methods characterize a drought according to a specific index. Thus, a drought index should pri-
marily be an objective measure of the system status that may help in identifying the onset, increasing or
decreasing severity and termination of a drought. Nevertheless, no single indicator or index alone may
precisely describe the onset and severity of the event. Numerous climate and water supply indices are in
use to present the severity of drought conditions. In the literature different indices have been discussed
and applied, with the SPI (McKee et al., 1993), the Palmer Drought Severity Index (Palmer, 1965) and
the Crop Moisture Index (Palmer, 1968) being three most usually applied. Although none of the major
indices is inherently superior to the rest in all circumstances, some indices are better suited than others
for certain uses (Karavitis et al., 2012a,b). All in all, the type of index, local conditions, data availability
and validity usually lead to the index selection (Nardo et al., 2005;Singh et al., 2009;Skondras et al.,
However, apart from those event-related indices, a few more complex ones were developed, some of which
refer to the vulnerability concept (Briguglio & Galea, 2003;Pratt et al., 2004;Fussel, 2010;Ganase &
Fig. 2. Comprehensive Management Scheme (adapted from Yevjevich et al., 1983;Grigg & Vlachos, 1990,1993;Karavitis,
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–1197 1177
Teelucksingh, 2011). The following indices serve as examples (Kaly et al., 2004;Skondras et al., 2011;
Ganase & Teelucksingh, 2011): The Composite Human Vulnerability Index –by the Indian Institute of Tech-
nology in Bombay; The Key Indicators for Global Vulnerability Mapping –by the United Nations
Environment Programme; The Coral Reef ‘Vulnerability Index’of Exposure to Climate Change –by Green-
peace; The Environmental Vulnerability Index –by the South Pacific Geoscience Commission; and the
Climate Vulnerability Index –by Sullivan & Huntingford (2009). Increasingly, the term ‘vulnerability’
appears in the environmental change literature (Adger, 2006;Gallopin, 2006;Janssen, 2006;Janssen &
Ostrom, 2006). It is associated with the evolution in environmental studies from impact analysis, to crisis
assessment, to vulnerability evaluation reflecting the large number of critical variables involved, cumulative
consequences and multi-dimensional sources of threats, hazards and unanticipated consequences. Even more
vulnerability has been tied to security in all its forms, such as food security, economic security, environmental
security and political security, all the way to individual security (Adger & Kelly, 1999;Adger, 2000,2006).
This dynamic evolution coincides also with the transformation from simple, linear models, to more complex,
potentially circular, feedback, heterarchical and non-linear approaches. When combined with ‘volatility’it
becomes the current potent theme of expanding time-scale units of analysis and assessment. Nevertheless,
the term vulnerability as well as its relative ones –resilience and adaptive capacity –have proved difficult
to be conceived and applied (Walker & Meyers 2004;Füssel, 2007). These difficulties usually derive from
the fact that vulnerability has been used by a plethora of authors in a variety of disciplines including social,
economic and environmental sciences (Adger, 2006;Gallopin, 2006). As a result, a rich literature exists
and a great number of definitions are offered (WeAdapt, 2013). Throughout the majority of vulnerability lit-
erature, regardless of the background, two major issues surface: vulnerability generally has a human- or
society-centered perspective; and a link to cope with and a capacity to handle stress or perturbation is usually
present (National Research Council (NRC), 2001;Preston & Stafford-Smith, 2009;WeAdapt, 2013).
Such issues are usually included in the various definitions. Vogel (1998) defined vulnerability as ‘the
characteristics of a person or group in terms of their capacity to anticipate, cope with, resist and recover
from the impacts of natural hazard’, while Langeweg & Gutierrez-Espeleta (2001) expressed it as ‘the
exposure to hazard by external activity (e.g. the climatic change) and coping capacity of the people to
reduce the risk at a particular point of time’.IPCC (2001) specialized the term, stating that:
‘Vulnerability is the degree to which a system is susceptible to, or unable to cope with, adverse effects
of climate change, including climate variability and extremes. Vulnerability is a function of the char-
acter, magnitude, and rate of climate variation to which a system is exposed, its sensitivity, and its
Expanding it again, Turner et al. (2003) specified vulnerability as ‘the degree to which a system, sub-
system, or system component is likely to experience harm due to exposure to a hazard, either a
perturbation or stress/stressor’.
Overall, vulnerability is not a static systemic state but a dynamic one. It changes temporally following
the various changes that occur in the system of interest (Adger & Kelly, 1999;Leichenko & O’Brien,
2002;Dalziell & McManus, 2004;Luers, 2005;Miller et al., 2010). In a similar manner, the vulner-
ability definitions are correspondingly not static. They also change following the changes of human
perspectives regarding the systemic functionality and the relations occurring between systems and com-
ponents in a variety of scales. Changes of perspective and efforts in the field of vulnerability include the
integrated forms of Social-Ecological Systems –SES (Berkes & Folke, 1998;Chapin et al., 2009;Folke
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–11971178
et al., 2010) and the principles of ‘Panarchy’described by Holling (2001) and Gunderson & Holling
(2002). The current attempt is focusing primarily on the technical/engineering elements, rather than
the more comprehensive and/or general versions of the vulnerability definitions. All in all, the assess-
ment of risk related to water resources is highly reliant on society’s vulnerability to water-associated
hazards. On top of that, the uncertainty created by climate variability and change also has an important
role (United Nations Educational, Scientific and Cultural Organization (UNESCO), 2006). Hence, based
also on International Strategy for Disaster Reduction (ISDR) (2004), vulnerability analysis may be con-
sidered to compose social, economic, physical and environmental factors and to be expressed of two
basic elements and as such described by:
Vulnerability ¼Risk identification Impacts assessment (1)
This expression includes exposure, but sometimes the role of exposure is not clear. Exposure may be
considered both as a vulnerability component as well as the relation that connects the given hazard to the
system of interest (Gallopin, 2003). In both cases, no hazard exposure implies no vulnerability. Vulner-
ability assessments may become quite challenging tasks, since not all the systemic components present
the same vulnerability on a specific hazard and therefore assumptions (weights) should be made in order
for the average systemic vulnerability to be measured (Turner et al., 2003). Measuring the vulnerability
of an area or a system is even more challenging since the ability of a particular system to cope with
potential stresses or the pressure required for an ecological threshold to be crossed cannot be exactly
determined in space and time (Gunderson & Holling, 2002;US Climate Change Science Program
(USCCSP), 2009). Drought mitigation, then, is part of answering not only the traditional goals of
equity, efficiency and environmental integrity, but more complex questions of critical exposure to a
richer menu of challenges as well as coping and adapting through resilient and robust political insti-
tutions and other structural organizations.
