Earth’s Future
Adaptation to flood risk: Results of international paired flood
event studies
Heidi Kreibich1 , Giuliano Di Baldassarre2 , Sergiy Vorogushyn1 , Jeroen C. J. H. Aerts3,
Heiko Apel1 , Giuseppe T. Aronica4 , Karsten Arnbjerg-Nielsen5 , Laurens M. Bouwer6,
Philip Bubeck7 , Tommaso Caloiero8 , Do T. Chinh1, Maria Cortès9, Animesh K. Gain1 ,
Vincenzo Giampá10, Christian Kuhlicke11 , ZbigniewW. Kundzewicz12, Maria Carmen Llasat9,
JohannaMård2 , Piotr Matczak13, Maurizio Mazzoleni14, Daniela Molinari15 ,
Nguyen V. Dung1, Olga Petrucci10 , Kai Schröter1, Kymo Slager6, Annegret H. Thieken7 ,
Philip J. Ward3 , and BrunoMerz1
1Section 5.4 Hydrology, GFZ German Research Centre for Geosciences, Potsdam, Germany, 2Department of Earth
Sciences, Centre of Natural hazards and Disaster Science (CNDS), Uppsala University, Uppsala, Sweden, 3Department of
Water and Climate Risk, Institute for Environmental Studies, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands,
4Department of Engineering, University of Messina, Messina, Italy, 5Urban Water Systems Section, Department of
Environmental Engineering, Bygningstorvet, Technical University of Denmark, Kgs. Lyngby, Denmark, 6Deltares, Delft,
The Netherlands, 7Institute of Earth and Environmental Science, University of Potsdam, Potsdam, Germany,
8CNR-ISAFOM National Research Council, Institute for Agricultural and Forest Systems in the Mediterranean, Rende,
Italy, 9GAMA, Department of Applied Physics, University of Barcelona, Barcelona, Spain, 10CNR-IRPI National Research
Council, Research Institute for Geo-Hydrological Protection, Rende, Italy, 11Department Urban & Environmental
Sociology, UFZ Helmholtz Centre for Environmental Research, Leipzig, Germany, 12Institute for Agricultural and Forest
Environment, Polish Academy of Sciences, Poznan´, Poland, 13Institute of Sociology, AdamMickiewicz University,
Poznan, Poland, 14Integrated Water Systems & Governance, IHE Delft Institute for Water Education, Delft, The
Netherlands, 15Department of Civil and Environmental Engineering, Politecnico di Milano, Milan, Italy
Abstract As flood impacts are increasing in large parts of the world, understanding the primary drivers
of changes in risk is essential for effective adaptation. To gain more knowledge on the basis of empirical
case studies, we analyze eight paired floods, that is, consecutive flood events that occurred in the same
region, with the second flood causing significantly lower damage. These success stories of risk reduction
were selected across different socioeconomic and hydro-climatic contexts. The potential of societies to
adapt is uncovered by describing triggered societal changes, as well as formal measures and sponta-
neous processes that reduced flood risk. This novel approach has the potential to build the basis for an
international data collection and analysis effort to better understand and attribute changes in risk due to
hydrological extremes in the framework of the IAHSs Panta Rhei initiative. Across all case studies, we find
that lower damage caused by the second event was mainly due to significant reductions in vulnerabil-
ity, for example, via raised risk awareness, preparedness, and improvements of organizational emergency
management. Thus, vulnerability reduction plays an essential role for successful adaptation. Our work
shows that there is a high potential to adapt, but there remains the challenge to stimulate measures that
reduce vulnerability and risk in periods in which extreme events do not occur.
1. Introduction
Damage due to floods is increasing in large parts of theworld [IPCC, 2012]. More knowledge about whether
flood risk increases over time in specific regions, and if so, why, is essential for policy response in terms of
flood risk management and adaptation strategies [Merz et al., 2010; Bouwer, 2011]. According to the IPCC
SREX concept, risk depends on hazard, exposure, and vulnerability [IPCC, 2012]: In this context, hazard is
defined as the potential occurrence of a natural or human-induced physical event that may cause adverse
effects to social elements. Exposure is defined as the presence of people, livelihoods, environmental ser-
vices and resources, infrastructure, or economic, social, or cultural assets in places that could be adversely
affected by physical events. Vulnerability is defined generically as the propensity or predisposition to be
adversely affected [IPCC, 2012]. Such predisposition constitutes an internal characteristic of the affected
element, and it includes the characteristics of a person or society and the situation that influences their
RESEARCH ARTICLE
10.1002/2017EF000606
Special Section:
Avoiding Disasters:
Strengthening Societal
Resilience to Natural Hazards
Key Points:
• Across different socio-economic and
hydro-climatic contexts there is high
potential to adapt to future flood risk
• Focusing events act as triggers for
raising risk awareness, preparedness
and improvements of emergency
management which reduce
vulnerability
• Vulnerability reduction is key for
successful adaptation but the
challenge remains to stimulate risk
reduction when no extreme events
occur
Supporting Information:
• Supporting Information S1
Corresponding author:
H. Kreibich,
heidi.kreibich@gfz-potsdam.de
Citation:
Kreibich, H. et al (2017), Adaptation to
flood risk: Results of international
paired flood event studies, Earth’s
Future, 5, 953–965,
doi:10.1002/2017EF000606.
Received 29 APR 2017
Accepted 24 JUL 2017
Accepted article online 26 JUL 2017
Published online 3 OCT 2017
© 2017 The Authors.
This is an open access article under
the terms of the Creative Commons
Attribution-NonCommercial-NoDerivs
License, which permits use and distri-
bution in any medium, provided the
original work is properly cited, the use
is non-commercial and no modifica-
tions or adaptations are made.
KREIBICH ET AL. ADAPTATION TO FLOOD RISK 953
Earth’s Future 10.1002/2017EF000606
capacity to anticipate, cope with, resist, and recover from the adverse effects of physical events [Wisner
et al., 2004].
The observed increase in flood damage in many regions of the world is dominated by exposure increase,
while an impact of changes in flood hazard due to anthropogenic climate change has hardly been observed
to date [Bouwer, 2011; Merz et al., 2012]. The climate signal might be masked by a counteracting decrease
in vulnerability, as suggested by studies at global [Jongman et al., 2015] and regional [Di Baldassarre et al.,
2015;Mechler and Bouwer, 2015] scales. However, knowledge is still scarce about the underlying processes
that drive changes in flood risk, particularly in respect to vulnerability [UNISDR, 2015].
The vulnerability of societies may be influenced by flood risk management, other formal measures like
land use planning, societal changes, as well as spontaneous processes that influence flood risk. “Focusing
events,” that is, events that provide a sudden, strong push for action, often trigger flood risk mitigation and
improvements of risk management [Kingdon, 1995; Kreibich et al., 2011]. For example, the 1953 North Sea
flood disaster lead to the Delta Works in The Netherlands [Van Koningsveld et al., 2008] and the construc-
tion of the Thames Barrier [McRobie et al., 2005] in the UK. Several studies are available on various aspects
of societal vulnerability [e.g., Tapsell et al., 2002; Brouwer et al., 2007; Kuhlicke et al., 2011] and learning [e.g.,
Birkland, 1998; Pahl-Wostl, 2009; Armitage et al., 2008]. However, we believe that our study provides empiri-
cal evidence adding essential information about how extreme flood events stimulate changes in flood risk
management and how these manifest during a subsequent flood in the same region.
The objective of our study is to gain knowledge on how flood events trigger adaptation to future flood risk.
