International Symposium CLIMATE-ES March 2015 Tortosa, Tarragona, Spain

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1 (1) Museo Nacional de Ciencias Naturales, CSIC, Madrid (2) Dpt. of Geography and Earth Sciences, Aberystwyth University, UK (3) Institute of Geography, Leipzig University, Leipzig, Germany. (4) School of Geography, University College Dublin. International Symposium CLIMATE-ES March 2015 Tortosa, Tarragona, Spain

2 IPCC AR5 Ch. 3: Freshwater Resources Observed and projected impacts on hydrology are widespread and consequential Glacier melting: Most glaciers are too big even for the present climate; future warming will only increase rates of loss and (eventually) disappearance Reduced freshwater resources in subtropical regions Projected increase of flooding (some regions) due to climate change Morteratsch Glacier, Alps, circa 1900 Credits: Jürg Alean Morteratsch Glacier, Alps, 2012

3 Freshwater resources and climate change Each degree of warming will diminish the renovable water resources of ca. 20%, considering an increase of World population of 7%. Reduction of freshwater resources will increase competition among sectors such as agriculture, ecosystems, people, industry and energy production.

4 Significant reduction of freshwater resources Percentage of change in the annual mean runoff associated to a temperature increase of 2ºC Increase of 2ºC in relation to the reference period Scenario RCP8.5 (Schewe et al., 2013). Schewe, J., and 24 others, 2014, Multimodel assessment of water scarcity under climate change, Proceedings of the National Academy of Science, 111(9),

5 Normalized probability Are floods increasing due to Global Warming? Individual floods occurring presently cannot be directly related to climate change impacts. However, recent studies show that in some regions (e.g. UK) extreme floods are between 3 to 4 times more probably to occur in a warming World than under a natural World. Increase on flood risk attributed to Climate Change - Magnitud de inundación + Pall, P., and 7 others, 2011, Anthropogenic greenhouse gas contribution to flood risk in England and Wales in autumn Nature, 470,

6 A high-carbon future will expose more people to the risk of floods RCP8.5 1 Hydrological model + 11 GCMs of CMIP5 Hirabayashi, Y., and 6 others, 2013, Global flood risk under climate change, Nature Climate Change, 3,

7 Bi-decadal flood frequency based on documentary and instrumental records Decrease In winter floods Decrease frequency. Puntuated large floods Decrease in winter floods Summer floods increased magnitudes in some sites Increase of extraordinary floods Decrease frequency & magnitude Increase flooding IPCC AR5, Ch. 5: Information from Paleoclimate Archives

8 Holocene floods in the Mediterranean Hydroclimatical diversity of flooding Palaeoflood records in fluvial environments Methodological approach for detecting changes on flood frequency from palaeoflood dated units Results at regional and inter-regional level Hydroclimatic interpretation of palaeoflood records

9 Hydroclimatic spatial variability in the Mediterranean Rainfall regions based on PCA analysis of weather types from daily surface pressure centres at 500hPa Rainfall regimes in the Mediterranean with indication of seasonal rainfall maxima Thornes et al., 2009 Littmann, 2000 Zorita et al., 2004 Xoplaki et al., 2004 Correlation between NAO index and Mediterranean precipitation in the cold season (December-February) Correlation between the East Atlantic/Western Russia patterns (EA/WRUS; Xoplaki et al., 2004) and winter (NDJF) Mediterranean precipitation

10 Palaeoflood: A flood that has occurred prior to the systematic gauging record and its magnitude and timing are estimated by indirect hydraulic, geologic, geomorphic, sedimentologic and botanical methods. V.R. Baker (1983)

11 Relevant fluvial data sources: Slackwater flood deposit analysis: Sedimentary records of floods; R: ka Overbank floodplain deposits: Cut and fill sequences recording major changes on discharge-sediment load; R: ka Flood-basin environments - Infill continuous sequences; R: 0.1 ka

12 Fluvial sedimentary environments recording palaeofloods HIGH LEVEL FLOW LOW LEVEL FLOW

13 Fluvial sedimentary environments recording palaeofloods CHANNEL WIDENING TRIBUTARY MOUTH HIGH LEVEL FLOW LOW LEVEL FLOW

14 Palaeoflood sediments in the Gardon River, Southern France Sheffer et al., 2008

15 Lower Moulouya River, NE Morocco Zielhofer et al., 2010

16 Guadalentín River, SE Spain Benito et al., 2010; Medialdea et al., 2013

17 Objectives Compile a large database of 14 C and OSLdated Holocene fluvial units Identify past extreme hydrological events their temporal and geographical distribution across the Mediterranean Explain these patterns in the context of regional variability of climate fluctuations (100s-1000s years), and land-use changes

18 Location of 14C and OSL sample sites included in the analysis Benito et al., 2015, Catena

19 Methodology Construction of a database based on own work and published literature C and 53 OSL dates from 62 river sites Each date was classified according to depositional environment, type of material dated, drainage area, elevation.