All in all, the vulnerability term may be expressed by two basic elements: hazard and impacts. Thus,
without a hazard or something to be affected, no vulnerability is implied. Exposure is also considered to
be part of vulnerability (Bohle, 2001) though sometimes it is conceived as the relation that connects the
system to the given hazard (Gallopin, 2003). Generally, the term of vulnerability refers to the factors –in
a holistic concept –that affect both the system’s likelihood to be harmed and the system’s ability to cope
It has to be stated that drought vulnerability depends both on the sector of concern the drought is
applied on (agriculture, society, etc.) and the system of interest as the enabling environment. Such a
term may include current infrastructure, water governance practices, management actions, economic
level, environmental conditions and existing social relationships and context. Using the presented ration-
ale an effort was made to relate drought impact sectors and vulnerability. Holistic Drought management
principles should be followed for such an endeavor. A similar approach has been attempted delineating
strategies and tactics for comprehensive drought management by Karavitis (1999a). Since strategies and
tactics aim predominately at changing or minimizing drought vulnerability in a spatial and temporal
scale through focused responses, the approach has been further elaborated and targeted towards identi-
fying a system’s vulnerability components to drought. Such an outcome is presented in Table 1.
It is believed that the scheme displayed in Table 1 may lead towards connecting drought impacts with
vulnerability, their categorization both in space and in chronological sequence, and at the same time pro-
vide a means to enhance decision-making in order to mitigate the multiple and diversified drought
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–1197 1179
effects. In this context a pertinent index may be of essence and the methodological steps for its devel-
opment are demarcated in the following.
3.1. Area of application
Greece has an area of 1,31,957 km
with coastlines of 13,676 km and 10,815,197 inhabitants
(Census, 2011). It is located in south-eastern Europe and is part of the Mediterranean region. The Med-
iterranean region as a whole is ecologically fragile and seriously endangered by existing social and
economic trends, where water is used mostly in an unsustainable manner (Karavitis & Kerkides,
2002;Vicente-Serrano et al., 2004,2010;Llasat-Botija et al., 2007;Gaume et al., 2009). In addition,
vulnerability raises the question of ecosystem resilience, especially because of periodic extreme events
such as droughts and floods, as well as increasing anthropogenic disturbances (Karavitis et al., 2012a,b).
The weather patterns range from hot and dry summers to cool and rainy winters. Thus, combined
Table 1. Impacts and vulnerability interdependencies using integrated drought management principles.
stress and strains
Decision Support Systems (DSS).
Multi Criteria Decision Analysis (MCDA).
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–11971180
with the country’s mountainous character with extreme morphological disparities, for example in the
area of mount Olympus (central Macedonia), where in a distance of only 20 km from the seashore
the elevation climbs to 3,000 m, and its high dispersal (due to the great number of islands –more
than 3,000), it produces quite a diversity of microclimates, ecosystems and landscapes. This encourages
tourism, especially during the summer seasons, which is the area’s main economic activity. Agriculture
is the second significant economic activity of the country. Agricultural areas occupy almost 38,540 km
or 20.38% of the total land area (NationMaster, 2008).
Those activities are highly dependent on the available water resources of the country. Such resources
may reach 58 10
per year; while almost steadily in recent decades, the country’s total water con-
sumption has been about 12% of the total annual water availability (Karavitis, 1999b;Barraque et al.,
2008). This fact could signify that Greece should not ideally present water shortages or any other water
stress-related issues. Nevertheless, Greece has not developed the required infrastructure level in order to
use to a greater percent its large surface water resources potential, while it overexploits the limited
groundwater reserves with the accompanying effects of their contamination and sea-water intrusion
(Karavitis, 2008). This makes the country highly dependent on the annual rainfall patterns with the
result that any precipitation deficit may cause, most of the time, significant impacts on the economy,
societal activities and the environment. A series of such deficits has occurred during recent decades
(e.g. 1989–90, 1993, 2000, 2003 and 2007) characterizing Greece as drought prone, exposing the econ-
omy to threats and leaving it vulnerable to losses (Tsakiris & Vangelis, 2004:Livada &
Assimakopoulos, 2007;Loukas et al., 2007;Vasiliades et al., 2009).
3.2. SPI-based SDVI description
The SDVI is a composite index that has been developed, within the context of the Drought Manage-
ment Centre Project (DMCSEE), by the Agricultural University of Athens research team as part of its
partner obligations. It was first presented during the project’s Fifth Meeting and Training at Lasko,
Slovenia, on 28 June–1 July 2011 (Karavitis et al., 2011a,2012a,b;DMCSEE, 2012,2013).
Following the rationale elaborated in Table 1,Figure 3 was developed to visualize the relationship
among impact sectors and drought vulnerability components. Based on Figure 3, it may be pointed
out that the SDVI aims at describing an attempt for a potential integrated estimation of drought vulner-
ability by enclosing Meteorological, Hydrological, Social and Economic Drought manifestations
(Figure 3). Hence, the SDVI includes six components in four categories or aspects as follows.
1. Incorporation of the SPI 6 and SPI 12 values.Wu et al. (2007) reported that in arid and semi-arid
regions SPI values with scales up to 12 weeks are distributed non-normally. On the contrary, the
6-month and above scale results in the SPI values being normally distributed. They stated that the
SPI user should be careful when adapting short time scale SPI values in such locales. They also pointed
out that the discussion of short-term drought in dry climates may be meaningless, since zero rainfall is a
normal part of the local climate. A 6-month SPI may be very effective showing the rainfall patterns over
distinct seasons, indicating medium-term trends. Hence, the 6 month and above SPI values may also
display abnormalities in stream flows and reservoir storage (Tsakiris & Vangelis, 2004). Furthermore,
and possibly being a more specific argument, annually arid and semi-arid climatic conditions usually
exhibit an extended distinct dry period of at least a few months; thus, the SPI values of 6 months and
above time scale seem more useful. All in all, precipitation patterns in most regions usually affect the
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–1197 1181
surface waters, as well as the replenishment of the aquifers. Thus the SPI 12 becomes central, since
urban water supply and sometimes irrigation may greatly depend on annual reservoir storage and/or
aquifer status (Karavitis et al., 2012a,b). In this context, SPI 12 may represent mostly the non-agricul-
tural water availability (hydropower, households and tourism) and SPI 6 may portray the agricultural
(irrigation) availability, respectively, particularly for rain-fed crops. However, it is believed that their
mutual incorporation enhances interconnections, operability and may contribute to more sound out-
comes. The SPI values are calculated on local scale (based on each meteorological station).
2. Supply and demand that describe the deficits in supplying capacity (including network losses) and
in demand coverage based on relevant data. Their magnitude depends on the available quantity of
water, existing water consumption patterns, reported uses, and demographic, social and technical
3. Impacts that describe the losses transformed into monetary units. Such losses might have been caused
by supply–demand deficiencies. Measures on the demand side of the supply-minus-demand economic
drought equation have the basic objective to trim the water use of the least unit impact, provided the
legal consent conditions permit it. The resulting impacts are primarily focused on economic costs
and production losses transferred to the society. The environmental impacts are not analyzed in the cur-
rent effort, unless they can have a direct monetary representation. It is believed that a more specialized
analysis should be applied in order to quantify them in a pertinent research approach.
4. Infrastructure that describes the level of the current in-operation water infrastructure in association with
the divergence from the designed performance (magnitude of a deficiency). The terms of infrastructure
and supply may be treated with caution, as they may easily trigger some confusion (since, for example,
15% of an infrastructure deficiency may cause a proportional deficit in supply), but the main role of the
pertinent factor is to picture the infrastructure status that correlates to the drought hazard estimation.
For the index application, the six components portrayed in Figure 3 were classified into the following
vulnerability categories according to their performance on a 0 to 3 scale presented in Table 2. The cen-
tral premise for such a scaling was the attempt to quantify the various components in a simple and
Fig. 3. The relation among SDVI components and drought aspects (Karavitis et al., 2011a;2013;DMCSEE, 2012).
