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Pascal Peduzzi, Bruno Chatenoux and Adonis VelegrakisUNEP/GRID-Geneva
Risk and Vulnerability Assessment Methodology development Project (RiVAMP)
Kingston, 5-8 December 2011
www.grid.unep.chRiVAMP training sessionQuantifying the role of ecosytems
Work plan
Dates Morning Afternoon
5 Dec. 2011 Presentation of RiVAMP methodology
Presentation of OpenSource GIS
QGIS practices (creation of population grid & bathymetric grid)
6 Dec. 2011 Estimation of exposure; data extraction for statistical analysis
data extraction for statistical analysis (practice)
Work plan
Dates Morning Afternoon
7 Dec. 2011 Identification of the role of ecosystems using statistical regressions
Beach erosion: Occurrence & Impacts
8 Dec. 2011 Beach Morphodynamic Models I & II
Beach Morphodynamic Models III & IV
A. Velegrakis
UNEP
DEWA DEPI DRC DGEFDCPIDTIEDEWA
UNEP/GRID-Geneva
Global Change & Vulnerability
Unit(ex Early Warning)
P.Peduzzi C.Herold G. Giuliani
Global Change & Vulnerability Unit
R. Harding
Swiss Env. Agency
University of Geneva
B. Chatenoux
Global Change & Vulnerability: a unit of the
UNEP/GRID-Europe
Field data collection
Image analysisStatistical analysisSpatial analysis (GIS)
Global Change & Vulnerability Unit
Maps & Info
1999 - 2010
PREVIEW
Data (SDI)
1. Introduction: why RiVAMP ?
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1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010
World Population1975: 4.1 billion1990: 5.3 billion2011:7.0 billion
Population distribution change between 1975 and 2011
What are the drivers of global change?
More than 50% of world population is now urban…… and about a third of urban population lives in slums
Glaciers:Precipitations’buffers and watertanks.
19792007
Rise faster than expected
Future projections
Future sea level (rel. to 1990) basedon IPCC AR4 global temperature projections
Full range: 75 – 190 cm by 2100
Vermeer & Rahmstorf, PNAS 2009
constant rate 3.2 mm/year
Fig.1 Beach erosion (defined as irreversible coastline retreat) due to increased sea level
S, coastal retreat, α, sea level rise
Driver 1: Sea level rise (ASLR), process
Driver 2: Tropical cyclones & SST
North Atlantic tropical cyclones by temperatures
3. RiVAMP in Negril
Aims of RiVAMP
1 Env’ factors, climate change & Tropical Cyclones Disaster Risk in SIDS
2 Associate scientific quantitative analysis together with local expertise and community consultations
3 Quantifying the role of ecosystems and climate change on risk
Identifying local perspectives for developments4
Provide capacity building, to multiply these assessments.5Targeting audience at governments (both local and national levels) to
achieve better land planning.6
Study area: Negril
Erosion rate between 1968-2006 : 0.5 and 1 m/yr(large temporal and spatial variability; Smith Warner International, 2007)
Observation 2006-2008, shows that beach erosion continues (UNEP, 2010)
Aims of the spatial analysis
1. Evaluate the scale of beach erosion and coastal ecosystem degradation;
2. Identify the role of geomorphology (bathymetry, elevation) and natural features (coral, sea- grass) in the observed erosion patterns;
3. Prognosis under different Sea Level Rise scenarios and under increases in the frequency/intensity of tropical cyclones.
4. Identify population and infrastructures exposed to tropical cyclones storm surges.
Current beach erosion rate
Erosion rate between 1968-2006 : 0.5 and 1 m/yr(large temporal and spatial variability; Smith Warner International, 2007)
Observation 2006-2008, shows that beach erosion continues (UNEP, 2010)
Beach erosion: the drivers
1. Sea level rise
2. Storm surges from tropical cyclones.
3. Waves from storms
4. Decline of ecosystems
5. Presence of infrastructures
Hypothesis (not comprehensive)
Driver 1: See level rise
Sea levelrise (m)
Minimum beach retreat (m)
Maximum beach retreat (m)
0.35 3.6 12.3
0.52 5.3 17.3
0.65 6.3 20.9
0.75 7.5 24.0
1.05 10.0 32.9
2.02 20.6 61.9
2.55 25 78.7
Beach erosionScenarios
Beach erosionScenarios
Intensity equivalent to
return period
(years)
Hs
(m)
Period
(s)
Max. combined sea level elevation
(m)
Probability
for a period of 50 years
5 4.7 8.7 0.45 99.9
10 6.4 10.7 0.65 99.5
25 8.2 12.4 0.74 87.0
50 9.2 13.4 0.93 63.6
100 10.2 14.3 1.25 39.5
150 10.7 14.7 1.29 28.4
Sources: SWI, 2007. Key: Hs = significant wave height; Period = significant wave period; Max. combined sea level elevation, sum of inverse barometric pressure effects, long-term sea level rise (assumed at 5 mm/yr) and tidal effects (0.3 m above Mean Sea Level on springs).
