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Published in Global and Planetary Change
A global assessment of the societal impacts of
glacier outburst floods
Jonathan L. Carrivick1 and Fiona S. Tweed2
1School of Geography, University of Leeds, Woodhouse Lane, Leeds, West Yorkshire, LS2 9JT, UK
2Geography, Staffordshire University, Leek Road, Stoke-on-Trent, Staffordshire, ST4 2DF, UK
Correspondence to:
Dr. Jonathan Carrivick,
email: j.l.carrivick@leeds.ac.uk
tel.:+44 (0)113 343 3324
Abstract
Glacier outburst floods are sudden releases of large amounts of water from a glacier. They
are a pervasive natural hazard worldwide. They have an association with climate primarily
via glacier mass balance and their impacts on society partly depend on population pressure
and land use. Given the ongoing changes in climate and land use and population
distributions there is therefore an urgent need to discriminate the spatio-temporal patterning
of glacier outburst floods and their impacts. This study presents data compiled from 20
countries and comprising 1348 glacier floods spanning 10 centuries. Societal impacts were
assessed using a relative damage index based on recorded deaths, evacuations, and
property and infrastructure destruction and disruption. These floods originated from 332
sites; 70 % were from ice-dammed lakes and 36 % had recorded societal impact. The
number of floods recorded has apparently reduced since the mid-1990s in all major world
regions. Two thirds of sites that have produced > 5 floods (n = 32) have floods occurring
progressively earlier in the year. Glacier floods have directly caused at least: 7 deaths in
Iceland, 393 deaths in the European Alps, 5745 deaths in South America and 6300 deaths
in central Asia. Peru, Nepal and India have experienced fewer floods yet higher levels of
damage. One in five sites in the European Alps has produced floods that have damaged
farmland, destroyed homes and damaged bridges; 10 % of sites in South America have
produced glacier floods that have killed people and damaged infrastructure; 15 % of sites in
central Asia have produced floods that have inundated farmland, destroyed homes,
damaged roads and damaged infrastructure. Overall, Bhutan and Nepal have the greatest
national-level economic consequences of glacier flood impacts. We recommend that
accurate, full and standardised monitoring, recording and reporting of glacier floods is
essential if spatio-temporal patterns in glacier flood occurrence, magnitude and societal
impact are to be better understood. We note that future modelling of the global impact of
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glacier floods cannot assume that the same trends will continue and will need to consider
combining land-use change with probability distributions of geomorphological responses to
climate change and to human activity.
Key words: jökulhlaup; GLOF; glacier lake; proglacial; hazard; risk
Highlights:
•1348 floods from 332 sites, and 36 % of these sites have recorded societal impact
•Over 12,000 deaths recorded globally due to glacier floods
•Recurrence intervals calculated based on volume, discharge and damage
•Damage type and index determined per event, per country and per major world
region
1. Introduction and rationale
Glacier outburst floods, or ‘jökulhlaups’, are sudden releases of large amounts of water
from a glacier. These floods typically have hydrograph characteristics of dam break floods
since they are often initiated by failure of ice, moraine or landslide dams impounding glacial
lakes (Tweed and Russell, 1999). They also include a subset of floods generated near-
instantaneously by subglacial volcanic or geothermal activity and by heavy rainfall routed
through glacier catchments (Roberts, 2005).
Glacier outburst flood occurrence and hydrograph characteristics are linked to climate via
glacier downwasting and consequent meltwater production (Haeberli and Beniston, 1998).
The formation and evolution of ice- and moraine-dammed lakes are related to
environmental factors which are, in turn, heavily dependent on climatic conditions (Carrivick
and Tweed, 2013). In particular, the attributes of some glacier outburst floods including
timing (date of initiation) and peak discharge can be controlled by climate (e.g. Ng et al.,
2007; Kingslake and Ng, 2013, respectively).
Present global deglaciation is increasing the number and extent of glacial lakes around the
world (e.g. Paul et al., 2007; Gardelle et al., 2011; Wang et al., 2011; Carrivick and Tweed,
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2013; Carrivick and Quincey, 2014; Tweed and Carrivick, 2015). There is a causal
relationship between deglaciation and volcanic activity (e.g. Maclennan et al., 2002; Tuffen,
2010; McGuire, 2013) and volcanic activity beneath ice masses can generate glacier
outburst floods both through the near-instantaneous melting of ice and from the drainage of
meltwater temporarily stored as a water pocket or glacier lake.
Glacier outburst floods have been recorded for many centuries, particularly in Iceland and
in Europe where there are records from the 1500s onwards. The societal impact of glacier
floods most obviously includes direct destruction and damage to infrastructure and property,
disruption to communities and loss of life, as has been reported from Iceland (e.g.
Thorarinsson, 1939, 1974; Rist, 1984; Ives, 1991; Tómasson, 1996; Björnsson, 1976,
2002), the European Alps (e.g. Haeberli et al., 1989; Raymond et al. 2003; Huss et al.,
2007), South America (e.g. Carey, 2005; Iribarren Anacona et al., 2015) and the Himalaya
(e.g. Mool et al., 2001; Ives et al., 2010). Repeated glacier outburst floods from Lac du
Mauvoisin, Switzerland, which killed hundreds of people and destroyed houses and
infrastructure (Tufnell, 1984; Woodward, 2014), have been recognised as influencing the
direction of scientific thinking on glacial geology and geomorphology, thus developing
modern science. Firstly, in ‘Principles of Geology’, Lyell (1830) effectively challenged
catastrophism and paved the way for scientific theory that recognised the former existence
of ice ages and therefore a changing climate. Secondly, Ignaz Venetz, who was an
engineer asked to drain water from Lac du Mauvoisin in Switzerland, and was subsequently
asked to make the first survey the glaciers of the Alps. His ground-breaking field work,
alongside that of Jean de Charpentier, Jens Esmark, William Buckland and ultimately Louis
Agassiz, explored the links between glacial fluctuations and environmental change.
Recent major studies of glacier outburst floods have concerned the conceptualisation of
sources, triggers and mechanisms (e.g. Tweed and Russell, 1999; Björnsson, 2003),
physical mechanisms governing meltwater generation and routing through a glacier (e.g.
Roberts, 2005; Kingslake, 2013, 2015; Flowers, 2015) and landscape impacts (e.g.
Shakesby, 1985; Maizels, 1991, 1997; Carrivick et al., 2004a,b; Carrivick, 2007; Russell et
al., 2006). Whilst these and other regionally-focused research papers (see citations in Table
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1) frequently refer to the impacts of glacier outburst floods as being an important rationale
for research, there has not yet been a comprehensive global assessment of the impacts of
glacier outburst floods on communities and economies.
The aim of this study is to provide the first global analysis of the societal impacts of glacier
floods. We focus primarily on descriptive statistics of glacier floods and of their relative
impact, because as it will be shown, a precise definition of the absolute impact of most
events is impossible given the nature of existing records. In this study we define ‘societal’
as ‘of or relating to the structure, organisation or functioning of human communities (AHD,
2011). We also shorten ‘glacier outburst floods’ to glacier floods for simplicity hereon in this
text.
