Download 3. Causes Of Beach Erosion

Beach modelling I: Beach
erosion occurrence and causes
Adonis F. Velegrakis
Dept Marine Sciences
University of the Aegean
Synopsis
1 Significance of beaches to other ecosystems and economic
activity
2 Coastal erosion
3 Causes of beach erosion
4 Climate change: a short review
4.1 Trends
4.2 The mechanism
4.3 The future
4.4 What scenario
5. Erosion costs and adaptation
1 Significance of beaches to other ecosystems
and economic activity
Beaches, i.e. the low lying coasts built on unconsolidated sediments, are
valuable ecosystems by themselves; they also, front/protect various
other important back-barrier environments/ecosystems
Beaches protect very important coastal economic assets/infrastructure
and activities from marine inundation
Beaches are very important assets by themselves, being the focus of
the very large and lucrative ‘sun and beach’ tourist industry; islands,
in particular, depend on their beaches for most of their income.
Beaches are considered as particularly vulnerable to climate change,
likely to bear the brunt of the adverse impacts of climate change,
particularly through coastal retreat/erosion
2 Beach erosion
Coastal (beach) erosion, i.e. the retreat of the coastline (which may or may
not be accompanied by reduction in the beach sediment volume), is a
global phenomenon
It can be differentiated into:
•
Long term erosion, i.e. non-reversible coastline retreat, occurring in
long (in engineering terms) temporal scales and
•
Short term erosion, i.e. reversible on non-reversible retreat, occurring
in short (in engineering terms) temporal scales
Both can be devastating
3. Causes of beach erosion
Major causes of beach erosion include:
•
•
•
•
Climatic changes (e.g. sea level rise (ASLR), changes (reduction) in
precipitation and, thus, in river sediment discharges, changes in the
frequency/intensity and destructiveness of storms/storm surges
Reduction in coastal sediment supply-negative sediment budgets due to
e.g. river management schemes, destruction of coastal seagrass prairies
that provide marine biogenic sediments to beaches and badly designed
coastal works
Isostatic and tectonic movements
Natural or human –induced subsidence of coastal deltaic/estuarine
sediments on which most of the large coastal cities are built (Erikson et
al., 2005)
Climate change impacts on beaches
One the most potent drivers of beach erosion are the climatic changes, i.e.
•
•
•
•
the sea level rise
changes (reduction) in precipitation and, thus, in river sediment
discharges
changes in the frequency/intensity/destructiveness of storms/storm
surges
increases in coastal water temperatures that may negatively affect
natural beach defences e.g. coral reefs and seagrasses
Note: Beach response to climatic changes is a non-linear process; it (mainly)
depends on the magnitude/rate of sea level rise, beach slope and
morphology, the impinging (and generated-infragravity) wave energy
and the intensity, duration and frequency of storm surges and the
nature of coastal sediments
Our knowledge on these processes is still incomplete and, thus, predictions
are characterised by a large uncertainty
4. Climate change: a short review
4.1 Trends
Climate Change (CC): defined as the change of climatic conditions relative to a
reference period, i.e.:
• Period with first accurate records (1850s-1860s) or
• Average climate of periods with accurate climatic information and associated
with infrastructure used today (e.g. 1961-1990 1980-1999)
• Temperature, sea level and precipitation trends
• Polar Ice loss
• Extreme climate events
• There are also feedbacks/tipping points. Trends can be changed by
reinforcing (or negative) feedbacks and if thresholds are crossed changes
will not be linear and potentially reversible, but abrupt, large and (potentially)
irreversible in human temporal scales (Lenton et al., 2009).
4.2 Mechanism: what are the processes involved?
• Climate is controlled by solar heat inflows/outflows
• A major cause of the observed increase in the planet’s heat
content is the increasing atmospheric concentrations of
greenhouse gases (GHGs) that absorb heat reflected back from
the Earth’s surface
• Variability is both natural and human- induced
4.3 The Future
Predictions of future changes are characterised by uncertainty and, thus, there
is a large range of predictions,
Predictions depend on:
• Simulations based on complex coupled atmospheric-oceanographic models
• Different scenarios regarding drivers which, in turn, are controlled by
different scenarios of anthropogenic factors/socio-economic behaviour
• The predicted changes are region-dependent
• It must be stressed that there is a lot to learn on both the ‘slow’ processes
and the feedback mechanisms and the abrupt (‘catastrophic’) changes
• It must be noted that (IPCC) predictions are conservative, due to (a) politics
and (b) scientists’ attitude.
4.4 What scenario?
• Impacts are scenario-dependent and, thus, GHG emissiondependent
• These scenarios do not include ‘run-away’ climatic changes due
to feedbacks/tipping points (e.g. permafrost melting, conveyor
belt grinding halts and the melting of the Greenland and Antarctic
ice sheets).
