Climate Induced Changes on the Hydrology of Mediterranean Basins - - PowerPoint PPT Presentation

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Climate Induced Changes on the Hydrology of Mediterranean Basins - - PowerPoint PPT Presentation

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Climate Induced Changes on the Hydrology of Mediterranean Basins Lessons learned from the CLIMB project Third Workshop on Water Resources in Developing Countries 30 April 2015, ICTP, Trieste Ralf Ludwig and the CLIMB Consortium A A co colla

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ICTP – Workshop, Trieste, 30 April 2015 1 1

Climate Induced Changes on the Hydrology of Mediterranean Basins

Lessons learned from the CLIMB project

Third Workshop on Water Resources in Developing Countries 30 April 2015, ICTP, Trieste

Ralf Ludwig and the CLIMB Consortium

A A co colla llabora rative ive re rese search rch pro roje ject ct under r the 7th Fra rame mework rk Pro Progra ramme mme Environment, incl. Climate Change (ENV)

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ICTP – Workshop, Trieste, 30 April 2015 2

Climate Change Impacts in the Mediterranean

Source: European Environmental Agency, 2012

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Conclusion…

Measurements and projections indicate…

à severe impacts on water resources management & key strategic sectors of regional economies à a strong need for adaptation à but is all this knowledge useful for the local stakeholder (water user, water manager)? à modeling CC impacts on the local (catchment) scale!

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ICTP – Workshop, Trieste, 30 April 2015 4 4 CLimate Induced Changes on the Hydrology

  • f Mediterranean Basins –

Reducing Uncertainty and Quantifying Risk

  • funded under EU’s FP7 Environment Theme

(Theme: Climate, Water & Security, ENV.2009.1.1.5.2)

  • funding period 50 months (01/2010 – 02/2014)
  • 20 beneficiaries
  • 9 countries:

EU – Austria, France, Germany, Italy SICA – Egypt, Palest. Adm. Areas, Tunisia, Turkey Other – Canada

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ICTP – Workshop, Trieste, 30 April 2015 5

CLIMB – mission & objectives

à analyse future climate induced changes in hydrological budgets and extremes à link the changes in hydrological quantities to vulnerability and associated risks à quantify uncertainties in climate change impact analysis

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ICTP – Workshop, Trieste, 30 April 2015 6

CLIMB – conceptual framework

Hydrological Model 1 Hydrological Model 2 Hydrological Model n Hydrological Models Audit & Uncertainty Assessment GCM / RCM 1 GCM / RCM 2 GCM / RCM n Climate Model Audit & Uncertainty Assessment Study Site Characterization Conventional data (soil, DEM, vegetation, water availability and consumption etc.) Remote Sensing Geophysical Data Acquisition

Parameter retrieval &

Data assimilation Risk Model Vulnerability & Risk Assessment Socioeconomic Factor Assessment Dissemination & Stakeholder Interaction (Interviews, WebGIS, Website, CLIMBPortal)

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ICTP – Workshop, Trieste, 30 April 2015 7

CLIMB – Structure & Workflow

Hydrological Model 1 Hydrological Model 2 Hydrological Model n Hydrological Models Audit & Uncertainty Assessment GCM / RCM 1 GCM / RCM 2 GCM / RCM n Climate Model Audit & Uncertainty Assessment Study Site Characterization Conventional data (soil, DEM, vegetation, water availability and consumption etc.) Remote Sensing Geophysical Data Acquisition

Parameter retrieval &

Data assimilation Risk Model Vulnerability & Risk Assessment Socioeconomic Factor Assessment Risk Model Vulnerability & Risk Assessment Socioeconomic Factor Assessment Dissemination & Stakeholder Interaction (Interviews, WebGIS, Website, Focus Groups etc.)

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ICTP – Workshop, Trieste, 30 April 2015 8

CLIMB – geophysical data acquisition

Study Site Characterization Conventional data (soil, DEM, vegetation, water availability and consumption etc.) Remote Sensing Geophysical Data Acquisition

Parameter retrieval &

Data assimilation

e.g. soil sampling and geostatistical analysis for soil texture regionalization

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ICTP – Workshop, Trieste, 30 April 2015 9

CLIMB – geophysical data acquisition

Study Site Characterization Conventional data (soil, DEM, vegetation, water availability and consumption etc.) Remote Sensing Geophysical Data Acquisition