2. Data sources and methods
We created our own database of glacier floods by initially extracting data from published
glacier flood inventories (see citations in Table 1). These flood inventories have generally
focused on timing and to a lesser degree on magnitude and whilst both are interesting from
a phenomenological perspective, the ‘date’ and ‘peak discharge’ attributes reported in the
literature are not consistently recorded or calculated, as will be discussed below. In this
study, we used several physical attributes together with societal impact attributes primarily
to estimate the first-order global societal impact of glacier floods, but also to recognise
linkages between physical characteristics and thus to assist correct interpretation of the
potential landscape and societal responses to climate and land use change (Pelletier et al.,
2015).
Physical and societal impact data was compiled from published literature and available
regional/national reports, with guidance from a number of key research experts, to whom
we are indebted for their helpful advice and assistance (Table 1). Overall we have compiled
records of 1348 glacier floods (Figure 1; Table 2). This is the biggest single compilation of
the occurrence and characteristics of glacier floods to date. Of this total, 9 % were in
Scandinavia, 22 % were in the European Alps, 6 % were in South America, 16 % were in
central Asia, 25 % were in north-west America, 20 % were in Iceland and 2 % were in
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Greenland. Definition of these global regions was informed by the most recent and most
comprehensive global glacier mapping project by Pfeffer et al. (2014).
We stress that our study is based on records of events that we were able to identify and
access and for which attributes are available. We acknowledge that there will be events
that: (i) we have not been able to capture due to lack of data recording and/or availability,
and (ii) we are aware of, but for which attributes are either missing or inconsistent. For
example, we know of a few glacier outburst floods that have occurred in New Zealand (e.g.
Davies et al., 2003; Goodsell et al., 2005), Svalbard (e.g. Wadham et al., 2001; Cooper et
al., 2002), the Canadian high arctic (e.g. Cogley and McCann, 1976) and on the Antarctic
Peninsula (e.g. Sone et al., 2007), but these floods do not have a full date (day/month/year)
associated with them nor records of any other attributes and therefore are not considered
further in this study. We have not included glacier floods from supraglacial lakes in western
Greenland or from subglacial lakes in Antarctica for the same reason.
2.1 Physical attributes
Lake name, glacier name, location/region/river, country, latitude, longitude, date, volume,
peak discharge, trigger mechanism and dam type were recorded in this study. It was difficult
to discriminate glacier flood records from other ‘floods’ in publically-available natural
hazards databases, so cross-checking attributes of date and place and ‘name’ was vital. In
a minority of cases, extra cross-checking was required to make the correct definition of the
attribute ‘name’ because it was not necessarily obvious if that name pertained to a lake or
to a glacier, or perhaps even to a catchment, valley river or region. Glacier floods that have
been reported without an exact source being known include those in Canada (Geertsema
and Clague, 2005), and in the Shimshal region of Pakistan (e.g. Iturrizaga, 2005), for
example. Additionally:
•A single glacier can have multiple lakes that have drained;
•A single lake can drain multiple times: well-documented examples include Tulsequah
Lake in Canada (e.g. Marcus, 1960), Merzbacher Lake in Kyrgyzstan (Ng et al.,
2007), Gornersee in Switzerland (Huss et al., 2007) and Grímsvötn and Grænalón in
Iceland (Björnsson, 1976; 2003);
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•Large floods can have multiple outlets and inundate multiple rivers and this is
probably more common than apparent in the records due to a tendency to report
from the largest river only.
•The same event can occur in different countries, because some events are trans-
boundary, originating in one country and routing into another.
We determined latitude and longitude for 77 % of our records (Supplementary Information),
and have converted the varying coordinate systems used in the literature to a standard
(global latitude and longitude in format of decimal degrees, geoid WGMS84). Regarding the
‘date’ attribute, the most commonly reported format was simply ‘year’ but > 50 % also have
month and day, which permits analyses of seasonality and assists discrimination of multiple
events from the same site within a single year. Since glacier floods often span several days
we usually remained uncertain as to whether the day reported pertained to that of the flood
onset at source, the time of peak discharge, or to the time of any gauging or flood impact
down valley. To give an indication of the spatial scales being considered Mason (1929)
reported a 21 m rise in river level at 300 km from source, and also destruction of the village
of Abadan 400 km from source in the 1926 Shyok floods in Pakistan.
We also encountered many cases where the timing of a glacier flood as reported in the
literature had been constrained for example via remotely-sensed images that bracketed the
flood in time. Some literature noted that some glacier lakes drained every year for several
decades, but there were no other details available (e.g. Vatnsdalslón, Iceland reported in
Thorarinsson, 1939; Glacier lake Moreno had about 24 events registered between 1917
and 2012 and Glacier lake Colonia had floods every summer between 1928 to 1958).
Additionally, some glacier lakes are hydrologically connected so that as one drains it
causes another in the cascade to do the same, for example at Brady Glacier (Capps and
Clague, 2014) and in the Bhutanese Himalaya (Bajracharya et al., 2007). As well as cross-
checking dates between multiple literature sources, we converted all dates into the same
date format (day/month/year) and to further assist numerical analysis we also incorporated
four columns of ‘day’, ‘month’, ‘year’ and ‘Julian day of year’.
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In assessing flood magnitude, the attribute volume was compiled and converted to units of
M m3. However, in most cases we have been unable to determine whether the reported
volume is: (i) measured outflow (with known lake bathymetry and lake drawdown) with
consideration of any coincident internal water release (e.g. Huss et al., 2007; Anderson et
al., 2003), or (ii) reconstructed from gauged (and separated baseflow) hydrograph analysis
(e.g. Ng et al., 2007), (iii) pertaining to water and sediment (e.g. if from a gauged stage
record), or only a water fraction (e.g. if from an empirical equation relating drained lake
volume). Furthermore, if the peak discharge was gauged, we then have to ask whether
baseflow was considered. Additionally, if the peak discharge was reconstructed or
estimated, we could not necessarily determine whether the Clague-Mathews (1973)
relationship, or one of its derivatives was used (e.g. Evans, 1986; Walder and Costa, 1996;
Ng and Björnsson, 2003). We compiled all available details on the drainage mechanism
and dam type for individual glacier floods (Fig. 1).
2.2 Societal impact data
Societal impact recorded in this study were primarily sourced from the academic literature,
but we sought supplementary data from publically available natural hazards databases,
specifically Dartmouth Flood Observatory (2015): Masterlist, Guha-Sapir et al. (2015): EM-
DAT, and UNISDR (2015): DI-Stat. Securing societal data from a variety of sources was
necessary to surmount the common problems with acquiring such information, which in
summary are as described above for the physical attribute data; i.e. that records are not
systematic, homogeneous, nor in compatible format (e.g. Petrucci, 2012; UNISDR, 2015;
Iribarren Anacona et al., 2015). These natural hazards databases yielded some extra
societal impact data and most crucially, these data were quantitative (such data is difficult to
obtain) Overall 24 % of the glacier floods we have identified also had a recorded societal
impact (Table 2).