• Major scenarios appear to be optimistic if current attitudes are
taken into account (e.g. the commissioning of new coal plants)
• If the BAU scenario will be the case, in 2050, global annual GDP
is predicted (Stern Review 2006) to be significantly (negatively)
affected (̴ 5 %) annually.
.
5. Erosion costs and adaptation
Few integrated, comprehensive studies on the ecological and socioeconomic impacts of climate-change driven beach erosion
The best studies undertaken in the US, UK and the Netherlands
These studies highlight the huge socioeconomic and environmental costs
of the ‘do nothing’ attitude and the large costs of the inevitable adaptation
For example, it is predicted that in 2050 (at least) 124 million people and
assets of 28 trillion US $ will be at risk of coastal inundation at the 136
coastal megacities
The evidence suggests that we have no other choice but to get prepared
for a huge adaptation effort that will be based on sound science and
engineering.
Thank you for your patience
and see you after coffee!
Fig. 1.
If beaches (and/or coastal
defences) are breached, then
large tracts of back-barrier
ecosystems (e.g. wetlands and
saltmarshes) are under a deadly
threat
The Netherlands disaster case
(Mollema, 2009).
Coastal housing destruction, following short-term
(catastrophic) beach erosion
Fig. 2 S. Carolina (US) beach
(c) before and (d) after a storm
event in September 1996
(USGS, 1996)
Coastal transport infrastructure
Sochi, S. Russia
Fig. 3 The main railway line to Sochi in Black Sea will be in jeopardy, if the fronting
beach would be eroded – which, will be (red line) under 1 m storm surge and offshore
waves with height (H) = 4 m and period (T) = 7.9 sec.
Leont’ yev Model
Present normal
conditions
Storm surge 1 m
US Gulf Coast inundation risk
Fig.4 (a) Flood risk at US Gulf
coast under sea level rise of 06-1.2 m (MSL+ storm surge);
such rise could inundate > 2400
miles of roads, > 70% of the
existing port facilities, 9% of the
rail lines and 3 airports.
(b) In the case of a ~5.4-7 m
rise (MSL+ storm surge), >
50% of interstate and arterial
roads, 98% of port facilities,
33% of railways and 22 airports
could be affected (CCSP,
2008).
Fig. 5. Super Paradise (Mykonos). A
pocket beach with very large
economic potential. Economic value
of Greek beaches min €1400/m/yr.
This beach, €60000/m/yr.
Examples of beach erosion
Erosion
Long-term
%
St.Lawrence,
Canada
rate
Causes
Reference
Storm waves/surges
Forbes et al,
2004
Short-term
%
rate
up to
1.5m/y
S. Carolina (US)
70%
1.4 m/yr
59%
1.8 m/y
Storm waves and surges, SLR
Morton & Miller,
2005
Louisiana
91%
8.2±4.4
m/yr
88%
12.0 m/y
Subsidence,storm waves and surges,
SLR, sediment supply reduction, coastal
works
Morton et al,
2004
Texas (US)
64%
1.8±1.3
m/yr
48%
2.6 m/y
Subsidence,storm waves and surges,
SLR, sediment supply reduction, coastal
works
Morton et al,
2004
C. California
(US)
53%
0.3±0.1
m/yr
79%
0.8±0.4
m/y
El Niño, storm waves and surges, SLR,
sediment supply reduction, coastal works
Hapke et al,
2006
E. China
44%
420 m/y
(delta)
Subsidence, storms, SLR, sediment
supply reduction, coastal works, sand
abstraction
Cai et al, 2009
Provence,
France
40%
60% of erosion due to SLR
Brunel and
Sabatier, 2009
ΝΑΟ Storm waves and surges, SLR, sand
abstraction
Costas & Alejo,
2007
Storm waves and surges, SLR,
Taylor et al.,
2004
Storm waves and surges, SLR, sediment
supply reduction, coastal works
Stanica & Panin,
2009
Storm waves and surges, SLR sediment
supply reduction
Okude &
Ademiluyi, 2006
Storm waves and surges, SLR, sediment
supply and seagrass reduction,
RiVAMP, 2010
Cies Ιslands
(Spain)
0.1±0.03
m/yr
0.44
m/yr
E. UK
Romania,Black
Sea
67%
> 50%
5- 25
m/yr
Nigeria
Negril (Jamaica)
1.7 - 3.2
m/y
3 m/y
>
80%
Up to 1.4
m/yr
Coastal erosion in Europe
(km)
Coastline
erosion 2001
(km)
Protected
coastline 2001
(km)
Eroded
protected
coastline
(km)
Total eroded
coastline
(km)
Belgium
98
25
46
18
53
Cyprus
66
25
0
0
25
Denmark
4605
607
201
92
716
Estonia
2548
51
9