Parameter retrieval &

Data assimilation

e.g. hydrogeophysical measurements for the regionalization

  • f soil hydraulic

properties

508740 508750 508760 508770 508780 508790 508800 508810 UTM easting (m) 4362630 4362640 4362650 4362660 4362670 4362680 4362690 4362700 4362710 UTM northing (m) 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2 0.22 0.24 0.26 0.28 0.3

CONTENUTO IDRICO 5 APRILE

contenuto idrico (-) TDR

0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2 0.22 0.24 0.26 0.28 0.3

CONTENUTO IDRICO 3 APRILE

contenuto idrico (-)

508740 508750 508760 508770 508780 508790 508800 508810 UTM easting (m) 4362630 4362640 4362650 4362660 4362670 4362680 4362690 4362700 4362710 UTM northing (m)

linea ERT

a b

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ICTP – Workshop, Trieste, 30 April 2015 10

CLIMB – remote sensing

Study Site Characterization Conventional data (soil, DEM, vegetation, water availability and consumption etc.) Remote Sensing Geophysical Data Acquisition

Parameter retrieval &

Data assimilation

e.g. Multitemporal maps of land use for the study sites (e.g. Chiba, Tunisia)

1987 2010

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ICTP – Workshop, Trieste, 30 April 2015 11

CLIMB – remote sensing

Study Site Characterization Conventional data (soil, DEM, vegetation, water availability and consumption etc.) Remote Sensing Geophysical Data Acquisition

Parameter retrieval &

Data assimilation

e.g. Multitemporal soil moisture from radar remote sensing (e.g. Thau, France)

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CLIMB – remote sensing

Study Site Characterization Conventional data (soil, DEM, vegetation, water availability and consumption etc.) Remote Sensing Geophysical Data Acquisition

Parameter retrieval &

Data assimilation

e.g. Retrieval of spatially distributed vegetation parameters (e.g. Noce, Italy & Kocaeli, Turkey)

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CLIMB – Structure & Workflow

Hydrological Model 1 Hydrological Model 2 Hydrological Model n Hydrological Models Audit & Uncertainty Assessment GCM / RCM 1 GCM / RCM 2 GCM / RCM n Climate Model Audit & Uncertainty Assessment Study Site Characterization Conventional data (soil, DEM, vegetation, water availability and consumption etc.) Remote Sensing Geophysical Data Acquisition

Parameter retrieval &

Data assimilation Risk Model Vulnerability & Risk Assessment Socioeconomic Factor Assessment Dissemination & Stakeholder Interaction (Interviews, WebGIS, Website, Focus Groups etc.)

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CMs Auditing & Downscaling – main steps

The objectives of “Climate Models (CMs) Auditing and Downscaling” were pursued in five (5) steps:

  • 1. Climate Model selection (i.e. use a common subset of 4 regional

climate models for hydrological simulations in all target basins) 2. Large-scale bias correction (RCM scales, ~ 25 km) 3. Catchment-scale bias correction (250-3500 km2) 4. Small-scale interpolation and downscaling (i.e. provide high resolution input for hydrological models, about 1 km) 5. Overall uncertainty of climate forcing (i.e. evaluate the uncertainties related to the climatic component)

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CMs Auditing & Downscaling – main steps

!

!

Downscaled 1km "precMF" (mm/year): Catchment "riumannu" year 1954 8.95 9 9.05 9.1 9.15 9.2 9.25 9.3 9.35 39.25 39.3 39.35 39.4 39.45 39.5 39.55 39.6 39.65 39.7 450 500 550 600 650 700 750 800 850 900

!

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CLIMB – Structure & Workflow

Hydrological Model 1 Hydrological Model 2 Hydrological Model n Hydrological Models Audit & Uncertainty Assessment GCM / RCM 1 GCM / RCM 2 GCM / RCM n Climate Model Audit & Uncertainty Assessment Study Site Characterization Conventional data (soil, DEM, vegetation, water availability and consumption etc.) Remote Sensing Geophysical Data Acquisition

Parameter retrieval &

Data assimilation Risk Model Vulnerability & Risk Assessment Socioeconomic Factor Assessment Risk Model Vulnerability & Risk Assessment Socioeconomic Factor Assessment Dissemination & Stakeholder Interaction (Interviews, WebGIS, Website, Focus Groups etc.)