We assess eight paired flood events, which are real-world examples for successful risk reduction. This allows
us to derive robust conclusions fromcommonalities anddifferences between the case studies, across awide
range of hydro-climatic and socioeconomic conditions.
2. Compilation of Paired Flood Event Studies
This study is based on a selection of success stories of risk reduction, that is, case studies, collected from
around the world where societies effectively implemented flood risk management or other measures and
societal changes, which significantly mitigated potential flood damage (Figure 1). Besides such success
stories there are, unfortunately, examples of developmentswhich lead to an increase of flood risk. Examples
concern higher exposure due to urbanization or asset value increase [e.g.,Domeneghetti et al., 2015; Faccini
et al., 2015; Ferguson and Ashley, 2017]; an increase in vulnerability due to a lack of maintenance of pro-
tection structures [e.g., Orlandini et al., 2015; IKSE, 2001]; or fading of preparedness of administration and
affected parties [e.g. Kreibich andMerz, 2007; Nkwunonwo et al., 2016]. However, such cases are not consid-
ered in this study, sincewe aim to show how successful flood riskmitigation can be achieved. The approach
is based on the analysis of paired flood events in different river basins across different socioeconomic and
hydro-climatic conditions. Paired flood events were defined as consecutive floods that occurred in the
same region. Such paired events are natural experiments where processes which change flood risk can
be analyzed. The approach is analogous to the concept of “paired catchment studies” in hydrology, which
is widely used to determine the magnitude of water yield changes resulting from changes in vegetation
[Brown et al., 2005].
To assess changes in flood risk and its drivers, detailed case study analyses were undertaken (see Support-
ing Information S1). On this basis, hazard, exposure, and vulnerability indicatorswere derived and evaluated
for each case study. Inherently, the characterization of risk and its components combines both quantitative
and qualitative aspects. For this study, hazard is described using the following indicators: the event pre-
conditions (e.g., antecedent catchment wetness, saturated or frozen soils, etc.), the frequency and intensity
of precipitation, the hydrological severity (e.g., return period of the flood discharge, affected length of the
river network, inundation extent, etc.) and the failure of protectionmeasures (like dikes, dams, etc.). To char-
acterize exposure, the following indicators are used: the number of people affected, the area affected (e.g.,
settlement area, agricultural land, assets affected, etc.) and the presence of exposure hotspots, which shall
indicate if there was particularly high exposure in the flooded area, for example, due to affected cities or
industrial areas. There are various concepts and definitions of “Vulnerability” [Thywissen, 2006], many of
which consider a quite broad context [e.g. Nakamura and Llasat, 2017; Brooks et al., 2005; Turner et al., 2003;
KREIBICH ET AL. ADAPTATION TO FLOOD RISK 954
Earth’s Future 10.1002/2017EF000606
Figure 1. Case studies across different socioeconomic (e.g., population density, gross domestic product per capita [World Bank, 2016]) and hydro-climatic (e.g., climate, flood type)
contexts (for detailed information on the individual case studies see Supporting Information S1 (texts S1–S8)). The distribution of global flood frequency in the period 1985–2003 is
shown using a blue scale. The flood frequency grid was classified into 10 classes of approximately equal number of grid cells. The darker blue the grid cell is, the higher the relative
frequency of flood occurrence [CHRR and CIESIN, 2005].
Kelly and Adger, 2000]. For our case study comparison, we narrow the few and focus on the following vul-
nerability indicators: lack of awareness (e.g., lack of flood experience, information campaigns, precautionary
measures), lack of preparedness (e.g., lack of early warning, lead times, risk communication during event,
private emergency measures) and insufficient organizational emergency management (e.g., performance
of the governmental crisis management, civil protection, emergency plans, evacuation, etc.). The negative
form (e.g., lack of ) is chosen to have a positive correlation with vulnerability and to be consistent with the
effects of the hazard and exposure indicators so that a reduction in an indicator leads to a reduction in
flood risk and as such reflects a positive development. For instance, a reduction of lack of awareness relates
to a reduction of vulnerability and as such to a reduction in flood risk. This is particularly important for our
compilation of all paired event studies in Figure 2.
Detailed analyses of the individual paired flood events are based on case study research, literature review,
and expert knowledge about the impacted regions. These detailed analyses are provided in Supporting
Information S1 (texts S1 to S8). Based on these results, the hazard, exposure and vulnerability indicators
were derived. When available, quantitative empirical evidence from case study research was used for a
quantification of indicators. Where no empirical evidence was available, a qualitative assessment based
on the literature review and expert knowledge was used. For each case study, we examine how these
indicators manifested during both floods and particularly how they changed from the first flood to the
second flood. Particularly important is how their changes influenced the difference in the resulting dam-
age, that is, number of fatalities and monetary damage. These results were abstracted and compiled in
Figure 2 to achieve a homogenous cross-case study comparison and as such more generic results than
KREIBICH ET AL. ADAPTATION TO FLOOD RISK 955
Earth’s Future 10.1002/2017EF000606
Figure 2. Analysis of the eight paired flood events (for more detailed information see Table 1 and Supporting Information S1, texts
S1–S8). The figure shows the difference of the primary drivers of flood risk change as well as of fatalities and economic damage between
the first flood event, used as baseline, and the second event. Drivers are expressed using hazard, exposure, and vulnerability indicators.
on the basis of individual case study analyses only. Changes of the hazard, exposure, and vulnerability
indicators as well as of the resulting damage (fatalities and monetary damage) from the first flood used
as baseline to the second flood are indicated by upward and downward arrows for increase and decrease,
respectively (or circles for no change). In case of quantitative comparisons (e.g., precipitation intensities,
monetary damage) a change of less than 50% is indicated by a small arrow, and larger changes by large
arrows. The diversity of amount and quality of available information about the change of the individual
indicators are indicated by hollow and filled arrows/circles for limited and robust evidence. This distinction
is based on expert judgment inspired by the IPCC concept of treatment of uncertainties [Mastrandrea et al.,
2010]. Generally, evidence is evaluated to be robust when there is one (or preferably more consistent)
good-quality measurement, analysis, or study available from a reputable source (e.g., scientific study or
governmental report) which indicate(s) the change of indicator.
Our approach of analyzing pairs of events as well as undertaking a comparative analysis of various
event pairs yields generic results. A problem of extreme event or catchment studies is that every event,
catchment, region, situation, etc. is unique and has its own characteristics and processes which make it
KREIBICH ET AL. ADAPTATION TO FLOOD RISK 956
Earth’s Future 10.1002/2017EF000606
challenging to draw general, transferable conclusions. Transferring the established approach of paired
catchment studies [Brown et al., 2005; Prosdocimi et al., 2015] to event comparisons and complementing it
with (semi-)qualitative data on exposure and vulnerability enable a comprehensive attribution of changes
in risk, as demonstrated for floods in this study and as suggested for droughts by Van Loon et al. [2016].
Another approach to reach universal results is comparative analysis, which aims to find general patterns by
analyzing a large set of case studies (e.g., catchments) from all over theworld [Duanet al., 2006; Blöschl et al.,
2013]. Combining these two approaches in collecting a large number of paired events seems a promising
way forward for attributing changes in risk of hydrological extremes. Thus, the eight paired event studies
compiled in this study may be the starting point for an international effort to collect and analyze paired
events, for example, in the framework of the IAHSs Panta Rhei initiative.