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–11971182
practical manner based on the pertinent literature and in an effort to express supply and demand deficits,
economic impacts evaluation and infrastructure appraisals during drought incidents (DMCSEE, 2012).
The SPI classification in relation to vulnerability levels was more straightforward, since it is a standar-
dized index and may analogically relate to pertinent vulnerability levels. The final vulnerability value
per area is calculated by the average scaled value of the components as presented in Equation (2)
(Karavitis et al., 2011a,2013;DMCSEE, 2012):
Equation (2) was developed following Equation (1). The hazard magnitude/identification is expressed
by the combination of SPI, of supply failure, of demand deficits and of infrastructure deficiencies, while
the impacts magnitude/assessment is expressed by their monetary assessment. Equation (2) implies that
all the components are equally weighted in an effort to avoid showing bias towards one of them. This
has been also decided due to the fact that equal weighting is usually applied to a variety of indices
despite the danger of over- or under-promoting some of the parameters (Organisation for Economic
Co-operation and Development (OECD), 2008). However, in a potential expansion of the overall
effort, numerical or statistical analyses (principal component, correlation, regression or other relevant
processes) may reduce the number of the required components of the index, estimate corresponding
weighted coefficients and at the same time they may present a future avenue of research to be explored.
The SDVI results are then classified into six vulnerability categories (Table 3) for the vulnerability
status per area to be determined. The scale development has followed other similar vulnerability indi-
cators classification schemes in parallel with an effort to avoid many divisions (Kaly et al., 2004;
Skondras et al., 2011). Drought severity has been also classified in a similar manner depicting five
levels in a scheme developed by the National Drought Mitigation Center (2013). It also has to be
noted that by applying the initial full classification scale (0 to 3) instead of developing one correspond-
ing to the produced results, the absolute vulnerability of an area may be measured and/or estimated
instead of the relative one. An additional advantage of this scalar visualization may come from the
inclusion of the SPI, which is a normalized index.
Table 2. SDVI components vulnerability scale.
Level SPI Supply Demand Impact Infrastructure
0Wet 1,50 0 No Deficits 0 No Deficits 0 None 0 Complete
Vulnerable 1 Quite
0 to 1,49 1 15% Deficits 1 15% Deficits 1 15% Losses 1 15%
0to1,49 2 16–50%
3 Dry 1,50 3 .50% Serious
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–1197 1183
3.3. Application process
The following steps have been pursued for the index application:
1. The SPI 6 and 12 have been calculated country-wise. For that estimation, precipitation data from 46
stations were collected in collaboration with the National Meteorological Service of Greece (HNMS),
the Ministry of Public Works (MPW) and the Public Power Corporation (PPC, S.A.), covering different
time periods from 1947 to 2009 (Figure 4). All the precipitation data were converted to monthly values.
All the chosen precipitation stations exhibit good data quality, according to the main criterion for such a
selection, namely the existence of minimal data gaps in the time series. The criterion also that the SPI
values should be estimated from a time period of at least 30 years was fulfilled, since all the stations
used provided such data time series (McKee et al., 1993). No attempt to fill in any existing data gaps
was made, since as stated above the gaps were minimal and it was considered that raw data may be
more appropriate to represent natural drought conditions (extreme minimum values) rather than enforcing
‘corrective’homogeneity (Karavitis et al., 2011b). The monthly precipitation data were used as input for
the SPI calculation tool (DMCSEE Project, 2009). The tool also has a built in capability to treat the data
gaps in the precipitation time series and not to use them in the final computation. In the current effort, the
SPIs for January and August for 1990, 2007 (drought years) and 2009 (normal year) were selected to be
presented and compared. The geo-statistical method of kriging was chosen for the spatial distribution and
intensity of the drought according to the SPI values, since precipitation is a natural parameter and chan-
ging the point original values may be acceptable (Karavitis et al., 2011b,2012a,b). The kriging method
(ordinary kriging) and the models to be followed (hole effect, exponential and spherical) were examined
and selected according to pertinent statistical parameters. The calculated parameters were the root mean
square error and the average standard error, whose values should be as low as possible in order to accept
Table 3. SDVI scaled values.
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–11971184
the corresponding surface. From the assessed statistical parameters the surfaces that visualized more
appropriately the SPI values were mostly those created by the hole effect model (Karavitis et al.,
2012a,b). Thus, the SPI values were spatially visualized using ordinary kriging (hole effect model) in
an ArcGIS 10 environment and are presented for SPI 6 and SPI 12 in Figures 5–7. Additionally, it is
pointed out that the SDVI may still be estimated based on SPI values, even if such values are indirectly
extrapolated using the kriging process for any specific points or areas, where precipitation data (for the
direct SPI calculation) are not available, as long as data on the remaining indicators are present.
2. An additional 28 extra locations (apart from the 46 station locations used) were also selected to serve pri-
marily as sign posts and are presented in Figure 4. Fifteen of such locations are high mountain peaks
(higher than 2,000 m a.s.l.), and the surrounding mostly barren areas, where the final SDVI estimate
Fig. 4. Stations and sign posts used (mountains and selected areas).
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–1197 1185
has axiomatically appointed a zero value since no significant economic or social aspects could be mea-
surably affected by drought. The remaining 13 locations are key areas of pivotal importance, where
crucial economic and social activities are present. In such areas, the above-mentioned extrapolated SPI
estimates on step 1 were used for the SDVI calculation. It is believed that these premises may lead towards
a more representative and suitable ‘calibration’of the SDVI estimation, since the initial runs of the pro-
cedure without the forced values in the selected locations have produced some results deviating from the
real conditions. This fact was particularly evident in the outcomes visualization, where the algorithm used
had assigned vulnerability values in areas of no actual vulnerability to drought (e.g. mountain peaks) and
viceversa. However, in regions where such knowledge is not available, the assigned values without the
sign posts may suffice, since they may represent reasonable enough approximations.
3. Impacts present nascent difficulties that need to be taken into account independently of geography, cli-
mate and political boundaries (DMCSEE, 2012;Grigg, 2014). The fragmentation of mostly anecdotal
reports does not lend itself to classify the drought impacts in economic, social and environmental cat-
egories. Instead, most reports are about agricultural impacts, and information about the other categories
is dispersed (Grigg, 2014). Data on water demand, water supply, pertinent water infrastructure and
drought impacts have been gathered for 59 of the 74 locations (not including the 15 mountain
peaks). More specifically, data time series covering different time periods from 1982 to 2009 on
supply network losses per water district, water availability and average water demand/consumption
per capita, and supply and demand deficits have been collected from the Water Resources Management
Fig. 5. SPI 6 and 12 for January and August 1990.
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–11971186
Plans of the River Basins in Greece (Special Secretariat for Water (SSW), 2013). These studies were
produced using MIKE SHE for the hydrological conditions and MIKE HYDRO BASIN for the man-
agement options. These Decision Support Systems are products of the Danish Hydrologic Institute
(DHI). Infrastructure information was based on the difference between the designed and the actual
capacity of the country’s reservoirs (dams) as well as on the reported operational conditions of the
water supply infrastructure at any given year including the drought ones (Ministry of Infrastructure,
Transport and Networks (MITN), 2013). The data reflected various time periods from 1964 to 2012.