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Hydrological modeling – Some examples: Chiba

2041-2070 1971-2000

Sept Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug

R (mm)

20 60 40

P (mm)

5 10 15 20

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Hydrological modeling – Chiba: Flow duration curve

1971-2000 2041-2070

Discharge (m3/s) High Flow Moist Conditions Mid- Range Conditions Dry Conditions Low Flow

Flow Exceedence Percentile

(Percentage of time that indicated discharge is equated or exceeded)

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ICTP – Workshop, Trieste, 30 April 2015 19

  • Hydrological modeling – Rio Mannu: soil water content
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Hydrological modeling – Rio Mannu: Max number

  • f consecutive low flow days
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Hydrological modeling – Noce: precipitation & runoff

Sept Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug

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  • Hydrological modeling – Noce: swow water

equivalent map

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Hydrological modeling – Noce: average of maximum

daily flow

Sept Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug

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CLIMB – Structure & Workflow

Hydrological Model 1 Hydrological Model 2 Hydrological Model n Hydrological Models Audit & Uncertainty Assessment GCM / RCM 1 GCM / RCM 2 GCM / RCM n Climate Model Audit & Uncertainty Assessment Study Site Characterization Conventional data (soil, DEM, vegetation, water availability and consumption etc.) Remote Sensing Geophysical Data Acquisition

Parameter retrieval &

Data assimilation Risk Model Vulnerability & Risk Assessment Socioeconomic Factor Assessment Risk Model Vulnerability & Risk Assessment Socioeconomic Factor Assessment Dissemination & Stakeholder Interaction (Interviews, WebGIS, Website, Focus Groups etc.)

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Uncertainty assessment

Handling of Uncertainty in science is central to its support of sound policy making” (Smith & Stern, 2011)

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FINDINGS AND IMPLICATION: Both sites:

  • TAW (-15 to -33%),

reduces significantly in FUT

  • CUS rated low (Chiba)

to medium (Rio Mannu)

  • Negative trend

confirmed

  • High confidence on

trend

Uncertainty assessment - 1

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ICTP – Workshop, Trieste, 30 April 2015 27

Certainty Map of key indicators (here TAW)

Monthly

Uncertainty assessment - 2

Annual

  • Decrease trend of long-term annual TAW
  • Monthly-based degree of certainty, more diverse
  • Hotspot areas can be clearly identified
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Spatial representation of Uncertainty (COV in %): Chiba

COV[%] 1971-2000: 15.8 +/- 11.2 COV[%] 2041-2070: 32.5 +/- 24.2 COV[%] 1971-2000: 13.4 +/- 11.2 COV[%] 2041-2070: 25.1 +/- 21.3

Uncertainty assessment - 3

Spatial UA:

  • COV doubles in FUT
  • Clay loam soils with highest COV
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Integrating Uncertainty and Risk

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Tourism – Value at Risk

Distribution of income generated by tourism in Sardinia (Jun.-Aug.) as a function of year-to-year weather variability

Climate signal uncertainty (CUS)

Income estimation: overnight stays * average expenditure per overnight stay

MEUR % REF 11.6 1.6 FUT 52.3 7.2 FUT (+Trend) 64.2 8.6 VaR(0.9):

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Tourism – potential CC-impacts

Expected change in overnight stays (in %) due to a change from reference (1971-2000) to future (2041-2070) climatic conditions

Potential losses in summer … … BUT … … tendentially positive annual net impacts.

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Tourism – future water demand scenarios

Change in future water demand (2041-2070) of tourism (Nabeul) during spring for different growth and water use scenarios

Effect of CC-independent overnight stay (os) growth and/or of change in average water consumption per os CC impact (multi-model-mean)

Current Tunisian average Target value (formulated in 2002) Maximum observed in recent years

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Agriculture - Tomatoes (same water usage as current)

March plantings – Yield ↓ 17% August planting – Yield ↓ 17% Results are soil dependent – Sandy clay loam strongly affected – Sandy loams least affected

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March plantings – Yield ↓ 86% – Crop failure 45% August planting – Yield ↓ 17% Total harvest: 50% less yield

Agriculture - Tomatoes (10% less water usage as current)

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Agriculture – Adaptation recommendations

Agricultural risk can be minimised through adaptation For crops / management systems at risk – Mulching – Alter planting dates to follow seasonal changes – Switch crops / management systems to lower risk systems that require less irrigation – Discontinue high risk irrigation of crops / management systems on specific soils – Discontinue high risk irrigation of crops / management systems completely Use irrigation water saved on remaining crops or for other purposes (tourism) Severity

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CLIMBPortal – the window to the inside/outside

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CLIMBPortal

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CLIMBPortal – http://lfi-climbsrv.geographie.uni-kiel.de