3. Flood Risk Change
The compilation of paired events shows that in all cases, reductions in flood damage between the first and
second flood occurred mainly along with large reductions of the three main elements of vulnerability, that
is, lack of risk awareness, lack of preparedness, and insufficient organizational emergency management.
In some cases additionally structural flood protection and reduction in exposure played a role (Figure 2).
Clearly, the different drivers of risk change (vulnerability, exposure and hazard) act simultaneously. In inte-
grated flood risk management, flood protection is complemented with nonstructural measures such as
land-use planning to reduce exposure, and improved private preparedness or organizational emergency
management to reduce vulnerability [Klijn et al., 2015]. The German Elbe, Danube 2002/2013 case is a good
exampleof the combinedeffects of structural andnonstructuralmeasures. Although thehydrological sever-
ity of the second event in 2013wasmuch larger (hydrological severity index: 75 in 2013, 35 in 2002 [Schröter
et al., 2015]), the monetary damage was reduced by about 50% and the fatalities by 33% due to improved
structural protection, as well as reduced vulnerability due to timely flood warning and better awareness
and preparedness of affected people and emergency managers [Thieken et al., 2016b].
3.1. Hazard Changes
Catchment preconditions and precipitation differ from event to event and cannot be influenced by flood
risk management. In all paired event cases, these factors are either insignificantly different between the
events or slightly lower for the second event with only a few exceptions (Figure 2). In the German Elbe,
Danube case, the hydrological severity in terms of themagnitude and spatial coverage of the second event
was higher and driven by strong catchment wetness [Schröter et al., 2015]. Still, a strong damage reduc-
tion for the second event was achieved, which underscores the decisive roles of reductions in vulnerability
and exposure. Largely lower precipitation is observed in the Italian case for the second event, which partly
explains reductions of damage along with the reduced vulnerability.
There is a general tendency to improve structural flood defenses and increase the protection level after
major flood events. For instance, in the German Elbe, Danube 2002/2013 case, massive investments in the
reinforcement of dikes after the 2002 flood were undertaken. The federal state of Saxony in Germany alone
allocated more than €800 million for structural flood defenses after the 2002 flood [Müller, 2010]. The rein-
forced protection infrastructure has led to reductions in protection failures: only 30 dike failures occurred
in 2013, compared to over 130 failures in 2002. Monetary damage was reduced by about 50% (Table 1).
Some reduction in damage as a result of reduced protection failures is also noted in the Bangladesh, Ital-
ian, and Spanish case studies. For these case studies, no evidence for massive investments into structural
flood protection is reported. It could be the case that fewer failures occurred during the later floods due
to smaller hydrological severity and lower hydrological load on flood protection structures. The causality is
different in the Vietnamese case: Many protection dikes, which are designed to protect farmland from flood
throughout the year, were built quickly on relatively weak soil foundations in the years following the 2000
flood. The dike system in 2011 led to confined stream flow, causing higher flow velocities and water levels
than might have been considered for dike construction and stability. This led to many dike failures during
the flood in 2011. However, sincemany dikes were newly built after the 2000 flood, the dike system (despite
the failures) still caused a reduction of affected agricultural area by 78% (Table 1). Given the hydrological
severity of the 2000 event, it has to be expected that many more dikes would have failed, if they were in
place. Construction of dikes is costly and time consuming; hence, if the time lag between two flood events
KREIBICH ET AL. ADAPTATION TO FLOOD RISK 957
Earth’s Future 10.1002/2017EF000606
is short, as was the case for Germany Rhine 1993/1995, it is unlikely that defenses are sufficiently repaired
or upgraded. However, where we have an indication of substantial investments into the flood protection
infrastructure (Elbe/Danube and Mekong basins), a strong evidence of risk reduction is present (Figure 2).
3.2. Exposure Changes
Across the eight case studies, the role of changes in exposure differs, with positive and negative trends
reported (Figure 2). In single cases, changes in exposure have clearly contributed to lower damage. For
example, in Vietnam 200,000 households were relocated to protected grounds after the flood in 2000.
Thus, the number of affected people was reduced by 88% (Table 1). Similarly, for the Mozambican case
the number of affected people was reduced by 93% mainly due to decreasing the number of settlements
in flood-prone areas after the event in 2000. The monetary damage was reduced by 94% and the fatalities
by 83% (Table 1).
In contrast, in the Italian case, industry moved out of the affected areas after the first flood, but was then
substitutedbyprivate residents over a longer time (Table 1). This lead to an increaseof exposure, particularly
the number of affected people increased by 86% (Table 1). This case highlights the necessity of keeping
flood risk awareness at a high level over long time periods.
In the German Elbe, Danube case the change of exposure is rather unclear. While EM-Dat [2015] reported
an increase of affected people by 82%, the affected area of residential and mixed use was calculated to be
reduced by 74% (Table 1). This combination appears very unlikely and points to high uncertainties associ-
ated with the exposure information (Figure 2).
During short time periods of a few years, exposure changes are hardly possible, as observable for the Rhine
floods in 1993 and 1995 in Germany (Figure 2). Large reductions in exposure are only observed in case
studies in which the time interval between the paired events is more than 10 years (Figure 2). Thus, it takes
time until spatial planning programs, settlement protection (e.g., by hard engineering works) or relocation
are implemented.
3.3. Vulnerability Changes
In almost all paired event cases, that is, success stories of risk reduction, a medium to large reduction in
vulnerability indicators is seen. Large reductions in all three vulnerability indicators occurred in both Ger-
man cases and in the Vietnamese case, indicating effective learning by societies, that is, of administra-
tive/governmental, commercial, and private sectors, after the focusing events using these as windows of
opportunity [Kreibich et al., 2011; Kingdon, 1995]. Apparently, measures to reduce vulnerability can be read-
ily implemented and unfold their positive effects quickly. For instance, after the Rhine flood in Germany in
1993, the number of precautionarymeasures that were implemented by private households, such as secur-
ing oil tanks or the deployment of mobile flood barriers, more than doubled [Bubeck et al., 2012]. Large
reductions in vulnerability were achieved between the floods in 1993 and 1995, resulting in a 67% lower
monetary damage in the latter (Table 1). Also in the other German paired flood event case in the Elbe and
Danube catchment, affected parties and authorities reduced their vulnerability after the extreme flood in
2002. Many governmental flood management programs and initiatives were launched, for instance, the
German Weather Service (DWD) has significantly improved its numerical weather forecast models and its
warningmanagement [Kreibich andMerz, 2007; Thieken et al., 2016b]. Also a high percentage of the private
households and companies adopted precautionary measures and were much better prepared for emer-
gency actions [Kreibich et al., 2011; Kienzler et al., 2015]. The comparison of theMekong flood events in 2000
and 2011 in Vietnam showed that considerable improvements regarding the vulnerability were possible,
supporting a significant reduction of monetary damage by 58% and of fatalities by 81% (Table 1).
In the Italian and Spanish cases, large reductions occurred in two vulnerability indicators and a small reduc-
tion in the third one. However, the timebetween the eventswas so long, that not only the effects of learning
after the first flood event can be observed during the second event; improved awareness andpreparedness,
as well as an improved emergencymanagement, are probably also due to general vulnerability decreasing
developments stimulated by policies such as the European Flood Directive [European Commission, 2007]
and the Hyogo/Sendai frameworks by UN-ISDR. In the Spanish case, monetary damage was reduced by
83% and fatalities by even 99%mainly due to a significantly improved early warning by themeteorological
services, based on advances in hydro-meteorologicalmonitoring andmodeling. Additionally, the activation
KREIBICH ET AL. ADAPTATION TO FLOOD RISK 958
Earth’s Future 10.1002/2017EF000606
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1
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un
g
et
al
.,
20
15
]
Bi
va
ria
te
p
ro
b
ab
ili
ty
of
p
ea
k
di
sc
ha
rg
e
an
d
vo
lu
m
e:
0.