20 Data Analysis Analysis of the database was carried out through cumulative probability plots (produced using the OXCAL calibration programme). This sums all the individual probabilities of each radiocarbon date during calibration and add each OSL datings (2-sigma values). Different data-sets can be analysed to compare records e.g. probability plots were produced for all samples; different depositional environments; & different catchment area classes

21 Data Interpretation The x axis of the cumulative probability plots represents the temporal distribution of the dates entered into the analysis. The y axis indicates the summed probability per year. Care must be taken when interpreting the shape of the curve, in particular the peaks in probability can relate to the shape of the calibration curve.

22 10,750-10, Cal BP Holocene Optimum Transition to cold periods Temperature GW Benito et al., yr LIA MCA

23 Summed probability plots from databases of radiocarbon dates yrs BP Floodplain Cold-wet period BP BP MCA LIA SWD Thorndycraft and Benito, 2006; Benito et al., 2008

24 Large floods are related with negative NAO phase Salgueiro et al., 2012

25 Iberian Peninsula Western: C dates; Eastern C dates Southern France: C and 6 OSL dates Southern Italy: C dates Central Tunisia: C dates North-east Morocco: C dates Eastern Mediterranean: 47 OSL and C dates

26 Centennial to multi-centennial episodes of flooding in the Mediterranean regions W-Iberian Peninsula (cal. yr B.P.) E-Iberian Peninsula (cal. yr B.P.) Southern France (cal. yr B.P.) NE-Morocco (cal. yr B.P.) Southern Italy (cal. yr B.P.) Tunisia (cal. yr B.P.) Eastern Mediterrane an (cal. yr B.P.) Overlapping (cal. yr B.P.) (No. of regions) (4) (5) (3) (4) (4) (4) (2) (3) (3) ~300 (3) (3)

27 Centennial to multi-centennial episodes of flooding in the Mediterranean regions W-Iberian Peninsula (cal. yr B.P.) E-Iberian Peninsula (cal. yr B.P.) Southern France (cal. yr B.P.) NE-Morocco (cal. yr B.P.) Southern Italy (cal. yr B.P.) Tunisia (cal. yr B.P.) Eastern Mediterrane an (cal. yr B.P.) Overlapping (cal. yr B.P.) (No. of regions) (4) (5) (3) (4) (4) (4) (2) (3) (3) ~300 (3) (3)

28 Region Proximity matrix based on Jaccard s similarity coefficient, last 5000 yrs. Binary information of temporal flood activity in 100-yr bins The highest similarity value equals 1 W-Iberia E-Iberia Southern France Proximity Matrix (Jaccard s Measure) Morocco (NE) S.Italy Tunisia Eastern Mediterranean W-Iberia E-Iberia Southern France Morocco (NE) Southern Italy Tunisia Eastern Mediterranean Classes: 1: Flood activity 100-yr bins; 0: Non-activity 100-yr bins. Percentage of class 1 values in datasets. W Iberia 25.5%; E Iberia 27.5%; S France 37.3%; Morocco 27.5%; S Italy 35.3%, Tunísia 45.1%; E Mediterranean 29.4%. Correlation values larger than 0.20 are printed in bold

29 Region Proximity matrix based on Jaccard s similarity coefficient, last 5000 yrs. Binary information of temporal flood activity in 100-yr bins The highest similarity value equals 1 W-Iberia E-Iberia Southern France Proximity Matrix (Jaccard s Measure) Morocco (NE) S.Italy Tunisia Eastern Mediterranean W-Iberia E-Iberia Southern France Morocco (NE) Southern Italy Tunisia Eastern Mediterranean Classes: 1: Flood activity 100-yr bins; 0: Non-activity 100-yr bins. Percentage of class 1 values in datasets. W Iberia 25.5%; E Iberia 27.5%; S France 37.3%; Morocco 27.5%; S Italy 35.3%, Tunísia 45.1%; E Mediterranean 29.4%. Correlation values larger than 0.20 are printed in bold

30 Cluster diagram of flood temporal patterns similarity using Jaccard Index

31 Atmospheric circulation, climate drivers and flooding in the Iberian Peninsula

32 Atmospheric circulation, climate drivers and flooding in the eastern Mediterranean Proxy of Intensity of Siberian High

33 Conclusions A meta-data analysis of dated fluvial units shows eleven region-wide flood episodes Flood clusters were related to atmospheric circulation patterns controlled by climate Western Mediterranean flooding increased in cool and wet conditions and negative NAO. In Iberia, some flood episodes also responded to high hydroclimatic variance (warming-dry: phases). North African flood episodes coincide with periods of generally drier climate An east-west Mediterranean opposite flood pattern implies a bipolar hydroclimatic behaviour at multidecadal to centennial time-scales

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35 Thanks for your attention Gracies, Gracias Guadalentín River: 1802 flood in Lorca