In this study, the societal attributes recorded were number of deaths, number of injured
persons, number of evacuees/displaced, total affected area, livestock lost, farmland lost,
houses/farms destroyed, total persons affected, road damage, bridges damaged,
infrastructure damage and financial cost. We also recorded positive impacts wherever
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available; for example tens of glacier floods in Norway were noted to have contributed
additional water into hydropower reservoirs (Jackson and Ragulina, 2014). However, there
was no single event for which we were able to populate all of these societal attributes. With
specific regard to the publically available natural hazards databases, we found that many
countries were not represented at all and we speculate that some countries have not
released such data. This could be due to lack of monitoring, recording and communication
of information or to the political sensitivity of particular locations.
Additionally, there are ‘word-of-mouth’ reports of glacier floods which are difficult to
substantiate; for example Vivian (1979) was told that several thousand people were killed
when a huge flood was generated from ice fall into a proglacial lake in Tibet (see Tufnell,
1984). In general, we encountered problems in matching the societal records of glacier
flood impacts to the physical data because the date and place of an impact can be different
to the date and place of flood origin. This ‘mis-match’ meant that laborious manual cross-
checking was the only way to compare the two sets of records. Most commonly, if deaths,
injuries, evacuees/displaced persons were reported, they were not quantified. Similarly,
‘livestock lost’, ‘farmland lost’, ‘houses’/’farms destroyed’, and ‘road damaged’ were
mentioned quite frequently, for example in the Icelandic (e.g. Thorarinsson, 1939; 1958)
and central Asian (e.g. Hewitt, 1982; 1985) literature, but were often unquantified. Perhaps
a village name was given, but the size of this village was not, for example. In contrast
‘bridges destroyed’ and ‘infrastructure damage’ frequently named the bridge(s) or the
infrastructure, which included hydropower installations, irrigation canals, communal
buildings, and tourist facilities, and thus a rudimentary tally of impacts was more easily
compiled. Costs reported were often costs of remedial work, and sometimes whilst there
was mention of elaborate emergency measures implemented, such as helicopter
evacuations of people and emergency pumping of water for example, no costs associated
with this emergency action were given.
2.3 Derivation of societal impact of glacier outburst floods
Approaches to assessing glacier flood impacts usually disregard any socio-economic
factors (Messner and Meyer, 2006). Those few approaches that do exist to assess the
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direct impact of floods (and other natural hazard phenomena) can be more or less complex,
not least depending on data availability, but also on the scale and intentions of the study. In
this study, we were motivated to provide a quantitative comparison between glacier flood
events; i.e. of their relative direct impact, rather than an attempt to precisely define the
absolute impact of any individual event. Indeed the latter is probably not possible given the
problems with reporting of this data as noted in section 2.2 above. Therefore, we applied
the simplest (and most clearly documented) societal relative impact classification present in
the peer-reviewed literature, which can be employed at both local and regional scale, and
which was performed by establishing a priori three damage levels (c.f. Petrucci, 2012; Table
3).
The total impact per glacier flood was then converted to a total impact per country, IC, or per
major geographical region (regions as in Figure 1), IR as the sum of relative damage Di
caused, as based on the concept that relative damage is the product of relative value, Vi, of
a damaged element and the relative level of loss, Li, that it suffered (Varnes, 1984):
IR = ΣDi
where:
Di = Vi x Li
where Vi and Li values were derived using the criteria in Table 3 and as adapted from
Petrucci (2012). We added deaths to the quantification of impact most simply whereby one
death was given a value, Vi of one and an level, Li, of one. We gathered country area data
(CIA, 2016), national population data (ESA, 2016) and national Gross Domestic Product
(GDP) data (World Bank, 2016) in order to normalise Di by both a population density and by
a measure of economic wealth. Thus we provide a crude measure of national susceptibility
and national capability to respond, respectively (c.f. Barredo, 2009). We appreciate that,
within national boundaries, regional differences will perturb these capacities and we also
recognise that glacier floods are frequently transboundary, but we could not source
consistent data to enable greater granularity in our assessment.
2.4 Derivation of recurrence intervals
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We calculated a recurrence interval = (n + 1 \ m), where n is the number of years on record
and where m is the ordered rank of the event being considered. In this study we considered
ranks of volume, discharge and damage.
3. Results
3.1 Spatial distribution of glacier floods
Historical and modern glacier floods occur worldwide (Fig. 1). 70 % of glacier floods are
from ice dammed lakes, 9 % are from moraine-dammed lakes, 16 % are from an unknown
dam type/trigger, and 3 % are triggered by volcanic activity (Fig. 1). The amount of available
information on dam type, trigger mechanism, volume and discharge varies considerably by
major world region (Fig. 1). There are spatial differences in the apparent susceptibility of
society to the impacts of glacier floods, because the number of events with recorded
societal impact per country or per major world region does not correspond with the total
number of glacier floods. This discrepancy between the number of floods and the number of
floods with recorded impact is due to: (i) the fact that some glacier floods occur far away
from people, property and infrastructure (e.g. many glacier floods in British Columbia:
Canada, Alaska: USA, Iceland), (ii) some sites produce multiple floods and some yearly
floods (Fig. 2), (iii) inconsistent reporting between countries and major world regions
regarding event occurrence and physical attributes. We have partially addressed the latter
issue by focusing on societal impacts because records are more likely if there has been a
preceding flood and more likely to be more detailed if there was societal impact.
3.2 Temporal distribution of glacier floods
Glacier floods have occurred throughout recorded history (Fig. 3). It is useful to consider
here for the first time, both for each major region (Fig. 3A) and globally (Fig. 3B), the
number of glacier floods on timescales from centuries to days because: (i) it documents
some of the raw data for our further investigation of seasonality and recurrence intervals,
(iii) it helps hint at process mechanisms, and (iii) this will help future studies put glacier
floods in the context of other natural hazards. Interestingly, all major world regions (Fig. 3A)
and Figure 3B show an apparent decline in the trend of the number of glacier floods being
recorded from the mid-1990s onwards and this is discussed below. There is a
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predominance of glacier floods in summer months, and this temporal clustering is weaker in
the cases of Europe and South America, and more pronounced in the cases of Iceland and
central Asia (Fig. 4). Scandinavia is unusual for having a seasonally bimodal distribution,
with many floods recorded in the winter month of January (Fig. 4). We do not have a trigger
mechanisms recorded for > 90 % of our Scandinavia records, but we speculate that a
possible reason for a peak in glacier flood activity in January in Scandinavia is that is a time
is when freeze-thaw cycles are pronounced and resultant rockfalls could route into glacier
lakes.
For sites that have produced more than three floods, the days of the year on which a flood
from a given site has occurred are presented in Figure 5. Figure 5 shows that most northern
hemisphere sites are experiencing floods earlier in the year and that in South America,
whilst there are only a couple of sites with multiple floods recorded in both of these cases,
the day of the year on which a flood occurs is apparently becoming later. This pattern is
discussed below and may be partly explained by the apparent (though not statistically
significant) reduction in glacier floods from ice-dammed lakes (Fig. 6).