1
[M
RC
,2
01
5]
;0
.0
2
[D
un
g
et
al
.,
20
15
]
Pr
ot
ec
tio
n
fa
ilu
re
s
0
0
45
00
km
di
ke
s
p
ar
tia
lly
/t
ot
al
ly
da
m
ag
ed
31
00
km
di
ke
s
p
ar
tia
lly
/t
ot
al
ly
da
m
ag
ed
13
1
di
ke
fa
ilu
re
s
30
di
ke
fa
ilu
re
s
in
cl
ud
in
g
3
m
aj
or
b
re
ac
he
s
[D
KK
V
,
20
15
]
12
70
km
di
ke
s
fa
ile
d/
w
er
e
ov
er
-t
op
p
ed
[D
M
C-
CC
FS
C
,
20
16
]
33
70
km
di
ke
s
fa
ile
d
[D
M
C-
CC
FS
C
,
20
16
]
Ex
p
os
ur
e
Pe
op
le
aff
ec
te
d
10
0,
00
0
[E
M
-D
at
,
20
15
]
N
D
a
30
,0
00
,0
00
36
,0
00
,0
00
33
0,
00
0
[E
M
-D
at
,
20
15
]
60
0,
00
0
[E
M
-D
at
,
20
15
]
∼
5
m
ill
io
n
p
eo
p
le
,8
95
,4
99
ho
us
es
aff
ec
te
d
[D
M
C-
CC
FS
C
,
20
16
]
59
0,
00
0
p
eo
p
le
,
17
6,
58
8
ho
us
es
aff
ec
te
d
[D
M
C-
CC
FS
C
,
20
16
]
(S
et
tl
em
en
t)
ar
ea
aff
ec
te
d
N
D
a
N
D
a
10
0,
25
0
km
2
54
,7
20
km
2
52
.6
km
2
(o
w
n
ca
lc
ul
at
io
n,
se
e
S3
)
13
.7
km
2
(o
w
n
ca
lc
ul
at
io
n,
se
e
S3
)
61
5,
70
4
ha
[D
M
C-
CC
FS
C
,
20
16
]
13
7,
59
9
ha
[D
M
C-
CC
FS
C
,
20
16
]
KREIBICH ET AL. ADAPTATION TO FLOOD RISK 959
Earth’s Future 10.1002/2017EF000606
Ta
b
le
1.
co
nt
in
ue
d
G
er
m
an
y
Rh
in
e
(S
up
p
or
tin
g
In
fo
rm
at
io
n
S1
,
Te
xt
S1
)
Ba
ng
la
de
sh
(S
up
p
or
tin
g
In
fo
rm
at
io
n
S1
,
Te
xt
S2
)
G
er
m
an
y
El
b
e,
D
an
ub
e
(S
up
p
or
tin
g
In
fo
rm
at
io
n
S1
,
Te
xt
S3
)
Vi
et
na
m
(S
up
p
or
tin
g
In
fo
rm
at
io
n
S1
,
Te
xt
S4
)
19
93
19
95
19
98
20
04
20
02
20
13
20
00
20
11
Ex
p
os
ur
e
ho
ts
p
ot
s
C
ol
og
ne
,
Ko
b
le
nz
,B
on
n
C
ol
og
ne
,
Ko
b
le
nz
,B
on
n
Ea
st
er
n
p
ar
to
f
D
ha
ka
C
it
y.
Sy
lh
et
ci
ty
,
ea
st
er
n
p
ar
to
f
D
ha
ka
C
it
y
D
re
sd
en
(C
ul
tu
ra
l
he
ri
ta
ge
)
Pa
ss
au
,D
eg
ge
n-
do
rf
,
H
al
le
(S
aa
le
)
N
o
p
ar
tic
ul
ar
ho
ts
p
ot
s
N
o
p
ar
tic
ul
ar
ho
ts
p
ot
s
Vu
ln
er
ab
ili
ty
La
ck
of
aw
ar
en
es
s
La
st
se
ve
re
flo
od
s
in
19
26
an
d
19
70
Ex
p
er
ie
nc
e
w
ith
flo
od
ev
en
tj
us
t
13
m
on
th
s
b
ef
or
e
[B
ub
ec
k
et
al
.,
20
12
]
H
ig
h
aw
ar
en
es
s
du
e
to
an
nu
al
flo
od
in
g,
la
st
se
ve
re
flo
od
s
in
19
87
an
d
19
88
In
cr
ea
se
d
co
p
in
g
ca
p
ac
it
y
du
e
to
de
cr
ea
si
ng
p
ov
er
ty
,
in
cr
ea
si
ng
ac
ce
ss
to
ed
uc
at
io
n
La
st
se
ve
re
flo
od
s
in
19
74
an
d
19
54
[K
re
ib
ic
h
et
al
.,
20
11
;K
re
ib
ic
h
an
d
Th
ie
ke
n,
20
09
]
Se
ve
ra
lr
ec
en
tfl
oo
ds
in
20
02
,2
00
5,
20
06
,
20
10
,2
01
1
[K
ie
nz
le
r
et
al
.,
20
15
]
La
st
se
ve
re
flo
od
22
ye
ar
s
ag
o
Ex
p
er
ie
nc
e
w
ith
20
00
flo
od
La
ck
of
p
re
p
ar
ed
ne
ss
Lo
w
p
re
p
ar
ed
ne
ss
[B
ub
ec
k
et
al
.,
20
12
;E
ng
el
et
al
.,
19
99
]
Im
p
ro
ve
d
ea
rl
y
w
ar
ni
ng
an
d
si
gn
.