Impact data have been also acquired from mass media archives, from reduction percentages of the agri-
cultural production for the drought years and from archive information on various drought impacts and
aspects of the corresponding local and national authorities and agencies, all dating from various time
intervals between 1950 and 2012 (Karavitis, 1999b;DMCSEE, 2012;Hellenic Statistical Authority
(HSA), 2013). Table 4 presents a sample of mass media drought data for Greece in 2007 and
Table 5 illustrates part of the applied drought responses assessment based on Figure 2 and Table 2.
All such data were used to produce the described scaled values according to Table 3.
4. The SDVI value per selected area and month has been calculated according to Equation (3). Then,
the produced values were classified into the vulnerability classes demarcated in Table 3. Finally, the
SDVI has been visualized using the Inverse Distance Weighting (IDW) in Geographical Information
System (Figure 8). The outcomes for both the index performance and drought vulnerability in Greece
are examined and analyzed in the following section. The IDW was chosen instead of kriging since
Fig. 6. SPI 6 and 12 for January and August 2007.
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–1197 1187
Fig. 7. SPI 6 and 12 for January and August 2009.
Table 4. Indicative selected drought chronology and data archives in Greece for 2007.
Archive Type: Mass
Media Date Drought Aspects Report
Country wide www.in.gr 13/3/2007 Measures against drought, forest fires and blackouts announced
by the government
18/3/2007 Drought hits Cyclades islands –Thessaly
Chios Aletheia Newspaper 12/4/2007 Subsidies announced for Drought in Chios Island
Chios Aletheia Newspaper 24/4/2007 Drought and the planned model of development for the county
Ikaria www.nikaria.gr 14/5/2007 Drought in Ikaria Island
Cyclades www.kykladesnews.gr 25/5/2007 Actions against the drought in the Cyclades: Intensified
groundwater drilling announced on all the islands
Thessaly Ethnos Newspaper 17/7/2007 Thessaly in the brink of civil war for water due to Drought
23/7/2007 Drought ‘burns’the plain of Thessaly
1/8/2007 Immediate measures are required against Drought. Cyclades
declare emergency conditions
Cyclades Kathemerine 1/8/2007 Drought intensifies in Cyclades
Country wide Eleutherotypia
9/8/2007 Measures are required for Drought. Water supplies
approaching limits in the whole country
Samos www.samos.gr 29/8/2007 The ministry announced measures for Drought
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–11971188
the method keeps intact its original values in the initial points and interpolates only among them for
the spatial representation of SDVI.
4. Results and discussion
According to the described procedure, the SPI 6 and SPI 12 maps for January and August of 1990,
2007 and 2009 were produced using precipitation data from 46 stations. The developed maps are visu-
alized in Figures 5–7.
Table 5. Indicative selected drought responses assessment in Greece for 2007.
Drought Responses Policy Actions
Supply Enhancement Demand Reduction
Reservoirs, dams, etc. Irrigation stops in
Crisis management approach
Improvement of the existing
conservation, groundwater use and
emergency water hauling by ships
Announcement of a drought master
plan formulation to be published in
2008. Announcement of
desalination plants construction in
most of the Cyclades Islands. Water
campaign on water
Existing dams do not suffice,
announcement of new dams’
Fig. 8. The SDVI maps for January and August 1990.
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–1197 1189
In the interpolation surface of SPI 6 in August 1990 (Figure 5) the Southern Aegean Islands, Central
Macedonia and Thrace are exhibiting drought conditions. Indicatively, in Thera Island station (South
Aegean) the rainfall was 16.4 mm, whereas the annual mean (1982–2006) was 325.6 mm therefore
having a 95% decrease. For January 2007 (Figure 6), it may be derived that western and particularly
southern Greece suffered the most from the drought conditions. Indicatively, the Cyclades Islands in
the southern Aegean are shown to have severely suffered as recorded. In Rhodes station the rainfall
was 398.2 mm, whereas the annual mean (1955–2009) was 675 mm therefore having a 41% decrease.
In August 2007 (Figure 6), the drought phenomenon had been dissipated. Droughts were observed only
in the central and eastern areas of the country. In Tauropos station precipitation was 811 mm and the
annual mean (1963–2008) was 1,247.8 mm reflecting a 35% decrease. In January of 2009 (Figure 7),
mild droughts were observed in Thrace as also recorded in Alexandroupolis station with a rainfall of
332.6 mm, whereas the annual mean (1947–2009) was 537.8 mm reflecting a 38% decrease. Mildly
wet conditions were experienced in the whole country during August of the same year. Overall, in
Greece, a temporal hysteresis was usually observed regarding water resources availability. Thus, the
social, economic and environmental impacts of limited precipitation incidents during the winter
period (represented also in the January maps) would appear significantly later, compounding the
summer season of increased demand. Such an issue should be taken into consideration, particularly
when referring to vulnerability estimation. Thus, it is believed that the 13 extra crucial areas selected
are also serving such a rationale, towards a more representative SDVI estimation.
Continuing, the SDVI values were calculated as stated according to the described procedure, and the
SDVI maps are produced and portrayed in Figures 8–10. All in all, the SPI 6 and SPI 12 reach their
highest values in 1990, and then they gradually decrease towards 2009. The lowest values are observed
during August 2009, signifying that the precipitation patterns were not greatly altered from their average
state. Overall the SPI representation seems to have fulfilled its purpose, namely to adequately portray the
natural climatic conditions regarding precipitation on a spatial and temporal scale.
Fig. 9. The SDVI maps for January and August 2007.
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–11971190
The remaining indicators (except those for Infrastructure) reached their highest values in January
1990 and August of 1990, 2007 and 2009. This may be attributed to the high water demand during
the summer seasons, when the country’s socio-economic state tends to suffer from the lack of available
water. During the winter seasons the drought impacts are usually less pronounced.
Regarding the estimation of the indicator for infrastructure, a significant change from 1990 to 2007
has been observed. From 1990 onwards, several new developments in water infrastructure took place,
particularly new dams and water systems networks. From 2007 to 2009, almost no change has been
recorded. Nevertheless, the average water infrastructure conditions in Greece were still lagging due to
lack of comprehensive planning, to operation and maintenance deficiencies and to insufficient develop-
mental efforts towards reaching their potential capacity (Barraque et al., 2008).
In commenting on the produced results, Figure 5 portrays a severe drought. Such a fact is connected to
‘High Vulnerability’for January and particularly August 1990, due to not only limited precipitation in this
month, but also to its combination with significant impacts. Furthermore, for January 2007 and 2009, the
country’s condition exhibited ‘Low Vulnerability’due to mainly low inflicted impacts despite the fact
that SPI values were signifying a severe enough drought. However, high vulnerability spots were starting
to appear and they should trigger a drought alert. August 2007 and 2009 presented ‘Medium Vulnerability’
reflecting the recorded limited precipitation during the previous winter months propagating as summer water
deficits while the August precipitation was also below even its usual low values. Thus high water demand
and decreasing water supply are signifying the portrayed drought vulnerability in the respective maps.