3.3 Glacier flood recurrence intervals
Recurrence intervals are presented for each major world region in Figure 7 and were
calculated with consideration of flood magnitude, as defined either by volume (Fig. 7A)
discharge (Fig. 7B) or a damage index (Fig. 7C). These estimates of recurrence intervals
are fits to past events and not predictions of future ones. The lack of error margins on these
graphs reflects our inability to define the magnitude of likely inaccuracies in volume or peak
discharge because the method of calculation for these attributes is often not reported. For
this reason it is the shape of these lines and the relative placing of the lines pertaining to
each major region that is most important rather than the absolute values. For a given
recurrence interval, north-west America experiences floods with the greatest volumes (Fig.
7A), but the least damage (Fig. 7C). In contrast, for a given recurrence interval the
European Alps experience low volume (Fig. 7A) and low discharge (Fig. 7B) glacier floods,
but moderate to high damage is caused (Fig. 7C). If a damage index of ten is considered,
which describes impact such as a highway bridge destroyed, or a large village destroyed, or
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ten persons killed (Table 3), then in broad terms South America has experienced this level
of impact on average every ten years, central Asia every twenty years, the European Alps
every forty years, Scandinavia every 50 years, Iceland every 60 years and north-west
America every 1000 years (Fig. 7C). South America is the most vulnerable region to glacier
floods causing societal impact of up to a damage index of ~30, and central Asia is the most
vulnerable region to glacier floods causing societal impact > ~30 (Fig. 7C).
3.4 Global impact of glacier floods
The global impact of glacier outburst floods can be crudely assessed using the number of
events recorded per country and per major world region (Fig. 8A). Using this measure,
north-west America (mainly Alaska), closely followed by the European Alps (mainly
Switzerland) and Iceland are the most susceptible regions to glacier floods (Fig. 8A).
However, since many floods occur repeatedly from the same location, an assessment of the
global impact should also consider the number of sites recorded to be affected by glacier
floods, per country and per major world region (Fig. 8B). Given these conditions the
European Alps is the most susceptible region, and Switzerland is the most susceptible
country (Fig. 8B). Canada, Chile, Tibet and Iceland are other countries that all have ~ 30
sites producing glacier floods (Fig. 8B).
The only societal impact attribute with standardised quantitative reporting was number of
deaths. We could not find records of deaths due to glacier floods from Greenland,
Scandinavia and north-west America. From the records that we were able to access, glacier
floods have directly caused at least 7 deaths in Iceland, 393 deaths in the European Alps,
5745 in South America and 6300 in central Asia. However, 88 % of these 12,445 recorded
deaths are attributable to just two events: the 1941 Huaraz, Peru (Carey, 2005) and the
2013 Kedarnath, India (Allen et al., 2015) disasters. The same two events account for 82 %
of the total damage caused globally by glacier floods because of the contribution to the
damage index of these exceptionally high numbers of reported deaths (Fig. 8C). Iceland
and Canada are notable for having relatively high number of events, relatively high number
of sites, yet low levels of damage, whereas Peru, Nepal and India have relatively few
events yet very high damage (Fig. 8).
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The totals by country of all other societal impact-related damage, excluding the
exceptionally high numbers of deaths associated with Huaraz in Peru and Kedarnath in
India, reveal that Nepal and Switzerland have the most recorded damage due to glacier
floods with 22 % and 17 % of the global total, respectively (Fig. 8C). If the major world
regions are ranked by damage due to glacier floods, central Asia is the most affected,
followed by South America, then the European Alps, Iceland, Scandinavia, north-west
America and Greenland (Fig. 8C).
Societal impacts of glacier floods are relatively rarely recorded for floods in Scandinavia
and north-west America (Fig. 9A). These are both geographical regions that might be
expected to have some of the most detailed records due to their economic development
and likely monitoring capability and so this lack of impact is not likely to be an artefact of
reporting bias. Where impacts were recorded in Scandinavia and in north-west America,
then they only constituted loss of farmland productivity (50 % of events in Scandinavia), and
loss of bridges, trails, tracks and other tourist-related infrastructure (< 5 % of events in
north-west America) (Fig. 9A). In contrast, < 10 % of all events in the European Alps and in
central Asia and < 15 % of all events in South America have produced impacts across the
spectrum of impact types (Fig. 9A).
If damage types are calculated as a proportion of the number of sites (Fig. 9B), in
comparison to the number of flood events: (i) the global severity of glacier floods apparently
increases, and (ii) the type of impacts recorded are more diverse, in comparison to
calculations made as a proportion of all events (Fig. 9A). For example, one in five sites in
the European Alps has produced floods that have damaged farmland, destroyed homes,
and damaged bridges; 10 % of sites in South America have produced glacier floods that
have killed people and damaged infrastructure; 15 % of sites in central Asia have produced
glacier floods that have inundated farmland, destroyed homes, damaged roads and
damaged infrastructure (Fig. 9B).
Mapping the relative damage index reveals that susceptibility to glacier outburst floods has
a global coverage and that the highest levels of relative impact occur in all major world
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regions except north-west America (Fig. 10a). Normalising Di by population density
homogenises the global distribution, and actually in comparison to the raw Di values (Fig.
10a) emphasises Alaska, Peru and Iceland and diminishes the prominence of central Asian
countries (Fig. 10b). This normalisation by population density is a crude measure of
vulnerability (c.f. Alcántara-Ayala, 2002). Italy and Norway, France, Pakistan and Iceland all
have a very similar relative damage index (~ 200), but are more (Iceland) or less (Pakistan)
vulnerable because of very high or low population density, respectively. Normalising Di by
country GDP (Fig. 10c) is a crude measure of the ability of a country to mitigate, manage
and recover from the impacts of glacier floods. Using this measure Iceland, Bhutan and
Nepal are the countries with the greatest economic consequences of glacier flood impacts
(Fig. 10c).
4. Discussion
4.1 Data recording
Investigating, compiling and analysing the data in this study has revealed disparate
detection and monitoring of glacier floods and non-standardised data reporting via scientific,
public and governmental sources. These concerns are not unique to glacier floods, but
potentially retard hazard mitigation and emergency preparation (Lindell and Prater, 2003).
Accurate, full and standardised data on glacier floods is needed by regional governments
and agencies to determine if external assistance is necessary and, if so, how much and in
what form(s). National governments and natural hazards authorities need to estimate
glacier flood damage to report to taxpayers and to identify communities - often relatively
isolated communities - that have been (or might be) disproportionately affected. Planners
need to develop damage predictions to assess the effects of alternative hazard
adjustments, to quantify expected losses and to understand the extent to which those
losses could be reduced, all in combination to implement cost-effective mitigation
strategies: for example, to protect hydropower installations on rivers fed from glaciated
regions and to safeguard valuable agricultural land. Road and rail transport requires rivers
to be bridged, which are then put at risk from glacier outburst floods; in locations where
there are repeated floods, there is a need to protect such communication routes (e.g.
Mason, 1929; Stone, 1963; Bachmann, 1979; Tufnell, 1984). Insurers need data on the
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maximum damage and the most likely damage. These issues of data acquisition and
sharing are nowhere more important than for less economically-developed countries where:
(i) most deaths from natural disasters occur (Alcántara-Ayala, 2002; Kahn, 2005), (ii) where
primary industries such as agriculture and fishing can represent a substantial part of a
nation’s economy; for example some glacier floods in west Greenland discharge so much
sediment into the fjords and off the coastline that fishing, which is a mainstay of the local
and national economy, is severely disrupted (Adam Lyberth, pers. comm.), and (iii) where
hydropower dominates a nations’ GDP and socio-economic development potential, such as
for Bhutan (Tshering and Tamang, 2016). However, the monitoring of events has resource
implications and in locations where such resources are scarce, other priorities frequently
and unsurprisingly take precedence.