In
cr
ea
se
d
p
re
p
ar
ed
ne
ss
[B
ub
ec
k
et
al
.,
20
12
;E
ng
el
et
al
.,
19
99
]
G
oo
d
p
re
p
ar
ed
ne
ss
an
d
ea
rl
y
w
ar
ni
ng
(fo
re
ca
st
s
fo
r2
4
an
d
48
h
le
ad
tim
es
)[
G
ai
n
et
al
.,
20
15
]
A
ft
er
19
98
,
fu
rt
he
ri
m
p
ro
ve
d
fo
re
ca
st
-
in
g/
w
ar
ni
ng
(fo
re
ca
st
s
fo
r7
2
h
le
ad
tim
e)
W
ar
ni
ng
s
re
la
tiv
el
y
la
te
an
d
im
p
re
ci
se
,l
ow
p
re
p
ar
ed
ne
ss
[K
re
ib
ic
h
an
d
M
er
z,
20
07
]
Si
gn
.I
m
p
ro
ve
d
w
ar
ni
ng
an
d
p
re
p
ar
ed
ne
ss
[T
hi
ek
en
et
al
.,
20
16
b
]
Lo
w
p
re
p
ar
ed
ne
ss
M
ed
iu
m
to
hi
gh
p
re
p
ar
ed
ne
ss
,
go
od
ea
rly
w
ar
ni
ng
In
su
ffi
ci
en
t
or
ga
ni
za
tio
na
l
em
er
ge
nc
y
m
an
ag
em
en
t
Pu
b
lic
flo
od
m
an
ag
em
en
t
b
ad
ly
p
re
p
ar
ed
Pu
b
lic
m
an
ag
em
en
t
si
gn
.I
m
p
ro
ve
d
du
e
to
le
ar
ni
ng
in
19
93
[E
ng
el
et
al
.,
19
99
]
W
ea
k
di
sa
st
er
p
re
p
ar
ed
ne
ss
an
d
re
sp
on
se
p
la
nn
in
g
W
ea
k
di
sa
st
er
p
re
p
ar
ed
ne
ss
an
d
re
sp
on
se
p
la
nn
in
g
Ex
er
ci
se
s
w
ith
in
in
di
vi
du
al
re
lie
f
or
ga
ni
za
tio
ns
Ev
er
y
2
ye
ar
s
tr
an
s-
or
ga
ni
za
tio
na
l
na
tio
na
lc
ris
is
m
an
ag
em
en
t
ex
er
ci
se
(L
Ü
KE
X
)
[T
hi
ek
en
et
al
.,
20
16
b
]
U
np
re
p
ar
ed
an
d
no
tw
el
l
or
ga
ni
ze
d
M
uc
h
b
et
te
r
or
ga
ni
ze
d,
fr
og
m
co
m
m
un
al
to
go
ve
rn
m
en
ta
l
le
ve
l
D
am
ag
e
fa
ta
lit
ie
s
5
5
10
50
73
0
21
[D
KK
V,
20
15
;
Th
ie
ke
n
et
al
.,
20
16
a]
14
[D
KK
V,
20
15
;
Th
ie
ke
n
et
al
.,
20
16
a]
48
1
[D
M
C-
CC
FS
C
,
20
16
]
89
[D
M
C-
CC
FS
C
,
20
16
]
M
on
et
ar
y
da
m
ag
eb
EU
R
76
7
m
ill
io
n
EU
R
25
6
m
ill
io
n
U
S$
50
00
m
ill
io
n
U
S$
22
00
m
ill
io
n
EU
R
14
.6
b
ill
io
n
[D
KK
V,
20
15
;
Th
ie
ke
n
et
al
.,
20
16
a]
EU
R
6
to
8
b
ill
io
n
[D
KK
V,
20
15
;T
hi
ek
en
et
al
.,
20
16
a]
U
S$
50
0
m
ill
io
n
[C
hi
nh
et
al
.,
20
16
]
U
S$
20
8.
9
m
ill
io
n
[C
hi
nh
et
al
.,
20
16
]
KREIBICH ET AL. ADAPTATION TO FLOOD RISK 960
Earth’s Future 10.1002/2017EF000606
Ta
b
le
1.
co
nt
in
ue
d
Po
la
nd
(S
up
p
or
tin
g
In
fo
rm
at
io
n
S1
,
Te
xt
S5
)
M
oz
am
b
iq
ue
(S
up
p
or
tin
g
In
fo
rm
at
io
n
S1
,
Te
xt
S6
)
It
al
y
(S
up
p
or
tin
g
In
fo
rm
at
io
n
S1
,
Te
xt
S7
)
Sp
ai
n
(S
up
p
or
tin
g
In
fo
rm
at
io
n
S1
,
Te
xt
S8
)
19
97
20
10
20
00
20
13
19
87
20
13
19
62
20
00
H
az
ar
d
Pr
ec
on
di
tio
ns
Sa
tu
ra
te
d
so
ils
af
te
r1
st
in
te
ns
e
p
re
ci
p
ita
tio
n
ev
en
t
(D
ec
is
iv
el
y)
sa
tu
ra
te
d
so
ils
Sa
tu
ra
te
d
so
ils
Le
ss
sa
tu
ra
te
d
so
ils
W
in
d
an
d
st
or
m
su
rg
e
ca
us
ed
b
ac
kw
at
er
eff
ec
ts
W
in
d
an
d
st
or
m
su
rg
e
ca
us
ed
b
ac
kw
at
er
eff
ec
ts
Ev
en
ta
ft
er
4
m
on
th
s
w
ith
ou
t
ra
in
fa
ll
Ev
en
ta
ft
er
so
m
e
w
ee
ks
w
ith
ou
t
ra
in
fa
ll
Pr
ec
ip
ita
tio
n
Ex
tr
em
e
ra
in
fa
ll
Ra
in
fa
ll
le
ss
ex
tr
em
e
th
an
in
19
97
5
w
ee
ks
of
he
av
y
p
er
si
st
en
tr
ai
nf
al
l
1
w
ee
k
of
he
av
y
ra
in
fa
ll
24
-h
ra
in
fa
ll—
re
tu
rn
p
er
io
d:
>
50
ye
ar
s
(3
h
rp
:1
1
ye
ar
s)
24
-h
ra
in
fa
ll
rp
:
30
ye
ar
s
(3
h
rp
:
20
ye
ar
s)
Ra
in
fa
ll
m
ax
.
6
m
m
/m
in
;
25
0
m
m
in
le
ss
th
an
3
h
[L
la
sa
t
et
al
.,
20
03
]
Ra
in
fa
ll
m
ax
.
10
0
m
m
/h
,
15
0
m
m
in
3
h
[L
la
sa
te
ta
l.,
20
03
]
H
yd
ro
lo
gi
ca
l
se
ve
rit
y
C
at
as
tr
.,
ra
re
flo
od
C
at
as
tr
.,
ra
re
flo
od
,b
ut
le
ss
se
ve
re
th
an
19
97
Fl
oo
d
le
ve
l1
3
m
(C
ho
kw
e)
Fl
oo
d
le
ve
l1
0
m
(C
ho
kw
e)
Sm
al
le
ra
re
a
aff
ec
te
d
th
an
20
13
La
rg
er
ar
ea
aff
ec
te
d
th
an
19
87
Ll
ob
re
ga
tR
iv
er
di
sc
ha
rg
e
at
ga
ug
e
M
ar
to
re
ll:
1.
55
0
m
3
/s
Ll
ob
re
ga
tR
iv
er
di
sc
ha
rg
e
at
ga
ug
e
M
ar
to
re
ll:
1.
40
0
m
3
/s
Pr
ot
ec
tio
n
fa
ilu
re
s
A
p
p
ro
xi
m
at
el
y
46
0
km
di
ke
s
da
m
ag
ed
37
di
ke
b
re
ac
he
s
N
D
a
D
ik
e
fa
ilu
re
in
C
ho
kw
e
12
00
m
di
ke
s
fa
ile
d
Se
ve
ra
ld
ik
es
ov
er
-t
op
p
ed
D
es
tr
uc
tio
n
of
b
rid
ge
s
an
d
hy
dr
au
lic
st
ru
ct
ur
es
D
es
tr
uc
tio
n
of
b
rid
ge
s
Ex
p
os
ur
e
Pe
op
le
aff
ec
te
d
16
0,
00
0
p
eo
p
le
ev
ac
ua
te
d
[B
ut
ts
et
al
.,
20
07
];
46
,0
00
ho
us
es
aff
ec
te
d
14
,5
65
fa
m
ili
es
ev
ac
ua
te
d;
18
,1
94
re
si
de
nt
ia
l
b
ui
ld
in
gs
aff
ec
te
d
4,
50
0,
00
0
31
5,
91
0
A
b
ou
t7
00
0
A
b
ou
t1
3,
00
0
>
50
,0
00
>
20
,0
00
(S
et
tl
em
en
t)
ar
ea
aff
ec
te
d
66
5,
00
0
ha
[K
un
dz
ew
ic
z
et
al
.,
20
12
]
68
2,
89
4
ha
14
0,
00
0
ha
17
0,
00
0
ha
In
du
st
rie
s,
cu
lt
iv
at
ed
fie
ld
s
U
rb
an
ar
ea
,r
oa
ds
,
cu
lt
iv
at
ed
fie
ld
s
50
9,
35
km
2
hi
gh
ly
aff
ec
te
d
ar
ea
50
37
,4
2
km
2
aff
ec
te
d
ar
ea
Ex
p
os
ur
e
ho
ts
p
ot
s
Kl
od
zk
o,
Ra
ci
b
or
z,
O
p
ol
e,
W
ro
cl
aw
Sa
nd
om
ie
rz
,
Ta
rn
ob
rz
eg
,
W
ilk
ow
,S
w
in
ia
ry
.