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CLIMBPortal – conclusion

The CLIMBPortal solved: à the problem of heterogeneous data and file formats à the missing of ISO-compliant metadata à the lack of a uniform presentation of model results The CLIMBPortal offers: à compliance to required geospatial standards (e.g. INSPIRE, OGC) à maps and figures of easy-to-interpret hydrological indicators à access to underlying data for registered users à a WebGIS-client that integrates external Web Mapping Services à an open source solution for longterm availability of CLIMB results

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Conclusion: CLIMB – mission & objectives (revisited)

This is what we announced: à to analyse ongoing and future climate induced changes in hydrological budgets and extremes à to link the changes in hydrological quantities to vulnerability and associated risk à to quantify (reduce?) uncertainties in climate change impact analysis à yes, but we had no means to look at all extremes à yes, a very comprehensive framework was established, but could only be filled partially à we managed to somewhat quantify (and even rank) uncertainties in some cases; but there was/is no way to effectively reduce it…

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CLIMB – Some closing remarks

What needs to be done (some personal thoughts for scientists and the EC): à monitoring, monitoring, monitoring… à uncertainty analyses! à broaden the view (looking at ‘climate induced changes…’ alone imposes limits) and improve the networks among projects

à continuity?

à Dissemination activities à Portals à Project follow-ups…

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ICTP – Workshop, Trieste, 30 April 2015 42 42

  • Prof. Dr. Ralf Ludwig

CLIMB Co-ordinator Department of Geography LMU Munich, Germany r.ludwig@lmu.de

www.cliwasec.eu www.climb-fp7.eu

Thank you for your attention!

Nuraghe Arrubiu Dam – Sardinia (Italy)

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Developing the cluster

Critical mass of 46 Partners

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Objectives of the CLUSTER

  • Scientific Synergy

Study Sites are comple- mentary in scope, region and scale à share information and data à Identify common stake- holder groups à compare and integrate model results à joint publications à joint science-policy briefs

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Summary for Policymakers

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Summary for Policymakers

WASSERMed - Research Highlights

  • The warming trend and changes in precipitation patterns could affect the

composition and functioning of natural and managed ecosystems.

  • Growing non-agricultural water needs will strongly affect agricultural water

shortages in the Southern Mediterranean; Water resources for environmental preservation, are likely to decrease, especially in the MENA region.

  • Intra-Mediterranean virtual water trade is likely to decline, with virtual imports

from central and northern Europe increasing.

  • Improved water efficiency appears to significantly mitigate the economic

impacts of water scarcity, especially in the Northern areas.

  • A seasonal change in tourism is probable due to improving climate conditions

in spring and autumn and a slight deterioration in summer.

  • Crop water requirements are very likely to increase in all case studies,

requiring specifically adapted management practices.

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Summary for Policymakers

CLICO - Research Highlights

  • Climatic and hydrological factors seem to be less influential than political,

economic and social factors for most water-related conflict situations.

  • Democracies are likely to have more domestic water conflicts than

autocracies, but autocracies are likely to have more violent water conflicts than democracies.

  • Wars and violence increase the vulnerability of the population to hydro-

climatic hazards.

  • States can maladapt, that is they pursue adaptation policies that end up

increasing, instead of decreasing, the vulnerability of parts of their population.

  • Social security and civil security institutions – such as entitlement schemes,

unemployment insurance, universal health care, or flood relief agencies – are central for reducing vulnerabilities and providing human security.

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Summary for Policymakers

CLIMB - Research Highlights

  • Climate change contributes, yet in strong regional variation, to water scarcity in

the Mediterranean; other factors, e.g. pollution or poor management practices are regionally still dominant.

  • Rain-fed agriculture needs to adapt to seasonal changes; stable or increasing

productivity likely depends on additional irrigation.

  • Tourism could benefit in shoulder seasons, but may expect income losses in the

summer peak season due to increasing heat stress.

  • Local & regional water managers and water users, lack, as yet, awareness of

climate change induced risks; emerging focus areas are supplies of domestic drinking water, irrigation, hydro-power and livestock.

  • Data and knowledge gaps in climate change impact and risk assessment are

still wide-spread and ask for extended and coordinated monitoring programs.

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  • Prof. Dr. Ralf Ludwig

CLIMB Co-ordinator Department of Geography LMU Munich, Germany r.ludwig@lmu.de

www.cliwasec.eu www.climb-fp7.eu

Thank you for your attention!

Nuraghe Arrubiu Dam – Sardinia (Italy)