Whilst several natural hazards databases (e.g. Dartmouth Flood Observatory, 2015:
Masterlist, Guha-Sapir et al. 2015: EM-DAT, and UNISDR, 2015: DI-Stat) purport long-term
records, they are in reality biased towards more recent events. For example, the EM-DAT
database (Guha-Sapir et al., 2015) has the first ‘hydrological flash flood’ event in Austria
occurring in 1952, and the first for Iceland in 1974. Yet the scientific literature confirms that
there have only been a few glacier floods in Austria since 1947 and many tens of floods in
Iceland before 1974. For Nepal, Whiteman (2011, page XXX) comments that “historical
records indicate that even during the four decades up to 1970 several GLOFs occurred in
Nepal, although a GLOF in 1977 in the Khumbu Himal seems to have been the first to have
received significant scientific study (Kattelmann, 2003)”. Furthermore, natural hazards
databases can apparently report an ‘aggregate’ or ‘composite’ impact, for example there
are circumstances in which heavy rain triggers flash flooding over a catchment area, but
only part of the resulting flood is due to a glacier flood. This is suggested by some of the
records in the EM-DAT database (Guha-Sapir et al., 2015) in which an individual entry can
span several weeks. Toya and Skidmore (2007) mentioned that developing countries have
an incentive to exaggerate damage to receive higher amounts of international assistance
and therefore data may not be entirely reliable. However, as a generalisation less
economically developed countries are perhaps less likely to have agencies responsible for
gathering damage data due to different priorities, resource constraints and political settings,
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for example, as suggested earlier. In short, despite the comprehensive efforts we have
made to gather available records of glacier floods in this study, if a flood was not recorded it
does not mean there was no flood, and if no impact was recorded for a flood it does not
mean that there was no impact. Our global assessment, country totals and damage index
are therefore minima.
Furthermore, even when physical attributes are reported, they are far more ambiguous than
may be immediately realised. Continuously-recording river stage gauges are not common
(although a few countries such as Iceland and Norway have relatively good coverage due
to their national monitoring programmes) and are often located many tens of kilometres
down valley from a glacier. Furthermore, gauging sites are often destroyed by larger
discharges (Haeberli et al., 1989) so records are likely to be biased towards events with
lower flow. We suspect that the Clague-Mathews (1973) relationship between drained lake
volume and peak discharge has been used to determine many of the reported ‘discharge’
values. Whether a reported discharge was measured at a gauge, or reconstructed using the
Clague-Mathews (1973) relationship, it cannot be an accurate reflection of the peak
discharge of water released from the glacier because it ignores the evolution of a dam-
break type flood hydrograph with time/distance down valley (e.g. Russell et al., 2010;
Carrivick et al., 2013). From the records of glacier floods that we analysed, it was often
unclear whether the ‘discharge’ of a reported glacier flood included consideration of
baseflow or of water already in the glacier hydrological system, since both introduce
difficulty when constraining the water balance of a glacier flood (e.g. Huss et al., 2007).
Very simply, we draw attention to the fact that uncertainty is almost always unreported in
both the volume and the discharge estimated for an individual glacier flood.
Mindful of these uncertainties in glacier flood attributes, it perhaps seems prudent to
consider using empirical hydrograph reconstructions (Herget et al., 2015) and stochastic
simulations of inundation (Watson et al., 2015). These approaches contrast with the
detailed knowledge needed for mechanistic modelling that preferably relies on lake level
changes or else an input hydrograph, plus down-valley observations of hydraulics, plus a
high- resolution digital elevation model, plus expertise to run the model (e.g. Carrivick et al.,
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2009, 2010). Morphodynamic models of glacier floods, which could be more accurate than
hydrodynamic-only models where there is widespread and intense sediment transport (e.g.
Staines and Carrivick, 2015; Guan et al., 2015), are even more computationally demanding.
Perhaps most importantly for quantifying socio-economic damage, there are emerging
modelling techniques to consider impacts on the scale of individual buildings (e.g. Jenkins
et al., 2015).
4.2 Global impact of glacier floods
The number of sites recorded and reported to have produced glacier outburst floods is very
small in comparison to the number of glaciers and the numbers of glacier lakes, whether on
a global, regional or country scale. For example, Wang et al. (2013) identified 1667 glacier-
fed lakes > 0.1 km2 in the Tian Shan and 60 of these as potentially dangerous at present,
yet our study only found nine sites that have ever been recorded to have produced glacier
floods in this area. As a proportion of the number of (individual mountain or outlet) glaciers
in each major world region (Pfeffer et al., 2014), just 5.6 % in Iceland have been recorded
to produce glacier floods, and this figure falls to 2.2 % for the European Alps, 0.8 % for
Scandinavia, 0.3 % for South America and for Canada and US (0.04 % for Alaska) and 0.2
% for central Asia. Globally, the percentage of glaciers that have been recorded to produce
glacier floods is 0.17 %. We consider all these percentages to be minima due to the issues
of detecting and publically recording glacier flood data, as outlined above.
An apparent decline in the number of glacier floods recorded from the mid-1990s onwards
(Fig. 3) is unlikely to be due to issues of detection, given that it is a global pattern and given
that improvements in earth observation and monitoring have gained spatio-temporal
coverage. The apparent decline in floods is conspicuous given the continued increase in
number and size of glacier lakes worldwide (Carrivick and Tweed, 2013). The apparent
decline in reported glacier floods could speculatively be ascribed to: (i) successful efforts to
stabilise glacier lake moraine dams (e.g. Grabs and Hanisch, 1992) but the number of
corresponding engineering projects is very small compared to the number of GLOFs
reported, (ii) the fact that successive floods can ‘armour’ flood channels (Ferrer-Boix and
Hassan, 2015) and improve conveyance-capacity at the reach scale (Guan et al., 2016)
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thus enabling a river channel to more efficiently accommodate subsequent similar, (iii) local
populations becoming more aware and more resilient (c.f. Carey, 2005), (iv) that over the
last 50 years ice-dammed lakes seem to be generating floods less often whereas there is
no such trend for moraine-dammed lakes (Fig. 6), nor is there such a trend in the
occurrence of glacier floods from englacial water pockets or from volcanic activity (not
graphed).