G
az
a
p
ro
vi
nc
e
(C
ho
kw
e
to
w
n,
X
ai
X
ai
C
it
y)
G
az
a
p
ro
vi
nc
e
(C
ho
kw
e
to
w
n,
X
ai
X
ai
C
it
y)
U
rb
an
ar
ea
s,
ho
sp
ita
ls
,r
oa
ds
,
ra
ilw
ay
s,
in
du
st
ri
es
U
rb
an
ar
ea
s,
ho
sp
ita
ls
,r
oa
ds
,
ra
ilw
ay
s
Va
llè
s
co
un
ty
in
du
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KREIBICH ET AL. ADAPTATION TO FLOOD RISK 961
Earth’s Future 10.1002/2017EF000606
Ta
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KREIBICH ET AL. ADAPTATION TO FLOOD RISK 962
Earth’s Future 10.1002/2017EF000606
of the INUNCAT Civil Protection Plan for floods supported damage reduction (Table 1). Technical develop-
ments can also support improved preparedness: For instance, early warning information was successfully
spread through mobile phone and social networks during the 2013 flood in Italy (Table 1).
Vulnerability did not decrease much in Bangladesh between 1998 and 2004 (Figure 2). Yet, an extraordi-
nary reduction of vulnerability had already taken place in the previous decades. For instance, the 1974 flood
killed about 29,000 people, 40 times more than the number of fatalities caused 30 years after by the 2004
flood, which had a similar magnitude [Mechler and Bouwer, 2015]. This reduction of people’s vulnerability
is explained by a number of factors, such as the emergence of spontaneous or informal processes (e.g.,
flood experience leading to increased awareness and preparedness) or the implementation of deliberate
and formal measures like the implementation of building codes. Bangladesh also had external assistance
and invested about 10 billion USD over the last five decades into disaster risk reduction [World Bank, 2010].
During the flood of 1998, the Flood Forecasting and Warning Centre of Bangladesh provided flood fore-
casting for 24 and 48 h lead-times with accompanyingwarningmessages [Gain et al., 2015]. After this flood,
further improvements were undertaken with the project “Consolidation and Strengthening of Flood Fore-
casting and Warning Services”. During the 2004 flood, the early warning system provided forecasts with a
72-h lead-time (Table 1).
In Poland, most improvements occurred in the administrative/governmental sector. Since the 1997 flood,
the forecasting andwarning systems of Poland have been significantly improved both technically and orga-
nizationally. In 2007, the Crisis Management Act constituted the organizational structure of the emergency
management. This clarification of the legal basis for operations and division of responsibility lead to sig-
nificant improvements of the organizational emergency management, which was proven during the 2010
flood. In Mozambique, vulnerability reduction is mainly attributed to increased awareness and prepared-
ness. This has been achieved primarily by promoting educational programs on flood risk at different levels
[Lumbroso et al., 2008]. Educational tools included: (1) material on sustainable flood risk management for
organizations involved inwater planning; (2) posters and pamphlets to raise flood awareness at community
level; and (3) “living with floods” manual and card game to raise awareness among young people and less
literate adults, whichwere distributed to rural and urban communities throughoutMozambique [Lumbroso
et al., 2008].
Overall, across the paired event cases, the observed reduction in vulnerability is in line with the observed
decrease in flood damage, which suggests an important role of vulnerability in adaptation to flood risk.
However, themajority of the changes in vulnerability are based on limited evidence (depicted in Figure 2 by
open symbols), which is in contrast to the majority of trends in hazard and damage, the latter beingmainly
based on robust evidence (Figure 2). For exposure, the underlying evidence is somewhere in between, with
about half of the observed changes being based on limited evidence. This is on the one handdue to the fact
that many hazard parameters, like precipitation or discharge, can be measured and are often continuously
monitored, in contrast to vulnerability indicators such as awareness or preparedness,which cannot be easily
measured and are only recorded occasionally, mostly after extreme damaging events. On the other hand,
this also reflects the fact that far more event analyses focus on the hydrological processes of floods than
on exposure or vulnerability. Thus, our knowledge on vulnerability is far more limited. Both German cases
are exceptions, as detailed vulnerability analyses were undertaken based on postevent surveys of affected
parties (Table 1).
4. Conclusions
This first study of paired flood events shows how societies adapt to flood risk through a variety of actions.
There is a clear signal that the first event acted as a trigger for raising risk awareness, preparedness, and
improvements of organizational emergency management, which in turn reduced vulnerability and dam-
age. Also, reinforcing floodprotection infrastructures reduced flooddamage. Exposure can also be reduced,
but it requires policy and legal changes and enforcement in the area of land use planning, and its effects
mostly occur on a longer (decadal) time scale. Our analysis underlines the essential role of reducing vulnera-
bility for effective adaptation, but also the need for an improvedunderstanding of vulnerability, in the sense
of its changes and effects ondamage and risk.Webelieve that our compilation of paired flood events canbe
the starting point for a broader international initiative to collect and analyze a large number of paired event
KREIBICH ET AL. ADAPTATION TO FLOOD RISK 963
Earth’s Future 10.1002/2017EF000606
studies, for example, in the framework of the IAHSs Panta Rhei initiative. Generally, the challenge remains
to stimulate adaptation processes without the occurrence of disastrous floods andmake risk reduction per-
sistent over long time scales.
References
Armitage, D., M. Marschke, and R. Plummer (2008), Adaptive co-management and the paradox of learning, Global Environ. Change, 18,
86–98.
Birkland, T. A. (1998), Focusing events, mobilization, and agenda setting, J. Public Policy, 18(3), 53–74.
Blöschl, G., M. Sivapalan, T. Wagener, A. Viglione, and H. Savenije (2013), Runoff Prediction in Ungauged Basins. Synthesis across Processes,
Places and Scales, Cambridge Univ. Press, New York.
Bouwer, L. M. (2011), Have disaster losses increased due to anthropogenic climate change? Bull. Am. Meterol. Soc., 92(1), 39–46.
Brooks, N., W. N. Adger, and P. M. Kelly (2005), The determinants of vulnerability and adaptive capacity at the national level and the
implications for adaptation, Global Environ. Change, 15(2), 151–163. https://doi.org/10.1016/j.gloenvcha.2004.12.006.
Brouwer, R., S. Akter, L. Brander, and E. Haque (2007), Socioeconomic vulnerability and adaptation to environmental risk: A case study of
climate change and flooding in Bangladesh, Risk Anal., 27(2), 313–326.
Brown, A. E., L. Zhan, T. A. McMahon, A. W. Western, and R. A. Vertessy (2005), A review of paired catchment studies for determining
changes in water yield resulting from alterations in vegetation, J. Hydrol., 310, 1–4. https://doi.org/10.1016/j.jhydrol.2004.12.010.