Driver 2: Tropical cyclones, generated waves
Numerical model results for wave heights (a) and wave-induced currents (b) at the Negril coast. Conditions: Offshore wave height (Hrms) = 2.8 m, Tp=8.7 s. Wave approach from the northwest. Note the diminishing wave heights and changed nearshore flow patterns at the lee of the shallow coral reefs.
Driver 3: High waves
Driver 4: Decline of ecosystems
Does the ecosystems (coral, seagrass) provide protection
against beach erosion ?
Sea grass and coral reef are declining (see later)
Site ID 55
Erosion 20.5124
Seagrass width 424
Dense Seagrass width 240
Width Reef 110
Deep Reef width 344
Total Seagrass Width 664
Depth at 500m 3.987434
Depth at 1000m 1.8887
Depth at 1500 m 6.466622
Depth at 2000m 20.57736
Depth at 2500 m 50.82628
Depth at 3000m 77.97657
Distance to 4 m depth 1168
Distance to 5 m depth 1316
Distance to 6 m depth 1420
Distance to 10 m depth 1738
6m depth
Erosion
Profiles
Data extraction
Driver 4: Multiple regression analysis
The model explains 41% of the erosion (correlation r=0.64).
Sea grass, slopes and waves were selected as significant parameters in the model. Sea grass plays the main role (47%): the wider the sea grass the less the erosion.
Erosion rate behind sea grass
Driver 4: Multiple regression analysis
Erosion rate behind coral
The model explains 83% of the erosion (correlation r=0.91).
Coral width and slopes were selected as significant parameters in the model. Width of coral plays the main role (59%): the wider the coral the less the erosion.
Waves H=2.8 m, T= 8.7s
Sea level rise 1m
Coastal ecosystem importance: beach protection by coral reefs
Fig. 9b. Modelled bed shear stress (force per unit area) (SBEACH model) induced by waves in the Negril coastal zone, showing the protection effects of inshore coral reefs
Coastal ecosystem importance: beach protection by seagrass meadows
Fig. 11. Modelled bed shear stress (force per unit area) (SBEACH mode (wave height 1 m, period 6s) in the Negril coastal zone
The seagrass meadows spread the wave force on wider area and dissipate wave energy
Without meadows
With meadows
Flooded areaReclassification of elevation grid
Wave splash on cliff: 7.5 m 8.0 m
Return period (years) 10 50
Tide (m) 0.3 0.3
Inverse Barometric Pressure Rise (m)
0.22 0.38
Global Sea Level rise (m) 0.1 0.5
Storm surge (m) 0.3 1.5
Wave run-up (m) 2.7 4
Storm wave elevation: 3.6 m 6.7 m
Exposure to tropical cyclones
Population exposure1 km grid10 yrp: 478 people exposed50 yrp: 2 487 people exposed
Population on the littoralarea: 18 500
Exposure to tropical cyclones
Assets exposure10 yrp
Asset type Beach Cliff
Hotels 2
Markets 1
Nwc priority facilities 1
Wastewater facilities 2
Wells 1
50 yrpAsset type Beach Cliff
Emergency shelters 1
Health centres 3
Health facilities 2
Hotels 61 2
Markets 1
Nwc priority facilities 2
Public schools 1
Touristic facilities 3
Waste water facilities 6 2
Wells 9
licj airport 1
Exposure to tropical cyclones
Stakeholder consultations
Quatre Bornes, September 2010
2. Stakeholder consultations
Study Area: Negril
• National level
• Negril Parish level
• CommunitiesWhitehall
Little Bay
Major Types of Ecosystems in Jamaica
• Coral reefs• Coastal vegetation: sea
grasses, mangroves and other types of beach vegetation
• Wetlands / peatlands (the “morass”)
• Forests
Critical services provided by ecosystems
Provisioning services Regulating / Buffering services
Social-cultural benefits
• Supports local livelihoods
• Supports other important economic activities
• Coastal ecosystems supply beach sediments
• Supports biodiversity
• Coastal ecosystems contribute to coastal stability and shoreline protection against storm surges
• Trees (including mangroves) act as a wind breaker and protective barrier
• Wetlands serve as a
natural filter and flood control system
• Forests protect watersheds and stabilize soils
• Educational / research opportunities
• Recreation / leisure / sports activities
• Contributes to local cultural identity
Drivers of ecosystem degradation
External drivers Local human-induced drivers
• Impacts from tropical storms or cyclones (hurricanes)
• Pathogens / diseases (e.g. CWBS, black sea urchin die offs)
• Climate change and variability: increased sea surface temperatures and more frequent and intense storms
• Invasive species (e.g. lionfish)
• Fires / drought
• Beach erosion
• Land-based sources of pollution: agricultural runoff, sewage and freshwater drainage, road and building construction runoff, solid waste
• Removal of sea grasses and other types of beach vegetation
• Coastal development
• Deforestation / vegetation clearance
• Destructive and unsustainable fishing practices
• Tourism-related activities
Community profile: Little Bay
• Small, rural community of about 350 residents
• Highly exposed to storm surges and strong winds due to hurricanes
Community profile: Whitehall
• Experienced rapid growth in past 30 years, mainly due to the expansion of tourism
• Frequent flooding due to heavy runoff
Methods used
• Break out group sessions
• Community mapping (past and present)
• Hazard mapping• Seasonal calendars • Ranking exercises
Key livelihoods depend on natural resources but contribute to ecosystem degradation
• Fishing • Farming • Tourism • Fuelwood production
Environmental degradation increases local exposure and vulnerability to hazards
Storm surges in Little Bay • Increased storm surge-related
flooding over the past 20 years
• Attributed to beach erosion, hurricanes, coral reef degradation, removal of coastal vegetation (mangroves, fruit trees and sea grasses) and illegal sand
mining
Local coping strategies stress the importance of ecosystem protection
• Depending on hurricane damage, residents may be forced to rely on unprotected groundwater sources for drinking and wood sources for fuel and housing materials.