It has been previously documented that some sites are experiencing floods earlier in the
year (Fig. 5). Thorarinsson (1939), for example, noted that Vatnsdalslón in Iceland drained
gradually earlier in the summer season between 1898 and 1938. Other well-documented
examples include Lake Merzbacher in Kyrgyzstan (Ng and Liu, 2009) and Gornersee in
Switzerland (Huss et al., 2007). Diminishing flood magnitude with successive events is also
typical of the late stage of a ‘jökulhlaup cycle’ in settings that have ice dams (Mathews and
Clague, 1993). In these circumstances, ice margin retreat and/or thinning over time reduces
the depth of the lake that can be impounded and consequently the amounts of water that
can be released on drainage (Evans and Clague, 1994). However, Huss et al. (2007) noted
that there was no pattern of peak discharge variation with progression through a jökulhlaup
cycle at Gornersee. In general, Tufnell (1984) suggested that three types of periodicity
could be identified, namely: (i) annually or sub-annually and associated with retreating
glaciers and ice-dammed lakes, e.g. Gornersee, (ii) irregularly, as associated with barrier
lakes from glacier advances such as Allalin, Vernagt and Rutor glaciers in Switzerland, and
with volcanogenic glacier floods, and (iii) isolated phenomena such as Tete Rousse,
Switzerland in 1892. It must be noted however that the periodicity of floods at a site can
change: Stone (1963) identified four stages of different periodicity in Alaskan ice-dammed
lakes.
Cycles of floods from the same site, and flood periodicity, are dependent on trigger and
drainage mechanisms and in the context of societal impacts are important because to some
degree they can be dependent on climate and hence may become predictable (e.g.
Kingslake and Ng, 2013). Most obviously the key relationship is that between lake water
depth and the thickness of damming ice, as well as with hydrologic connections within the
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glacier (Clague and Evans, 1997; Tweed and Russell, 1999; Roberts et al., 2005; Walder et
al., 2006; Carrivick and Tweed, 2013; Tweed and Carrivick, 2015). In contrast, floods from
Aniakchak in Alaska (Waythomas et al., 1996) are produced by geothermal and volcanic
activity producing meltwater and so are independent of climate. In contrast, floods from
Grímsvötn in Iceland decreased in volume but increased in frequency from 1934 to the mid-
1970s (Preusser, 1976) because as ice thickness reduced, the threshold for ice-dam
flotation diminished: thus even glaciers floods that might be assumed to be independent of
climate can be controlled by glacier fluctuations and hence indirectly by climate.
The relative damage index is extremely heterogeneous whether considered on a global,
world region or country scale or per event (Fig. 8). The occurrence with which types of
impact are recorded is also very heterogeneous (Fig. 9). These two observations together
with comparison of the recurrence interval curves by volume, discharge and by damage
index together highlight that there is no relationship between the size (volume or peak
discharge) of a glacier flood and the societal impact of that flood, as measured by a relative
damage index (Fig. 7). Simply, recorded damage is not a function of the physical attributes
of the flood. This lack of a relationship between flood size and flood impact is perhaps not
surprising because elements of risk are not uniformly distributed in space, but additionally
may be because the same material impact (e.g. footbridge or road washed away) can have
fundamentally different consequences, i.e. secondary or indirect losses, that depend on
social, political, cultural and economic contexts.
Damage also varies with multiple floods from the same site (Fig. 2) as physical and societal
adaptation or resilience develops. In terms of adaptation of the physical environment, two
floods of similar size (volume or peak discharge) can have different impacts depending on
sediment concentration and thus flow rheology, since the time since the last event
conditions sediment availability due to geomorphological responses such as collapse of
undercut banks infilling the channel, subsequent lower-magnitude flows infilling the channel
with sediment, a channel becoming wider and straighter due to erosion by the first event
and thus of improved conveyance capacity (e.g. Staines et al., 2014a, 2014b, Guan et al.,
2015). Thus glacier floods can behave as a Newtonian fluid, or be of debris flow type ( e.g.
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Huggel et al., 2003; Breien et al., 2008) or exhibit transitional flow regimes (e.g. Carrivick,
2010; Carrivick et al., 2009, 2010, 2011). The Jancarurish, Peru 1950 flood released 2 M m3
of water and transported 3 M m3 sediment and the Tête Rousse 1982 flood generated 0.2
M m3 water and 0.8 M m3 sediment (Liboutry, 1971; Vivian, 1974; Bachmann, 1979; Tufnell,
1984). Unfortunately the sediment-water ratio is rarely measured in glacier floods.
In terms of human adaptation, activity such as progressive development of infrastructure
and livelihoods on a floodplain, or conversely relocation to higher ground or even
permanent removal of people, property or infrastructure from risk, will change societal
impact for a second flood of the same physical characteristics. The nature of these human
activities also has a spatio-temporal evolution. Engineered flood defences in distal locations
including walls and bunds to protect villages were common in European Alps even in the
18th Century (e.g. Venetz, 1823) but are only recently being constructed in the central
Himalaya (Ives et al., 2010). The walls and bunds in Europe are now to a degree
superseded by reservoir dams, sluice gates and check weirs in more proximal locations
(Kantoush and Sumi, 2010)
5. Conclusions
This study has highlighted considerable spatio-temporal heterogeneity in the style of
monitoring and reporting of glacier floods and of their associated societal impacts.
Standardised reporting and sharing of data globally has been started most prominently by
GRIDBASE (2016) and GAPHAZ (2016) and this study is a progression to a global analysis
and data sharing, but there is still a problem that some countries do not have the economic
or infrastructural capacity to achieve the necessary monitoring nor to prioritise it against
other issues. This problem leads us to make key recommendations that there needs to be
accurate, full and standardised monitoring and recording of glacier floods, in particular to
preferably discriminate flood volume and peak discharge at source rather than at some
distance down valley. Otherwise the physical mechanisms responsible for generation of the
flood are masked by the effects of channel topography on flood evolution with distance
down valley.
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With the available data analysed, our key over-arching findings are that:
•Of 1348 recorded glacier floods, 24 % also had a societal impact recorded.
•Of recorded floods from 332 sites, 36 % had recorded societal impact.
•Recorded glacier floods have predominantly occurred from ice-dammed lakes (70 %
of all recorded floods).
•The number of recorded glacier floods per time period has apparently reduced since
the mid-1990s in all major world regions, but the reasons for this apparent trend are
unclear.
•Two thirds of sites that have produced > 5 glacier floods (n = 32) are doing so
progressively earlier in the year, which hints at a global climatic control. However,
there was no relationship found between timing and peak discharge of glacier floods
•We have found records of ice-dammed lakes at 78 sites that have produced three or
more glacier floods, some annually, including Tulsequah Lake in Canada at > 100
floods and 23 other sites with ten or more floods each.
•North-west America experiences floods with the greatest volumes but with the least
damage. In contrast, the European Alps experience low volume and low peak
discharge glacier floods, but moderate to high damage.
•South America is the most vulnerable world region to glacier floods causing high
levels of societal impact (of up a damage index of ~30), and central Asia is the most
vulnerable region to glacier floods causing extreme levels of societal impact
(damage index > ~30).
•Glacier floods have directly caused at least 7 deaths in Iceland, at least 393 deaths
in the European Alps, at least 5745 in South America and at least 6300 in central
Asia. However, 88 % of these 12,445 recorded deaths are attributable to just two
events: the 1941 Huaraz, Peru (Carey, 2005) and the 2013 Kedarnath, India (Allen et
al., 2015) disasters. Thus a single event with a large impact can change the spatio-
temporal pattern considerably.