0
60
Finland
14018
5
7
0
12
France
8245
2055
1360
612
2803
Germany
3524
452
772
147
1077
Greece
15780
3945
579
156
4368
Italy
7468
1704
1083
438
2349
Malta
173
7
0
0
7
Poland
634
349
138
134
353
Portugal
1187
338
72
61
349
Spain
6584
757
214
147
824
Sweden
13567
327
85
80
332
UK
17381
3009
2373
677
4705
Total
100925
15111
7546
2925
19732
Coastline
Country
Source: Eurosion, 2004
Coastal development planning/engineering time scales
must take into consideration future climate
Climate Impacts
Engineering
Design
Construction
Potential length of service
Development
Planning Process
Project
Concept
0
10
Adopted
Long-term Plan
20
30
40
50
Years
60
70
80
90
Adapted from Savonis (2011)
100
Long-term beach erosion
Fig. 7 Beach erosion since the 1945 in Morris Island, S. Carolina, US (SEPM, 1996)
Retreat
Advance
L’AMELIE
(m/year)
10
0
(m/year)
-10
-20
ROYAN
-30
- 40
20
German
bunkers built in
1942 on
the foredune
DE
N
O y
IR ar
G stu
E
Pointe de la Négade
Pointe de Grave PK 0
St Nicolas
Les Huttes
Les Arros
SOULAC
L’AMELIE
Pointe de la Négade
LE GURP
3
PK 20
40
PK 40
MONTALIVET
HOURTIN-PLAGE
CARCANS-PLAGE
60
PK 60
LACANAU-OCEAN
LE PORGE-OCEAN
80
PK 80
LE GRAND CROHOT
CAP-FERRET
Source J-P. Tastet
ARCACHON
100
PK
100
Sémaphore
Fig. 9 Nearshore bed cover and
shoreline changes along Negril’s
beaches (at the location of the
74 used beach profiles (RiVAMP,
2010)
Fig.10 Long-term and short-term (catastrophic beach erosion, Eressos
beach E. Mediterranean
Fig. 11 Trends in total annual stream flow into Perth dams 1911–2008.
(Steffen, 2009)
Fig. 12 Coastal sediment supply in the Med has been reduced from 1012 x 106 σε 355
x106 tons/yr during the second half of the 20th century due to the presence of about 3500
dams, 84% of which have been constructed during this period (Poulos et al., 2002).
Fig. 13 (a) The dam and the
Eressos drainage basin/beach,
(c) monthly time series (2004) of
(potential) sediment load (in tons)
of the Eresos basin (black) and
the sub-basin of the dam (white),
for steady and high intensity
(simulated) rainfall for 2 soil
cases (i) sand soil (K=0.03) and
(ii) silt soil (K=0.52). The dam
witholds 52-55% of the sediments
produced in the drainage basin
Fig. 14 Eressos, Lesbos, E. Med 27-2-2004.
The beach, the river and the dam, which
Fig. 15 Sea level rise at
Pensacola (FL) 2.14 mm/yr,
Grand Isle (LA)- 9.85
mm/yr, and Galveston (TX)6.5 mm/yr. These trends
show the high rates of local
subsidence in Louisiana
and Texas relative to the
more stable geology of
Florida (Savonis et al.,
2008)
Fig. 16 Schema showing the beach response to sea level rise. For a sea level
increase α, sediments from the shoreface are eroded and transported to the
submarine section of the beach, resulting to a coastal retreat s.
Fig. 17 Mean temperature rise
1880-2010. NASA Data
(Rahmstorf, 2011).
Projections for 2100:
- Increase 0.5 - 4.0 oC, depending
on the scenario (IPCC, 2007)
Fig.?? Global sea level changes
1860-2010 (Rahmstorf, 2011).
Projections for 2100:
- 0.20 - 0.59 m (IPCC, 2007)
- > 1 m if the melt of Ice sheets is
included (Rahmstorf, 2007)
above the mean sea level of
1980-1999
Fig 18. Long term climate-induced increase in sea level (accelerated sea level riseASLR) is caused by the thermal expansion of the oceans and the melting of continental
ice sheets (IPCC, 2007). The relationship, however is complex, particularly at a regional
level
Fig. 19
(a) Linear trend of annual
temperatures in °C per decade for
1979-2005. Areas in grey denote
insufficient data. Data sets from
Smith and Reynolds (2005). After
IPCC (2007)
(b) Geographic distribution of 19932003 trends in mean sea level
(mm yr–1) based on TOPEX/
Poseidon satellite altimetry (after
Cazenave and Nerem, 2004)
Figure 3.9
Figure 5.15
Figure 3.14
Fig. 20 Annual mean trends (% per century) for 1901-2005 (Grey areas- insufficient data). Time
series of annual precipitation (% of mean for 1961-1990) for the different Green bars
(annual), black bars (decadal variations). After IPCC (2007).