All in all, it seems that SDVI may offer a step towards making the interconnection between precipi-
tation deficits and demand deficits that usually demarcate the drought conditions and lead to drought
vulnerability. In this context, the index seems to adequately present an approximation towards linking
drought impacts to drought characteristics on a temporal and spatial scale. The index showed potential in
portraying various vulnerability states and followed satisfactorily the vulnerability fluctuations in Greece
in relation to recorded drought hazard dimensions and impacts. The current economic crisis that affects
Greece can also play a crucial role in future drought mitigation effort by affecting, through lack of
Fig. 10. The SDVI maps for January and August 2009.
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–1197 1191
funding, the country’s ability to absorb the drought impacts and improve the water infrastructure level.
Such conditions should be taken in to account when future drought vulnerability is to be examined.
The common thread in any discussion of sustainable water development and integrated water resources man-
agement emphasizes how new strategies are needed because water resources problems and their impacts are
becoming more and more multifaceted and large-scale. It may be said that the traditional spatial and environ-
mental envelope has collapsed and water development project peripheries –and consequences –may be much
more dispersed. Thus, it is essential to bring forward approaches that require drastic drought management
responses which in turn need as precise as possible estimates of drought magnitude, areal extent and duration.
Such estimates also entail improvement of drought monitoring, impacts assessment and information by
expanding the factual basis of reliable and timely data, drought-related decision support systems and indices.
Therefore, this work concentrated on providing a drought vulnerability index as complete and comprehen-
sive as possible under the current state of affairs. To achieve this goal, the droughts in Greece were examined
and evaluated. This framework presented the unique opportunity to study and evaluate drought and drought
vulnerability under stressed physical, structural and socio-economic environments. Compounding this is
also the context of understanding the implications of global change, the forces of interdependences, and
the complexity of interrelated physical and social systems. Thus, during recent decades, the concept of
drought vulnerability emerged. Such a concept is composed of the elements of risk and impacts and therefore
an index is needed in order to describe, and if possible provide further insight on, drought magnitude and
severity. The last brings forward an item repeated throughout all recent literature; that is, the great difficulty
in measuring through quantitative and qualitative indicators a water system’s drought resilience, levels of
significance, critical thresholds and comparability of impacts to responses over time. In the current approach
and in an effort to fill this gap, an SPI-based Drought Vulnerability Index was presented and applied on a
country scale. By the index application, Greece may be classified as a country vulnerable to drought not
because of a random lack of adequate water resources, but due to the combination of natural spatial and tem-
poral precipitation distribution with the water infrastructure deficiencies and its state of development.
The SDVI presented may be considered as a first step for the emergence of an integrated drought vul-
nerability index with multi-scalar applications in environmental research and decision-making. The SDVI
aims to describe the vulnerability to the various definitions/types of droughts (meteorological, hydrologi-
cal, agricultural and social), while incorporating the elements of drought impacts and the state of the
pertinent infrastructure. The index includes SPI, a powerful and well-established tool that may describe
the drought patterns and severity. The remaining indicators are used to provide necessary complementary
information through picturing the conditions accompanying a drought event on an area. However, the
embodied indicators still remain within a qualitative domain that may increase the inherent uncertainty.
Future efforts may be required for the transformation of such indicators into more quantitative ones.
Additionally, the equal weighting and linear aggregation approach that was selected needs to be tested
in comparison with other approaches so as to produce a statistically and conceptually more sound tool.
Finally, the various index components may be further transformed into sub-indices containing much
more information compared to the current structure of the index. There are arising agreements as to
such specific indicators, but they tend to be more evasive and difficult to pin down in socio-political
and institutional dimensions. Even more, political will and commitment are important preconditions for
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–11971192
successful cooperation in all aspects of water management, and particularly in applying a drought contin-
gency plan incorporating a vulnerability index. All in all, the end result of such postures and desired
accommodations would be the contingency preparedness for continuous changes, the ability to cope rea-
listically with the challenges of natural hazards and anthropogenic interdependencies, and the appreciation
of flexibility in drought management policy options and implementable practices.
Adger, W. N. (2000). Social and ecological resilience: are they related? Progress in Human Geography 24, 347–364.
Adger, W. N. (2006). Vulnerability.Global Environmental Change 16(2006), 268–281.
Adger, W. N. & Kelly, P. M. (1999). Social vulnerability to climate change and the architecture of entitlements.Mitigation and
Adaptation Strategies for Global Change 4, 253–266.
Andreu, J., Rossi, G., Vagliasindi, F. & Vela, A. (eds) (2006). Drought Management and Planning for Water Resources. Taylor
& Francis Group, New York, 252 pp.
Barraque, B., Karavitis, C. & Katsiardi, P. (2008). The range of existing circumstances in the Water Strategy Management
(WSM) case studies. In: Koundouri, P. (ed.) Coping with Water Deficiency: From Research to Policymaking. Environment
and Policy 48, Springer, Heidelberg, pp. 45–112.
Berkes, F. & Folke, C. (eds) (1998). Linking Social and Ecological Systems: Management Practices and Social Mechanisms
for Building Resilience. Cambridge University Press, Cambridge, UK.
Bohle, H.-G. (2001). Vulnerability and Criticality: Perspectives from Social Geography. International Human Dimensions Pro-
gramme on Global Environmental Change (IHDP) Newsletter Update, 2/2001, 1–7. http://ipcc-wg2.gov/SREX/report/njlite?
Bordi, I., Fraedrich, K., Petitta, M. & Sutera, A. (2006). Large scale assessment of drought variability based on NCEP/NCAR
and ERA-40 re-analyses.Water Resources Management 20, 889–915.
Briguglio, L. & Galea, W. (2003). Updating the Economic Vulnerability Index.Occasional Chapters on Islands and Small
States, 2003–04. Islands and Small States Institute, University of Malta, Malta.
Bruce, J. P. (1994). A perspective on reducing losses from natural hazards.Bulletin of the American Meteorological Society 75,
Cancelliere, A., di Mauro, G., Bonaccorso, B. & Rossi, G. (2005). Stochastic forecasting of Standardized Precipitation Index.
11–16 September 2005, Seoul, Korea.
Census (2011). Press Release: Notes on Demographic and Social Characteristics of the Resident Population of the Country
According to Census 2011. Available online in Greek: http://www.statistics.gr/portal/page/portal/ESYE/BUCKET/General/
Changnon, S. A. & Easterling, W. E. (1989). Measuring drought impacts: the illinois case.Water Resources Bulletin 25(1),
Chapin, F. S., Carpenter, S. R., Kofinas, G. P., Folke, C., Abel, N., Clark, W. C., Olsson, P., Stafford Smith, D. M., Walker, B.
H., Young, O. R., Berkes, F., Biggs, R., Grove, J. M., Naylor, R. L., Pinkerton, E., Steffen, W. & Swanson, F. I. (2009).
Ecosystem stewardship: sustainability strategies for a rapidly changing planet.Trends in Ecology and Evolution 25, 241–249.
Dalziell, E. P. & McManus, S. T. (2004). Resilience, Vulnerability and Adaptive Capacity: Implications for Systems Perform-
ance. International Forum for Engineering Decision Making (IFED), Switzerland, 6–8 December 2004. http://ir.canterbury.
Ding, Y., Hayes, M. & Widhalm, M. (2010). Measuring economic impacts of drought: a review and discussion. Papers in
Natural Resources. Paper 196. http://digitalcommons.unl.edu/natrespapers/196.