•Iceland and Canada are notable for having relatively high number of glacier floods
and relatively high number of sites, yet low levels of damage; whereas Peru, Nepal
and India have relatively few events, yet high levels of damage.
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•One in five sites in the European Alps has produced floods that have damaged
farmland, destroyed homes, and damaged bridges; 10 % of sites in South America
have produced glacier floods that have killed people and damaged infrastructure; 15
% of sites in central Asia have produced glacier floods that have inundated farmland,
destroyed homes, damaged roads and damaged infrastructure.
•Bhutan and Nepal are the countries with the greatest economic consequences of
glacier flood impacts.
In future work, it is the intention to add to the records of glacier floods compiled and
analysed in this study (Supplementary Information) because i) we invite correspondence
from anyone with more data to fill any gaps, and ii) more glacier floods will occur in the
future. Other studies may wish to include lake area and shape, since the hypsometry of a
glacier lake is partly determined by the dam type (e.g. Cook and Quincey, 2015) and has an
effect on the rate of water efflux. More sophisticated statistical analyses on the spatial and
temporal attributes could be considered, such as by employing non-stationary time-series
methods and by normalising impact by spatial density of socio-economic attributes such as
building density, respectively. Comparison of our data to other records; of climate, of glacier
changes, of socio-economic development, for example could be instructive. Secondary or
indirect impacts such damage or disruption to utility services and local businesses, loss of
revenue or increase in costs and emergency assistance and recovery expenses are very
rarely mentioned in the scientific literature in connection with glacier floods. Neither is there
ever any mention of intangible losses, which might include psychological impairments
caused by both primary and secondary losses that people experience due to a flood. To our
knowledge there has never been an assessment of societal impact in terms of response to
a glacier flood, i.e. comparing a socio-economic situation immediately before and in the
weeks and months after a flood (e.g. ECLAC, 2003).
Overall, combining glacier flood data with societal impact data recognises the interactions
of a non-linear physical system with a human system, both of which can behave in a linear
or non-linear manner and with threshold responses. Therefore if future studies attempt
modelling of the global impact of glacier floods, be it of geomorphology or of populations or
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infrastructure, then the response of the Earth’s surface to climate change and to land-use
change must be combined with probability distributions of possible geomorphological
responses (e.g. Alcántara-Ayala, 2002) and of human activity to statistically characterize
risk (Pelletier et al., 2015).
Supplementary Information
Table of lake name, glacier name, date, lat/long, and indication if societal impact record.
Acknowledgements
We are indebted to Victor Baker, Pavel Borodavko, Paul Carling, John Clague, Neil Glasser,
Jürgen Herget, Per Holmlund, Christian Huggel, Matthias Huss, Miriam Jackson, Andreas
Kääb, Oliver Korup, Felix Ng, Matthew Roberts and Vít Vilímek who all responded very
helpfully to our requests for data. Veðurstofa Íslands (the Icelandic Meteorological Office)
kindly supplied some data on Iceland’s glacier floods.
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A global assessment of the societal impacts of glacier outburst floods
Jonathan L. Carrivick and Fiona S. Tweed
List of Tables
Major
region Countries Key publications for physical attributes
Key source of
societal impact
data
Acknowledge
ment of
personal
assistance
Scandinavia Norway
Kjøllmoen and Engeset. 2003; Kjøllmoen, et al., 2009;
Liestøl, 1956; Knudsen and Theakstone, 1988; Tvede,
1989; Jackson and Ragulina, 2014
Jackson and
Ragulina, 2014 Miriam Jackson
Sweden Klingbjer, P., 2004 Per Holmlund
Iceland Iceland
Hákonarson, 1860; Askelsson, 1936; Thorarinsson, 1939,
1958, 1974; Rist, 1973, 1976, 1984; Preusser, 1976; Ives,
1991; Sigurðsson et al., 1992; Sigurðsson and Einarsson,
2005; Björnsson, 1976, 1988, 2003; Björnsson et al., 2000,
2001, 2003; Roberts, 2002; Roberts et al., 2001, 2003;
Rushmer, 2006.
Veðurstofa Íslands,
2016
Matthew
Roberts
North-west
America
Canada
Jackson, 1979; Mathews and Clague, 1993; Rickman and
Rosenkrans, 1997; Clague and Evans, 2000; Geertsema
and Clague, 2005; John Clague
Alaska,
USA Stone, 1963; Post and Mayo, 1971; Mayo, 1989; Capps et
al., 2010; Wolfe et al. 2014; Wilcox et al., 2014
Stone, 1963; Post
and Mayo, 1971
Other USA Dreidger and Fountain, 1989; O’Connor and Costa, 1983
South
America
Peru
Chile
Argentina
Lliboutry, L., 1956; Harrison and Winchester, 2000;
Harrison et al., 2006; Dussaillant et al., 2010; Emmer and
Vilímek, 2013; Vilímek et al., 2014; Iribarren Anacona et al.
2015
Carey, 2005; Peru
and Chile and
Argentina in
UNISDR (2015): DI-
Stat; Guha-Sapir et
al. (2015): EM-DAT
Vít Vilímek,
Christian
Huggel
Central Asia Tibet
Bhutan
Mason, 1929; Hewitt, 1982, 1985; Feng, 1991; Xiangsong,
1992; Yamada and Sharma, 1993; Watanbe and
Richardson and
Reynolds, 2000;
Jürgen Herget
Feliz Ng
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Nepal
India
Pakistan
Kyrgyzstan
Kazakhstan
Tajikistan
Rothacher, 1996; Richardson and Reynolds, 2000; Mool et
al. 2001; Ghimire, 2004; Campbell et al., 2005; Ng et al.,
2007; Ng and Liu, 2009; Chen et al. 2010; Glazarin, 2010;
Hewitt and Liu, 2010; Ives et al., 2010; Narama et al.,
2010; Shresta et al., 2010; Komori et al., 2012; Liu et al.,
2014
Iturrizaga, 2005;
Komori et al., 2012;
Nepal and Uttar
Pradesh (India) both
in UNISDR (2015):
DI-Stat reports;
Guha-Sapir et al.
(2015): EM-DAT
European
Alps
France
Austria
Switzerland
Italy
Hoinkes, 1969; Bachmann, 1979; Haeberli, 1983;
Raymond et al., 2003; Richard and Gay, 2003 (and
GRIDBASE); GAPHAZ; Huss et al., 2007; Flubacher,
2007; Vincent et al., 2010; Kämpfer, 2012
Richard and Gay,
2003 and
GRIDBASE,
GAPHAZ
Christian
Huggel,
Andreas Kaab
Table 1. Key data sources used for the compilation of physical and societal impact
attributes of glacier outburst floods. Other major sources that were not region-specific
included Evans (1986) and Walder and Costa (1996).
A global assessment of the societal impacts of glacier outburst floods
Jonathan L. Carrivick and Fiona S. Tweed
Scandinavi
a
European
Alps
South
America
central
Asia
north-
west
America
Iceland Greenlan
dGlobal
Total records 118 301 86 216 335 270 22 1348
Events with recorded
impact (%) 74 39 7 25 10 7 5 24
Total single locations 20 88 49 79 57 32 7 332
Events at single
locations with
recorded impact (%) 65 45 27 39 14 38 14 36
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Table 2. Summary of the total number of records of glacier outburst floods compiled in this
study and the number of those events with recorded societal impact.