Fig. 21 (a) The decrease of Arctic sea ice: minimum extent in September 1982 and
September 2007 and projections for the future late summers (2010-2030, 2040-2060
and 2070-2090) (http://maps.grida.no/go/graphic/the-decrease-of-arctic-sea-iceminimum-extent-in-1982-and-2007-and-climate-projections-norwegian). (b) Model
results/observations of sea ice loss (Rahmstorf, 2011).
Current trends: More energetic extreme waves
Fig. 22 Increases in the
annual
mean,
winter
averages, mean of the highest
annual waves and annual
maxima
significant
wave
heights at the NDBC #46005
platform (NE Pacific). The
annual maximum significant
wave height has increased 2.4
m! in the last 25 years.
(Ruggiero et al., 2010).
Fig. 23 Predictions
(estimates) showing an
increase in the number of
large storms (hurricanes)
in the US coast (from M.
Beniston, 2009).
Fig. 24 Observed and projected increase in hurricane intensity. If the increase is due to the
relatively higher increase in the Atlantic SSTs relative to other oceans, then the intensity
might relax to earlier levels as inter-ocean basin SSTs equilibrate. Conversely, if the intensity
is related to absolute SSTs, then even more intense cyclones are expected (Steffen, 2009).
Global temperature a result
of energy balance
Heat = solar radiation - back radiation
Trends in GHG atmospheric concentration
Fig. 26 Atmospheric CO2 concentration (in parts per million) during the last 11000 years
(Rahmstorf, 2011) and the last 50 years. The concentrations of the CH4 and N2O (in
ppb-parts ber billion) since 1978 are also shown (Richardson et al., 2009).
Climate change: Natural causes
Fig.
27.
Astronomical
(Milankovich) cycles that force
periodic
increases
and
decreases of incoming heat to
the Earth system (Zachos and
Berger, 2004).
Climate change: Natural causes
Fig. 28. Relationship between temperature and CO2 concentration (from ice
cores in the Antarctic, Petit et al., 1999) with the astronomical cycles
Climate change: Anthropogenic causes
Fig. 29 Tempearture/CO2 concentration increase in the northern hemisphere
in the last 1000 years. Note the large and accelerating increase since the
industrial revolution (e.g. Mann and Jones, 2003; Zachos and Berger, 2004).
Climate change: Natural and anthropogenic
Fig. 30
Diagnosis/prognosis
from
climatic models (Hadley Centre
for Climate Prediction, UK)
which show the combined
natural/anthropogenic
control
on temperature; only combined
forcing results in aggreemnt
between
moels
and
observations
((Mann
and
Jones, 2003).
Fig. 27 Temperature anomalies with respect to 1901-1950 for 6 oceanic regions for (a) 1906-2005
(black line) and as simulated by known forcings; and (b) as projected for 2001-2100 for the A1B
scenario (orange envelope). The bars at the end of the orange envelope represent the range of
Figure 11.22
projected changes for 2091-2100 for the B1 scenario (blue), the A1B scenario (orange) and the
A2 scenario (red). Black line is dashed where observations are present for less than 50% of the
area in the decade concerned.
Fig. 28 Global mean sea level (relative to the 1980-1999 mean) in the past and future (grey
FAQ 5.1, Figure 1
shading shows past uncertainty). The red line from tide gauges (red shading shows variation
range). The green line shows global mean sea level observations from satellite altimetry. Blue
shading represents the range of model projections for the 21st century, relative to the 19801999 mean. Emissions scenario?. More recent research (2008-2011) shows that we may
have underestimated the trends by a factor of 2.5-3.
Table 1. IPCC 2007 socioeconomic scenarios (IPCC 2007)
Fig. 29 Scenario-dependent global warming (IPCC 2007)
Fig. 30 Stabilisation levels/probability
ranges for temperature increases
Types of impacts as the world comes into
equilibrium with greenhouse gases.
•The top panel shows the range of
temperatures projected at stabilisation
levels 400ppm-750ppm CO2 at
equilibrium.
•The solid horizontal lines indicate the 5 95% range based on climate sensitivity
tests from IPCC 2001 and a recent Hadley
Centre ensemble study.
•The vertical line indicates the mean of the
50th percentile point.
•The dashed lines show the 5 - 95% range
based on 11 recent studies.
•The bottom panel illustrates the range of
•impacts expected at different levels of
warming. The relationship between global
average temperature changes and
regional climate changes is uncertain.
(Stern Review, 2006).