• Local reliance on natural resources in post-hazard contexts highlights the importance of protecting ecosystems to ensure continued access to these services.
Priority Issues and Proposed Solutions
Negril faces 3 main options:
• Change nothing,
• Managed retreat
• Coastal engineering
• Improve the protection of coastal ecosystems
+
Results from the Project Evaluation A project evaluation was undertaken on 14-15 May 2010 (summary)
• UNEP provided added value as an external actor.
• Very good data collection and generation, including new satellite images at very high resolution.
• Successfully demonstrated the role of ecosystems for mitigating shoreline erosion and climate change scenarios.
• High government buy-in at all levels. National media coverage.
• Needs an economic analysis.
• Should start by defining long-term development needs. Then environment role(s) will follow.
• Limited timeframe; limited space for hands-on learning by local partner(s).
• Missing a third component: running scenarios with local / national land-use planning authorities
5. GAR 2009 presentation
Figure 2 Spatial pattern of terrestrial NPP linear trends from 2000 through 2009 sources: with kind permission of Zhao and Running, 2010.
More CO2 was supposed to increase photosynthesis (Nemani et al., 2003). But recent measurements on the warmest decades (2000-2009) show that the creation of biomass is slower. (Zao & Running, 2010) Photosynthesis also request H2O, which may be the limiting factors
We thought that with more CO2, there would be more photosynthesis, thus more biomass (Nemani et al. 2003). But it is not the case. Water might be the limitation factor (Zao & Runnin, 2010)
Forest: less biomass produced
Forest: drought, more fires
More drought, more forest fires (Van der Werf et al. 2008)
More drought more forest fires.From Van der Werf et al., (2008), reproduced with kind permission from the authors and courtesy of National Academy of Science.
Positive feedbacks
LessPhotosynthesis
LessCarbon sinks
Warmer temperatures
More CO2
More droughts
Less precipitationsHigher temperatures
MoreForest fires
DeforestationClimate change, deforestation, drought and forest firesA triple-loop of positive feedbacks
Peduzzi et al. (in prep.)
1973: Forests
2000: Deforestation in Paraguay
Barrage d’Itaipu et rivière d’Iguazu
Aral sea: coton is drying out the sea
18 June 2009
20042002
8 Jan. 2010
1973 – a town of 400’000 inhabitants
Images courtesy USGS
Las Vegas
2000 – 1 million inhabitants
Las Vegas
Lake Chad
1975 – Natural forest cover
Amazonia: lungs cancer
Rondonia, Brésil
1989 - Patterns showing conversion of forest to crops.
2001 – Crops are supplanting forest
Santa Cruz, Boliva: Land Use Change
Body text 1975: Forests
2000: agriculture fields for larege compagnies
Honduras: shrimps eat mangroves
1987-1999: shrimps farms are replacing mangroves in the golf of Fonseca.
Mine de cuivre en Papua Nouvelle-Guinée
1990-2004: Impacts d’exploitations minières dans le lit de la rivière
Local level
• The interest for the role of ecosystems in mitigating DRR increased sharply after the tsunami… although no scientific evidences were found.
„We used a zero intercept in our statistical analysis where this should not have been the case…“
SUMMARY:
no evidence for a protection function from this study
…lots of new (empty) housing
close to the seafront
(within the tsunami hazard zone?)
for example…
Aid efforts in Aceh: NGO‘s delivering with little acceptance
…without proper Planning and Research
…costly engineered coastal defence measures……and not necessarily very helpful…
…(fast) Action without Proper Surveying
As of August 2006
75% dead 98% dead
100% dead 100% dead
Photo B. McAdoo
Landslides mitigated by dense vegetation
Souces: Peduzzi, P.: Landslides and vegetation cover in the 2005 North Pakistan earthquake: a GIS and statistical quantitative approach, Nat. Hazards Earth Syst. Sci., 10, 623-640, 2010.