Bubeck, P., W. J. W. Botzen, H. Kreibich, and J. C. J. H. Aerts (2012), Long-term development and effectiveness of private flood mitigation
measures: An analysis for the German part of the river Rhine, Nat. Hazards Earth Syst. Sci., 12(11), 3507–3518.
Butts, M., A. Dubicki, K. Stronska, G. Jorgensen, A. Nalberczynski, A. Lewandowski, and T. vanKalken (2007), Flood forecasting for the
upper and middle Odra River basin, in Flood Risk Management in Europe, edited by S. Begum, M. J. F. Stive and J. W. Hall, Springer,
Dordrecht, The Neth.
Chinh, D. T., N. V. Dung, H. Kreibich, and P. Bubeck (2016), The 2011 flood event in the Mekong Delta: Preparedness, response, damage
and recovery of private households and small businesses, Disasters, 40(4), 753–788. https://doi.org/10.1111/disa.12171.
CHRR (Center for Hazards and Risk Research, Columbia University), and CIESIN (Center for International Earth Science Information
Network, Columbia University) (2005), Global Flood Hazard Frequency and Distribution, NASA Socioecon. Data and Appl. Center
(SEDAC), Palisades, N. Y. https://doi.org/10.7927/H4668B3D.
Di Baldassarre, G., A. Viglione, G. Carr, L. Kuil, K. Yan, L. Brandimarte, and G. Blöschl (2015), Perspectives on socio-hydrology: Capturing
feedbacks between physical and social processes,Water Resour. Res., 51, 4770–4781.
DKKV (German Committee for Disaster Reduction) (2015), Das Hochwasser im Juni 2013: Bewährungsprobe für das
Hochwasserrisikomanagement in Deutschland. DKKV-Schriftenreihe Nr. 53, Bonn, ISBN 978-3-933181-62-6, 207 S (in German).
DMC-CCFSC (Disaster Management Center - Central Committee for Flood and Storm Control) (2016), 25 Jun. 2017. [Available at http://
www.dmc.gov.vn, http://118.70.74.167:8081/DesInventar/profiletab.jsp?countrycode=vnn&continue=y].
Domeneghetti, A., F. Carisi, A. Castellarin, and A. Brath (2015), Evolution of flood risk over large areas: Quantitative assessment for the Po
River, J. Hydrol., 527, 809–823. https://doi.org/10.1016/j.jhydrol.2015.05.043.
Duan, Q., J. Schaake, V. Andréassian, S. Franks, G. Goteti, H. V. Gupta, Y. M. Gusev, F. Habets, A. Hall, L. Hay, et al. (2006), Model parameter
estimation experiment (MOPEX): An overview of science strategy and major results from the second and third workshops, J. Hydrol.,
320, 3–17.
Dung, N. V., B. Merz, A. Bárdossy, and H. Apel (2015), Handling uncertainty in bivariate quantile estimation – An application to flood
hazard analysis in the Mekong Delta, J. Hydrol., 527, 704–717. https://doi.org/10.1016/j.jhydrol.2015.05.033.
EM-Dat (2015), Data from “International Disaster Database” 1 Oct. 2015. [Available at http://www.emdat.be/].
Engel, H., N. Busch, K. Daamen, J. Helm, M. Keller, J. Ottens, B. Parmet, and E. Sprokkereef (1999), Eine Hochwasserperiode im Rheingebiet:
Extremereignisse zwischen Dez. 1993 und Febr. 1995, , Bericht Nr. I-17, Int. Komm. für die Hydrol. des Rheingebietes (KHR).
European Commission (2007), Directive 2007/60/EC of the European Parliament and of the Council of 23 October 2007 on the
Assessment and Management of Flood Risks (Floods Directive). Eur. Comm., Brussels, Belgium.
Faccini, F., F. Luino, A. Sacchini, and L. Turconi (2015), Flash flood events and urban development in genoa (Italy): Lost in translation, in
Engineering Geology for Society and Territory, vol. 5, edited by G. Lollino, A. Manconi, F. Guzzetti, M. Culshaw, P. Bobrowsky and F. Luino,
Springer, Basel, Switz., 797–801.
Ferguson, A. P., and W. S. Ashley (2017), Spatiotemporal analysis of residential flood exposure in the Atlanta, Georgia metropolitan area,
Nat. Hazards, 87(2), 989–1016. https://doi.org/10.1007/s11069-017-2806-6.
Gain, A. K., V. Mojtahed, C. Biscaro, S. Balbi, and C. Giupponi (2015), An integrated approach of flood risk assessment in the eastern part of
Dhaka City, Nat. Hazards, 29(3), 1499–1530. https://doi.org/10.1007/s11069-015-1911-7.
IKSE (Internationale Kommission zum Schutz der Elbe) (2001), Bestandsaufnahme des vorhandenen Hochwasserschutzniveaus im
Einzugsgebiet der Elbe. Magdeburg, Jan. 2001, 74 pp, 23 Jun. 2017. [Available at http://www.ikse-mkol.org/fileadmin/media/user_
upload/D/06_Publikationen/02_Hochwasserschutz/2001_IKSE-Bestandsaufnahme_Hochwasserschutzniveau.pdf]
IPCC (Intergovernmental Panel on Climate Change) (2012),Managing the Risks of Extreme Events and Disasters to Advance Climate Change
Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change, Cambridge Univ. Press,
New York.
Jongman, B., H. C. Winsemius, J. C. J. H. Aerts, E. C. dePerez, M. K. vanAalst, W. Kron, and P. J. Ward (2015), Declining vulnerability to river
floods and the global benefits of adaptation, Proc. Natl. Acad. Sci. U. S. A., E2271–E2280 https://doi.org/10.1073/pnas.1414439112.
Kelly, P. M., and W. N. Adger (2000), Theory and practice in assessing vulnerability to climate change and facilitating adaptation, Clim.
Change, 47(4), 325–352. https://doi.org/10.1023/A:1005627828199.
Kienzler, S., I. Pech, H. Kreibich, M. Müller, and A. H. Thieken (2015), After the extreme flood in 2002: Changes in preparedness, response
and recovery of flood-affected residents in Germany between 2005 and 2011, Nat. Hazards Earth Syst. Sci., 15, 505–526.
Kingdon, J. W. (1995), Agendas, Alternatives, and Public Policies, 2nd ed., Longman, Harlow, U. K.
Klijn, F., H. Kreibich, H. deMoel, and E. Penning-Rowsell (2015), Adaptive flood risk management planning based on a comprehensive
flood risk conceptualization,Mitig. Adapt. Strateg. Global Change, 20(6), 845–864.
Kreibich, H., and B. Merz (2007), Lessons learned from the Elbe river floods in August 2002 - With a special focus on flood warning, in
Extreme Hydrological Events: New Concepts for Security. NATO Science Series 78, edited by O. F. Vasiliev, P. H. A. J. M. Gelder, E. J. Plate
and M. V. Bolgov, Springer, Dordrecht, The Neth., 69–80.
Acknowledgments
The present work was developed by the
Panta Rhei Working Group “Changes in
flood risk” within the framework of the
Panta Rhei Research Initiative of the
International Association of Hydrolog-
ical Sciences (IAHS). All data and infor-
mation used for this study are available
in Appendix S1 (texts S1 to S8).
KREIBICH ET AL. ADAPTATION TO FLOOD RISK 964
Earth’s Future 10.1002/2017EF000606
Kreibich, H., and A. H. Thieken (2009), Coping with floods in the city of Dresden, Germany, Nat. Hazards, 51(3), 423–436.
