Michèle Clarke University of Nottingham, UK Helen Rendell ...
Transcript of Michèle Clarke University of Nottingham, UK Helen Rendell ...
Climate, Extreme Events and Climate, Extreme Events and Land DegradationLand Degradation
MichèleMichèle ClarkeClarkeUniversity of Nottingham, UKUniversity of Nottingham, UK
&&Helen RendellHelen Rendell
Loughborough University, UKLoughborough University, UK
Classifying extremesClassifying extremes
McGregor et al. 2005 In: Extreme Weather and Climate Events and Public Health Responses p13-23.
•• Statistical distributionsStatistical distributions•• Long continuous met Long continuous met
datadata•• Some localities are Some localities are
sparse or no longer sparse or no longer activeactive
•• Data quality issuesData quality issues
IPCC Climate Change Working Group I 2001
Determining change in Determining change in frequencyfrequency
Frich et al. 2002 Climate Research, 19, 193-212
Arblaster & Alexander 2005 Bull. Aust. Met. Ocean. Soc., 18, 125-130
Land DegradationLand Degradation
•• Examine impact of Examine impact of extreme events on extreme events on processes processes
•• FloodsFloods•• Mass movements Mass movements
(landslides, debris (landslides, debris flows)flows)
•• Soil erosion by water Soil erosion by water & wind& wind
•• SalinisationSalinisation
Monitoring ChallengesMonitoring Challenges
•• Long records required Long records required for estimation of for estimation of return periods & return periods & probabilitiesprobabilities
•• Daily met dataDaily met data•• Monitoring natural Monitoring natural
environmentenvironment•• Water & sediment Water & sediment
fluxesfluxes•• Discharge, soil Discharge, soil
erosion, mass erosion, mass movementmovement
Case StudiesCase Studies
•• Individual event Individual event studies are common studies are common esp. if impact societyesp. if impact society
•• Records spanning Records spanning decades with decades with individual event individual event impacts are rareimpacts are rare
•• Event recording Event recording depends on societal depends on societal impactimpact
El Niño related floods, Arizona 1993
Impacts on land degradationImpacts on land degradation
•• Not every event will have the same impactNot every event will have the same impact
•• Mitigation measuresMitigation measures•• Antecedent conditionsAntecedent conditions•• Variation in intensityVariation in intensity•• Variation in vulnerability (maybe seasonal)Variation in vulnerability (maybe seasonal)
•• Lack of consistent recordsLack of consistent records
SarnoSarno mudflows mudflows
•• MazzarellaMazzarella & & DiodatoDiodato20022002
•• List all hydroList all hydro--meteorological events meteorological events resulting in floods and resulting in floods and debris flowsdebris flows
•• But not those that did But not those that did not trigger responsenot trigger response
Mazzarella & Diodato 2002 Theor. Appl. Climatol. 72, 75-84
UNCCD exhibition Matera, Italy 1998
Clarke & Rendell 2006Land Degradation &
Development 17, 365-380
Impact eventsImpact events
•• Land degradation events range in magnitude Land degradation events range in magnitude from landslide blocking minor roads to those from landslide blocking minor roads to those forcing abandonment of townsforcing abandonment of towns
•• Seasonal distribution (autumn & winter) Seasonal distribution (autumn & winter) •• Sometimes simultaneous floods & landslidesSometimes simultaneous floods & landslides•• All events show wet antecedent conditions with All events show wet antecedent conditions with
>50mm falling during previous 30 days (P>50mm falling during previous 30 days (P3030))•• 73% landslides & floods = P73% landslides & floods = P3030 >100mm>100mm•• 16% landslides & floods = P16% landslides & floods = P22 >100mm>100mm
Large impact eventsLarge impact eventsP2 375.6mm; floods
12 landslides; 5 dead, 650 evacuatedP2 119.0mm; floods
400 people evacuated
P2 P2 47.9mm; 22 towns hit by landslides1800 permanently evacuated
P2 64.6mm; landslides500 evacuated, 67 houses destroyed
Pisticci - November 1976
1983 Mitigation measures
Extreme RainfallExtreme Rainfall
•• 10% mean annual rainfall over 5 day period 10% mean annual rainfall over 5 day period ((BrunettiBrunetti et al, 2002, et al, 2002, IntInt Journal ClimatologyJournal Climatology 22, 22, 543543--558)558)
•• 46 events 195146 events 1951--20002000•• 91% autumn/winter91% autumn/winter•• Of 46 extreme rainfall events, 59% caused floods Of 46 extreme rainfall events, 59% caused floods
& landslides which were recorded in the database& landslides which were recorded in the database•• What about remaining 41% ? Mitigation? Lack of What about remaining 41% ? Mitigation? Lack of
reporting?reporting?
Event frequency decreasingEvent frequency decreasing
•• + NAO = dry winters+ NAO = dry winters•• -- NAO = wet wintersNAO = wet winters
•• Correlation between Correlation between NAO & land NAO & land degradationdegradation
•• + NAO = increasing + NAO = increasing land surface stability land surface stability BUT .. salinisation ?BUT .. salinisation ?
Annual Annual -- decadal scale changedecadal scale change
Clarke & Rendell, The Holocene, 16, 341-355
Portugal landslidesPortugal landslides
Trigo et al. 2005 Natural Hazards 36, 331-354
Conclusions: Conclusions: Thoughts on Future Research Thoughts on Future Research
•• Studies of longStudies of long--term (decadalterm (decadal--scale) extreme scale) extreme event impacts on land degradation (as opposed event impacts on land degradation (as opposed to individual events) are useful in developing to individual events) are useful in developing predictive models predictive models
•• Coupling archival and meteorological records for Coupling archival and meteorological records for modelling impacts has real potentialmodelling impacts has real potential
•• Understanding of spatial & temporal resolution of Understanding of spatial & temporal resolution of extreme events and land degradation impacts extreme events and land degradation impacts brings challenges for large scale modellingbrings challenges for large scale modelling