DMCSEE Project (2009). Drought Management Centre for South Eastern Europe. European Commission Funded project, EU.
Available at: http://www.dmcsee.eu/.
DMCSEE Project (2012). Report on Drought Vulnerability Assessment. Drought Management Centre for South Eastern
Europe, European Commission Funded project, EU. Available at: http://www.dmcsee.eu/.
Drought Management (1986). Drought Management and its Impacts on Public Water Systems. Report on a Colloquium Spon-
sored by the Water Science and Technology Board, September 1985, National Academies Press, Washington, DC.
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–1197 1193
Easterling, D. R., Meehl, G. A., Parmesan, C., Changnon, S. A., Karl, T. R. & Mearns, L. O. (2000). Climate extremes: obser-
vations, modeling, and impacts.Science 289, 2068–2074.
Eriyagama, N., Smakhtin, V. & Gamage, N. (2009). Mapping Drought Patterns and Impacts: a Global Perspective.
IWMI Research Report 133, International Water Management Institute, Colombo, Sri Lanka, 31 pp.
Folke, C., Carpenter, C. R., Walker, B., Scheffer, M., Chapin, T. & Rockström, J. (2010). Resilience thinking: integrating resi-
lience, adaptability and transformability. Ecology and Society 15(4), 20. Available at: http://www.ecologyandsociety.org/
Füssel, H.-M. (2007). Vulnerability: a generally applicable conceptual framework for climate change research.Global Environ-
mental Change 17, 155–167.
Fussel, H.-M. (2010). How inequitable is the global distribution of responsibility, capability, and vulnerability to climate
change: a comprehensive indicator-based assessment.Global Environmental Change 20, 597–611.
Gallopin, G. C. (2003). Box 1. A systemic synthesis of the relations between vulnerability, hazard, exposure and impact, aimed
at policy identification. In: Economic Commission for Latin American and the Caribbean (ECLAC). Handbook for Estimat-
ing the Socio-Economic and Environmental Effects of Disasters. ECLAC, LC/MEX/G.S., Mexico, D.F., pp. 2–5.
Gallopin, G. C. (2006). Linkages between vulnerability, resilience, and adaptive capacity.Global Environmental Change 16, 293–303.
Ganase, S. A. & Teelucksingh, S. S. (2011). Linking vulnerability, adaptation, and mitigation in small island developing states:
climate change and the community of Grande Riviere, Trinidad. In: Paper presented at XLII (43rd) Annual Conference of
Monetary Studies: ‘Financial Architecture and Economic Prospects Beyond the Crisis in the Caribbean’,15–18 November
2011, Central Bank of Barbados.
Gaume, E., Bain, V., Bernardara, P., Newinger, O., Barbuc, M., Bateman, A., Blaškovicová, L., Blöschl, G., Borga, M., Dumi-
trescu, A., Daliakopoulos, I., Garcia, J., Irimescu, A., Kohnova, S., Koutroulis, A., Marchi, L., Matreata, S., Medina, V.,
Preciso, E., Sempere-Torres, D., Stancalie, G., Szolgay, J., Tsanis, I. & Velascom, A. (2009). A compilation of data on
European flash floods.Journal of Hydrology 367,70–78.
Grigg, N. S. (1988). Planning for Security of Local Raw Water Supplies. Department of Civil Engineering, Colorado State
University, Fort Collins, Colorado.
Grigg, N. S. (1996). Water Resources Management: Principles, Regulations, and Cases. McGraw-Hill, New York.
Grigg, N. S. (2008). Integrated water resources management: balancing views and improving practice.Water International
Grigg, N. S. (2014). United States drought 2012: new experiences and lessons. International Journal of Water Resources
Development 30(2), 183–199.
Grigg, N. S. & Vlachos, E. C. (eds) (1990). Drought Water Management. International School for Water Resources, Depart-
ment of Civil Engineering, Colorado State University, Fort Collins, Colorado, 48 pp.
Grigg, N. S. & Vlachos, E. C. (1993). Drought and water-supply management: roles and responsibilities.Water Resources
Planning and Management ASCE 119(5), 531–541.
Gunderson, L. H. & Holling, C. S. (eds) (2002). Panarchy: Understanding Transformations in Human and Natural Systems.
Island Press, Washington, DC.
Hagman, G. (1984). Prevention Better Than Cure. Report on Human and Environmental Disasters in the Third World. Swedish
Red Cross, Stockholm. Available at: http://soils.usda.gov.
Hellenic Statistical Authority (HSA) (2013). Special Publications, Athens, Greece. Available at: http://dlib.statistics.gr/portal/
page/portal/ESYE/categoryyears?p_cat=10007963&p_topic=10007963 (accessed 28 November 2013).
Holling, C. S. (2001). Understanding the complexity of economic, ecological, and social systems. Mini reviews.Ecosystems 4(5),
Intergovernmental Panel on Climate Change (IPCC) (2001). Climate Change 2001: Impacts, Adaptation, and Vulnerability.
Contribution of Working Group II to the IPCC Third Assessment Report. Cambridge University Press, New York.
Intergovernmental Panel on Climate Change (IPCC) (2007). Working Group II Contribution to the Intergovernmental Panel on
Climate Change Fourth Assessment Report Climate Change 2007: Climate Change Impacts, Adaptation and Vulnerability
Summary for Policymakers. 6 April, 2007.
Intergovernmental Panel on Climate Change (IPCC) (2013). Final Draft Report. Working Group I contribution to the IPCC 5th
Assessment Report ‘Climate Change 2013: The Physical Science Basis’. 7 June, 2013.
International Strategy for Disaster Reduction (ISDR) (2004). Living With Risk: A Global Review of Disaster Reduction
Initiatives. 2nd edn, UN-ISDR, Geneva.
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–11971194
Janssen, M. A. (2006). Historical institutional analysis of social-ecological systems.Journal of Institutional Economics 2(2),
Janssen, M. A. & Ostrom, E. (2006). Resilience, vulnerability, and adaptation: a cross-cutting theme of the international human
dimensions programme on global environmental change.Global Environmental Change 16(3), 237–239.
Kaly, U., Pratt, C. & Mitchell, J. (2004). The Environmental Vulnerability Index 2004. SOPAC Technical Report 384.
Available at: http://islands.unep.ch/EVI%202004%20Technical%20Report.pdf.
Karavitis, C. A. (1992). Drought management strategies for urban water supplies: the case of metropolitan Athens. PhD thesis,
Colorado State University, Fort Collins, Colorado.
Karavitis, C. A. (1999a). Decision support systems for drought management strategies in metropolitan Athens.Water
International 24(1), 10–21.
Karavitis, C. A. (1999b). Drought and urban water supplies: the case of metropolitan Athens.Water Policy 1(5), 505–524.
Karavitis, C. A. (coordinator) (2008). Technical Report on Contract No. 10889/11/07 /2007 with the Water Resources Man-
agement Sector, Agricultural University of Athens (AUA),Technical Support to the Central Water Agency of Greece for the
Development of a Drought Master Plan for Greece and an Immediate Drought Mitigation Plan. Ministry of Planning, Public
Works and the Environment, Athens, Greece (in Greek).