Kreibich, H., I. Seifert, A. H. Thieken, E. Lindquist, K. Wagner, and B. Merz (2011), Recent changes in flood preparedness of private
households and businesses in Germany, Reg. Environ. Change, 11(1), 59–71.
Kuhlicke, C., A. Scolobig, S. Tapsell, A. Steinfuhrer, and B. deMarchi (2011), Contextualizing social vulnerability: Findings from case studies
across Europe, Nat. Hazards, 58(2), 789–810.
Kundzewicz, Z. W., A. Dobrowolski, H. Lorenc, T. Niedz´wiedz´, I. Pinskwar, and P. Kowalczak (2012), Floods in Poland, in Changes in Flood
Risk in Europe, edited by Z. W. Kundzewicz , IAHS Press and CRC Press/Balkema, Wallingford, U. K., 319–334.IAHS Special Publication, 10
Llasat, M. C., T. Rigo, and M. Barriendos (2003), The “Montserrat-2000”flash-flood event: A comparison with the floods that have occurred
in the north-eastern Iberian peninsula since the 14th century, Int. J. Climatol., 23, 453–469.
Lumbroso, D., D. Ramsbottom, and M. Spaliveiro (2008), Sustainable flood risk management strategies to reduce rural communities’
vulnerability to flooding in Mozambique, J. Flood Risk Manage., 1, 34–42.
Mastrandrea, M. D., C. B. Field, T. F. Stocker, O. Edenhofer, K. L. Ebi, D. J. Frame, H. Held, E. Kriegler, K. J. Mach, P. R. Matschoss, G.-K. Plattner,
G. W. Yohe, and F.W. Zwiers (2010), Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of
Uncertainties, Intergovernmental Panel on Climate Change (IPCC). 14 Apr. 2016. [Available at http://www.ipcc.ch].
McRobie, A., T. Spener, and H. Gerritsen (2005), The big flood: North Sea storm surge, Philos. Trans. R. Soc. A, 363, 1263–1270. https://doi
.org/10.1098/rsta.2005.1567.
Mechler, R., and L. M. Bouwer (2015), Understanding trends and projections of disaster losses and climate change: Is vulnerability the
missing link? Clim. Change, 133(1), 23–35.
Merz, B., J. Hall, M. Disse, and A. Schumann (2010), Fluvial flood risk management in a changing world, Nat. Hazards Earth Syst. Sci, 10,
509–527, www.nat-hazards-earth-syst-sci.net/10/509/2010/.
Merz, B., Z. W. Kundzewicz, J. Delgado, Y. Hundecha, and H. Kreibich (2012), Detection and attribution of changes in flood hazard and risk,
in Changes in Flood Risk in Europe, edited by Z. W. Kundzewicz, IAHS Special Publication, 10, IAHS Press and CRC Press/Balkema,
Wallingford, U. K., 435–454.
MRC (Mekong River Commission) (2015), Annual Mekong Flood Report 2011. Mekong River Comm., 72 pp.
Müller, U. (2010), Hochwasserrisikomanagement. Theorie und Praxis, Vieweg+Teubner Verlag, Berlin, Germany. ISBN: 978-3-8348-1247-6.
Nakamura, I., and M. C. Llasat (2017), Policy and systems of flood risk management: a comparative study between Japan and Spain, Nat.
Hazards, 87(2), 919–943. https://doi.org/10.1007/s11069-017-2802-x.
Nkwunonwo, U. C., M. Whitworth, and B. Baily (2016), Review article: A review and critical analysis of the efforts towards urban flood risk
management in the Lagos region of Nigeria, Nat. Hazards Earth Syst. Sci., 16(2), 349–369. https://doi.org/10.5194/nhess-16-349-2016.
Orlandini, S., G. Moretti, and J. D. Albertson (2015), Evidence of an emerging levee failure mechanism causing disastrous floods in Italy,
Water Resour. Res., 51, 7995–8011. https://doi.org/10.1002/2015WR017426.
Pahl-Wostl, C. (2009), A conceptual framework for analysing adaptive capacity and multi-level learning processes in resource governance
regimes, Glob. Environ. Change, 19, 354–365.
Prosdocimi, I., T. R. Kjeldsen, and J. D. Miller (2015), Detection and attribution of urbanization effect on flood extremes using
nonstationary flood frequency models,Water Resour. Res., 51, 4244–4262.
Schröter, K., M. Kunz, F. Elmer, B. Mühr, and B. Merz (2015), What made the June 2013 flood in Germany an exceptional event? A
hydro-meteorological evaluation, Hydrol. Earth Syst. Sci., 19, 309–327.
Tapsell, S. M., E. C. Penning-Rowsell, S. M. Tunstall, and T. L. Wilson (2002), Vulnerability to flooding: Health and social dimensions, Philos.
Trans. R. Soc. Lond. A, 360(1796), 1511–1525. https://doi.org/10.1098/rsta.2002.1013.
Thieken, A. H., T. Bessel, S. Kienzler, H. Kreibich, M. Müller, S. Pisi, and K. Schröter (2016a), The flood of June 2013 in Germany: Howmuch
do we know about its impacts? Nat. Hazards Earth Syst. Sci., 16, 1519–1540.
Thieken, A. H., S. Kienzler, H. Kreibich, C. Kuhlicke, M. Kunz, B. Mühr, M. Müller, A. Otto, T. Petrow, S. Pisi, et al. (2016b), Review of the flood
risk management system in Germany after the major flood in 2013, Ecol. Soc., 21, 2.
Thywissen, K. (2006), Components of risk – A comparative glossary. Source, vol. 2.
Turner, B. L., P. A. Matson, J. J. McCarthy, R. W. Corell, L. Christensen, N. Eckley, G. K. Hovelsrud-Broda, J. X. Kasperson, R. E. Kasperson, A.
Luers, et al. (2003), A framework for vulnerability analysis in sustainability science, Proc. Natl. Acad. Sci. U. S. A, 100(14), 8080–8085.
https://doi.org/10.1073/pnas.1231334100.
UNISDR (United Nations International Strategy for Disaster Reduction) (2015), GAR 2015Making Development Sustainable: The Future of
Disaster Risk Management, UN Int. Strat. for Disaster Reduction Secretariat, Geneva, Switz.
Van Koningsveld, M., J. P. M. Mulder, M. J. F. Stive, L. Van der Valk, and A. W. Van der Weck (2008), Living with sea-level rise and climate
change: A case study of the Netherlands, J. Coast. Res., 24, 367–379.
Van Loon, A. F., K. Stahl, G. Di Baldassarre, J. Clark, S. Rangecroft, N. Wanders, T. Gleeson, A. I. J. M. Van Dijk, L. M. Tallaksen, J. Hannaford,
et al. (2016), Drought in a human-modified world: Reframing drought definitions, understanding, and analysis approaches, Hydrol.
Earth Syst. Sci., 20, 3631–3650. https://doi.org/10.5194/hess-20-3631-2016.
Wisner, B., P. Blaike, T. Cannon, and I. Davis (2004), At Risk: Natural Hazards, People’s Vulnerability and Disasters, Routledge, London.
World Bank (2010), Economics of Adaptation to Climate Change. Synthesis Report, World Bank, Washington, D. C.
World Bank (2016), Data from “GDP per capita, PPP (current international $)” World Development Indicators database. 14 Apr. 2016.
[Available at http://databank.worldbank.org/data/reports.aspx?source=world-development-indicators].
KREIBICH ET AL. ADAPTATION TO FLOOD RISK 965