A global assessment of the societal impacts of glacier outburst floods
Jonathan L. Carrivick and Fiona S. Tweed
Sub-type Vi Li
bridge
tunnel
road
Level 1
(1)
Level 2
(0.5)
Level 3
(0.25)
Road network
Highway 10 10 8
Prolonged road
traffic interruption
Temporary road
traffic interruption
Limited road
traffic disruption
but some road
damage
State road 8 8 6
County road 6 6 4
Municipal road 5 5 3
Track 1
Railway
network
State railway 10 10 8 Prolonged rail
traffic interruption
Temporary rail
traffic interruption
Limited rail traffic
disruption but
some rail damage
Regional route 8 8 6
Service track 5 5 3
Residential
buildings
Isolated house 6
Building collapse Building evacuation
No evacuation
but some adverse
effects
Small village 8
Large village 10
Public
buildings
e.g. airport, train or
bus station, religious
building, town hall,
school,
10 Building collapse Building evacuation
No evacuation
but some adverse
effects
Service
networks
e.g. irrigation or
drainage canals,
electricity lines,
telephone lines,
5
Prolonged service
interruption across
large areas
Temporary service
interruption across
large areas
Limited service
disruption but
some damage in
small areas
Productive
activities
Agriculture and
farming 4Interruption of
production, or loss
of production
system
Interruption of
production and loss
of products
Limited loss of
products
Commerce/business 5
Fishing 4
Other industry 8
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manuscript submitted to Global and Planetary Change
Other
infrastructure:
hydraulic
works
Check dam or weir
or sluice 4
collapse Loss of efficiency
No loss of
efficiency but
some adverse
effects
Earth embankment 5
Retaining wall 6
Dam 10
Tourist
facilities and
sports resorts
Hotel or resort
complex 10 Interruption of
activity and loss of
facility
Temporary
interruption of
activity
No interruption of
activity but some
adverse effects
campground 4
Car park 4
Human
fatality
Death of individual
reported 1 1 - -
Table 3. Types and sub-types of damaged elements. For each type and sub-type, the value
considered for damage assessment is Vi. The Level, Li are multiplying factors for assessing
total glacier flood impact per event and per country, I, and are 1, 0.5 and 0.25 for levels 1, 2
and 3, respectively. Adapted from Petrucci (2012), Petrucci and Gullà (2009, 2010).
A global assessment of the societal impacts of glacier outburst floods
Jonathan L. Carrivick and Fiona S. Tweed
List of Figures
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Figure 1. Overview by major region of the proportion of the glacier outburst flood records
compiled in this study that include physical attributes; namely volume, V, discharge, Q, flood
water release and/or routing mechanisms, and dam type. Note that ‘ice’ includes subglacial,
ice-marginal and supraglacial situations, and that ‘volc. eruption’ includes (i) instantaneous
outburst of meltwater derived from ice melt due to volcanic activity, (ii) release of water that
was temporarily stored having been generated by ice melt due to volcanic activity , (iii)
geothermal activity. Numbers on pie charts are the number of floods per dam type/trigger.
A global assessment of the societal impacts of glacier outburst floods
Jonathan L. Carrivick and Fiona S. Tweed
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Figure 2. Glacier outburst floods
that have originated from the same
source three times or more. Note
that ‘?’ refers to missing
information usually because there
was no visible/named lake (e.g. if
subglacial or englacial ‘water
pocket’). White parts of bars
denote documented but
unconfirmed sources of floods.
manuscript submitted to Global and Planetary Change
A global assessment of the societal impacts of glacier outburst floods
Jonathan L. Carrivick and Fiona S. Tweed
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manuscript submitted to Global and Planetary Change
Figure 3. Number of glacier outburst floods per 25 years by major region (A) and as a
global cumulative total (B). Note that for clarity the x-axis is limited to displaying records
from the last 500 years.
A global assessment of the societal impacts of glacier outburst floods
Jonathan L. Carrivick and Fiona S. Tweed
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manuscript submitted to Global and Planetary Change
Figure 4. Percentage of glacier outburst floods occurring per month by major region. Note
‘n’ is number of records for which month is known and % in brackets is proportion of all
records of glacier floods in that major world region.
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manuscript submitted to Global and Planetary Change
Figure 5. Comparison by major region of the day of year on which glacier lakes have
drained, for glacier lakes for which the day of the year is known. Black lines are linear
regression best fits. Note that we only have record of three glacier outburst floods from
Nevado del Plomo but is included here because there are few multiple glacier lake
drainages recorded in South America. Note only lakes that have drained more than 5 times
are depicted for clarity.
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manuscript submitted to Global and Planetary Change
Figure 6. Number of recorded glacier outburst floods per year, discriminated by dam type.
The excessively high number of events in 2013 in Scandinavia, in 1996 in North America
and in 2003 in Iceland were events in the Lyngen Alps (Jackson and Ragulina, 2014), at
Brady Glacier (Capps and Clague, 2014) and at multiple lakes around Vatnajökull
(Veðurstofa Íslands, 2016), respectively. Glacier floods from volcanism, ice-dammed lake –
volcano interactions, bedrock-dams and from englacial water pockets are not shown for
brevity and clarity.
A global assessment of the societal impacts of glacier outburst floods
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manuscript submitted to Global and Planetary Change
Jonathan L. Carrivick and Fiona S. Tweed
Figure 7. Global glacier outburst flood recurrence intervals calculated by magnitude as
defined by volume (A), discharge (B) and an index of damage (C). Note both x and y scales
are logarithmic. Note the lack of error margins because we cannot define the magnitude of
likely inaccuracies in volume or peak discharge, nor the effect of likely unreported impact.
For this reason it is the shape of these lines and the relative placing of the lines pertaining
to each major region that is most important rather than the absolute values. These
estimates of recurrence intervals are fits to past events and not predictions of future ones.
A global assessment of the societal impacts of glacier outburst floods
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manuscript submitted to Global and Planetary Change
Jonathan L. Carrivick and Fiona S. Tweed
Figure 8. Total number of recorded glacier floods (A), sites with recorded glacier floods (B),
and damage index (C) per country and per major world region. The absolute value of the
damage index is somewhat arbitrary, but permits comparison between countries and
between regions.
A global assessment of the societal impacts of glacier outburst floods
Jonathan L. Carrivick and Fiona S. Tweed
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manuscript submitted to Global and Planetary Change
Figure 9. Proportion of all glacier outburst floods (A) and proportion of all glacier outburst
flood sites (B) that have some attributes of societal impact recorded. Note different y-scale
for Scandinavia.
A global assessment of the societal impacts of glacier outburst floods
Jonathan L. Carrivick and Fiona S. Tweed
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manuscript submitted to Global and Planetary Change
Figure 10. Global societal impact of glacier outburst floods as defined by a relative damage
index (A), and this index normalised by population density (B) and by country GDP (C).
White circles denote country value without exceptionally high numbers of deaths included.
Note that it is the spatial pattern rather than the absolute values that are of interest.
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