Karavitis, C. A. (2012). Drought vulnerability assessment–introduction and theoretical background. In: Drought Management Centre
for South-East Europe –DMCSEE. Summary of the Result of the Project,Co-Financed by the South East Europe Transnational
Cooperation Programme (Contract No. SEE /A/091/2.2/X). Gregorič, G. (ed.). Slovenian Environmental Agency, Ljubljana, Slo-
venia. Available at: http://www.met.hu/doc/DMCSEE/DMCSEE_final_publication.pdf (accessed 28 October 2013).
Karavitis, C. A. & Kerkides, P. (2002). Estimation of the water resources potential in the island system of the Aegean
Archipelago, Greece.Water International 27(21), 243–254.
Karavitis, C. A., Alexandris, S. G., Fassouli, V. P., Stamatakos, C. G., Tsesmelis, D. E. & Skondras, N. A. (2011a). Vulner-
ability assessment, Task 4.2.5, DMCSEE project. In: 5th DMCSEE Consortium Meeting and Training, 28 June–1 July 2011,
Karavitis, C. A., Alexandris, S., Tsesmelis, D. E. & Athanasopoulos, G. (2011b). Application of the Standardized Precipitation
Index (SPI) in Greece.Water 3(3), 787–805.
Karavitis, C. A., Chortaria, C., Alexandris, S., Vasilakou, C. G. & Tsesmelis, D. E. (2012a). Development of the standardised
precipitation index for Greece.Urban Water Journal 9(6), 401–417.
Karavitis, C. A., Skondras, N. A., Tsesmelis, D. E., Stamatakos, C. G., Alexandris, S. G. & Fassouli, V. P. (2012b). Drought
impacts archive and drought vulnerability index. In: Drought Management Centre for South-East Europe –DMCSEE. Sum-
mary of the result of the project, co-financed by the South East Europe Transnational Cooperation Programme (contract no.
SEE /A/091/2.2/X). Gregorič, G. (ed.). Slovenian Environmental Agency, Ljubljana, Slovenia. Available at: http://www.met.
hu/doc/DMCSEE/DMCSEE_final_publication.pdf (accessed 28 October 2013).
Karavitis, C. A., Alexandris, S. G., Fassouli, V. P., Stamatakos, D. V., Vasilakou, C. G., Tsesmelis, D. E., Skondras, N. A. &
Gregoric, G. (2013). Assessing drought vulnerability under alternative water demand deficit scenarios in South-Eastern
Europe. In Eighth International Conference of EWRA: ‘Water Resources Management in an Interdisciplinary and Changing
Context’.26–29 June 2013, Porto, Portugal.
Langeweg, F. & Gutierrez-Espeleta, E. E. (2001). Human security and vulnerability in a scenario context: challenges for
UNEP’s global environmental outlook. IHDP Update 2,17–19.
Leichenko, R. M. & O’Brien, K. L. (2002). The dynamics of rural vulnerability to global change: the case of Southern Africa.
Mitigation and Adaptation Strategies for Global Change 7,1–18.
Livada, I. & Assimakopoulos, V. D. (2007). Spatial and temporal analysis of drought in Greece using the standardized precipi-
tation index (SPI).Theoretical and Applied Climatology 89, 143–153.
Llasat-Botija, M., Llasat, M. C. & Lopez, L. (2007). Natural hazards and the press in the western Mediterranean region.
Advances in Geosciences 12,81–85.
Loukas, A., Vasiliades, L. & Tzabiras, J. (2007). Evaluation of climate change on drought impulses in Thessaly, Greece.
European Water 17/18,17–28.
Luers, A. L. (2005). The surface of vulnerability: an analytical framework for examining environmental change.Global
Environmental Change 15, 214–223.
McKee, T. B., Doesken, N. J. & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. In:
Preprints, 8th Conference on Applied Climatology, 17–22 January, Anaheim, California, pp. 179–184.
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–1197 1195
Miller, F., Osbahr, H., Boyd, E., Thomalla, F., Bharwani, S., Ziervogel, G., Walker, B., Birkmann, J., van der Leeuw, S.,
Rockström, J., Hinkel, J., Downing, T., Folke, C & Nelson, D. (2010). Resilience and vulnerability: complementary or con-
flicting concepts? Ecology and Society,15(3), article 11. Available at: http://www.ecologyandsociety.org/vol15/iss3/art11/
(accessed 7 October 2011).
Ministry of Infrastructure, Transport and Networks (MITN) (2013). Records on Infrastructure. Athens, Greece (in Greek).
Mishra, A. K. & Desai, V. R. (2005). Drought forecasting using stochastic models.Stochastic Environmental Resources Risk
Assessment 19, 326–339. Springer-Verlag GmbH, Berlin. DOI: 10.1007/s00477-005-0238-4.
Nardo, M., Saisana, M., Saltelli, A., Tarantola, S., Hoffman, A. & Giovannini, E. (2005). Handbook on Constructing Compo-
site Indicators: Methodology and User Guide. OECD Statistics Working Paper STD/DOC 3. Paris. www.oecd.org/std/
National Drought Mitigation Center (2013). Drought Monitor: State-of-the-Art Blend of Science and Subjectivity.http://
droughtmonitor.unl.edu/classify.htm. 8 April 2013.
National Drought Policy Commission (NDPC) (2000). Preparing for Drought in the 21st Century. US Department of Agricul-
ture, Washington, DC.
National Research Council –NRC (2001). Under the Weather: Climate, Ecosystems, and Infectious Disease. National Acade-
mies Press, Washington, DC.
NationMaster.com (2008). Greece. Available at: http://www.nationmaster.com/country/gr-greece/agr-agriculture (accessed 17
Organisation for Economic Co-operation and Development (OECD) (2008). Handbook on Constructing Composite Indicators:
Methodology and User Guide. Available at: http://www.oecd.org/std/42495745.pdf (accessed 28 June 2011).
Palmer, W. C. (1965). Meteorological drought. Research Paper No. 45, US Department of Commerce Weather Bureau,
Palmer, W. C. (1968). Keeping track of crop moisture conditions, nationwide: the new crop moisture index.Weatherwise 21, 156–161.
Pratt, C., Kaly, U. & Mitchell, J. (2004). Manual: How to Use the Environmental Vulnerability Index. SOPAC Technical
Report 383. Available at: http://www.vulnerabilityindex.net/EVI_Library.htm.
Preston, B. L. & Stafford-Smith, M. (2009). Framing vulnerability and adaptive capacity assessment: discussion paper. CSIRO
Climate adaptation flagship working paper No. 2. Available at: http://www.csiro.au/org/ClimateAdaptationFlagship.html.
Priscoli, J. D. (2013). Keynote address: clothing the IWRM emperor by using collaborative modeling for decision support.
Journal of the American Water Resources Association (JAWRA) 49(3), 609–613.
Rogge, N. (2012). Undesirable specialization in the construction of composite policy indicators: the environmental performance
index.Ecological Indicators 23, 143–154.
Rossi, G., Benedini, M., Tsakiris, G. & Giakoumakis, S. (1992). On regional drought estimation and analysis.Water Resources
Management 6, 249–277.
Salas, J. D. (1986). State of the art of statistical techniques for describing drought characteristics, WARREDOC. International
Seminar on Drought Analysis, May, Perugia, Italy, 52 pp.
Shatanawi, K., Rahbeh, M. & Shatanawi, M. (2013). Characterizing, monitoring and forecasting of drought in Jordan River
basin.Journal of Water Resource and Protection 5(12), 1192–1202.
Sheffield, J., Wood, E. F. & Roderick, M. L. (2012). Little change in global drought over the past 60 years. Nature Inter-
national Weekly Journal of Science 491(7424), 435–438. http://www.nature.com/nature/journal/v491/n7424/full/
nature11575.html, 8 April 2013.
Singh, R. K., Murty, H. R., Gupta, S. K. & Dikshit, A. K. (2009). An overview of sustainability assessment methodologies.
Ecological Indicators 9, 189–212.
Skondras, N. A., Karavitis, C. A., Gkotsis, I. I., Scott, P. J. B., Kaly, U. L. & Alexandris, S. G. (2011). Application and assess-
ment of the environmental vulnerability index in Greece.Ecological Indicators 11, 1699–1706.
Special Secretariat for Water (SSW) (2013). Management Plans of the River Basins in Greece. Ministry of Environment,
Energy and Climate Change (MEECG), Athens, Greece (in Greek).
Sullivan, C. A. (2011). Quantifying water vulnerability: a multidimensional approach.Stochastic Environmental Research and
Risk Assessment 25, 627–640.
Sullivan, C. A. & Huntingford, C. (2009). Water resources, climate change and human vulnerability. In: Anderssen, R. S.,
Braddock, R. D. & Newham, L. T. H. (eds). Proceedings: 18th World IMACS Congress and MODSIM09. Modelling
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–11971196
and Simulation Society of Australia and New Zealand and International Association for Mathematics and Computers in
Simulation, 13–17 July 2009. Cairns, Australia, pp. 2377–2383. http://mssanz.org.au/modsim09.
Tsakiris, G. & Vangelis, H. (2004). Towards a drought watch system based onspatial SPI.Water Resources Management 18,1–12.
Turner, B. L., Kasperson, R. E., Matson, P. A., McCarthy, J. J., Corell, R. W., Christensen, L., Eckley, N., Kasperson, J. X.,
Luers, A., Martello, M. L., Polsky, C., Pulsipher, A. & Schiller, A. (2003). A framework for vulnerability analysis in sustain-
ability science.Proceedings of the National Academy of Sciences of the United States of America 100(14), 8074–8079.
United Nations Educational, Scientific and Cultural Organization (UNESCO) (2006). Water a Shared Responsibility. The
United Nations World Water Development Report 2, New York.
US Climate Change Science Program (USCCSP) (2009). Thresholds of Climate Change in Ecosystems. Final Report, Synthesis
and Assessment Product 4.2. Available at: http://www.sel.uaf.edu/manuscripts/bk18_Fagre-Thresholds-sap4-2-final-report-
all.pdf (accessed 22 September 2011).
Vairavamoorthy, K., Gorantiwar, D. S. & Pathirana, A. (2008). Managing urban water supplies in developing countries –cli-
mate change and water scarcity scenarios.Physics and Chemistry of the Earth 33, 330–339.
Vasiliades, L., Loukas, A. & Patsonas, G. (2009). Evaluation of a statistical downscaling procedure for the estimation of climate
change impacts on droughts.Natural Hazards and Earth System Sciences 9, 879–894.
Vicente-Serrano, S. M., González-Hidalgo, J. C., de Luis, M. & Raventós, J. (2004). Drought patterns in the Mediterranean
area: the Valencia region (Eastern Spain).Climate Research 26,5–15.
Vicente-Serrano, S. M., Begueria, S. & López-Moreno, J. I. (2010). A multiscalar drought index sensitive to global warming:
the standardized precipitation evapotranspiration index.Journal of Climate 23(7), 1696–1718.
Vlachos, E. (2004). Water conflict and cooperation the transition to a purposeful future. In: Speech at: ‘Water: A Catalyst for
Peace’Zaragoza Conference Interactive Role-play and Alternative Dispute Resolution (ADR) Techniques, 6–8 October
2004, Zaragoza, Spain.
Vlachos, E. C. (1982). Drought management interfaces. In: Annual ASCE Conference, Las Vegas, Nevada, 15 pp.
Vlachos, E. C. & Braga, B. (2001). The challenge of urban water management. In: Frontiers in Urban Water Management:
Deadlock or Hope. Makcimovic, C. & Tejada-Juibert, G. A. (eds). IWA Publishing, London.
Vogel, C. (1998). Vulnerability and global environmental change. LUCC Newsletter 3,15–19.
Walker, B. & Meyers, J. A. (2004). Thresholds in ecological and social-ecological systems: a developing database. Ecology and
Society 9(2), 3. Available at: http://www.ecologyandsociety.org/vol9/iss2/art3/ (accessed 20 July 2011).
WeAdapt Project Website: Available at: http://weadapt.org/knowledge-base/vulnerability/vulnerability-definitions (accessed
Wilhite, D. (1997). Improving Drought Management in the West: The Role of Mitigation and Preparedness. Report to the Wes-
tern Water Policy Review Advisory Commission. Denver, Colorado.
Wilhite, D. A., Diodato, D. M., Jacobs, K., Palmer, R., Raucher, B., Redmond, K., Sada, D., Smith, K.-H., Warwick, J. &
Wilhelmi, O. (2006). Managing drought: a roadmap for change in the United States. In: A Conference Report from Managing
Drought and Water Scarcity in Vulnerable Environments.18–20 September 2006.
Wilhite, D. A., Hayes, M. J. & Svoboda, M. D. (2000). Drought monitoring and assessment: status and trends in the United
States. In: Drought and Drought Mitigation in Europe. Vogt, J. V. & Somma, F. (eds). Kluwer Academic Publishers,
Springer, Netherlands, pp. 149–160.
Wilhite, W. A., Easterling, W. E. & Wood, D. A. (eds) (1987). Planning for Drought. Westview Press, London.
Woodhouse, C. A., Meko, D. M., MacDonald, G. M., Stahle, D. W. & Cook, E. R. (2010). A 1,200-year perspective of 21st
century drought in southwestern North America.PNAS 107(50), 21283–21288.
World Water Assessment Programme –WWAP (2009). The United Nations World Water Development Report 3: Water in a
Changing World. United Nations Educational, Scientific and Cultural Organization, Paris.
Wu, H., Svoboda, M. D., Hayes, M. J., Wilhite, D. A. & Wen, F. (2007). Appropriate application of the Standardized Precipi-
tation Index in arid locations and dry seasons.International Journal of Climatology 27,65–79.
Wu, J., He, B., Lu, A., Zhou, L., Liu, M. & Zhao, L. (2011). Quantitative assessment and spatial characteristics analysis of
agricultural drought vulnerability in China.Natural Hazards 56, 785–801.
Yevjevich, V., Da Cunha, L. & Vlachos, E. (1983). Coping with Droughts. Water Resources Publications, Littleton, Colorado.
Zou, X., Zhai, P. & Zhang, Q. (2005). Variations in droughts over China: 1951–2003.Geophysical Research Letters 32, L04707.
Received 10 December 2013; accepted in revised form 24 March 2014. Available online 12 May 2014
C. A. Karavitis et al. / Water Policy 16 (2014) 1172–1197 1197