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 ICTP – Workshop, Trieste, 30 April 2015 1 1 Environment, incl. Climate Change (ENV)
Climate Change Impacts in the Mediterranean Source: European Environmental Agency, 2012 ICTP – Workshop, Trieste, 30 April 2015 2
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! ICTP – Workshop, Trieste, 30 April 2015 3
CL imate I nduced Changes on the Hydrology of M editerranean B asins – 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 ICTP – Workshop, Trieste, 30 April 2015 4 4
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 ICTP – Workshop, Trieste, 30 April 2015 5
CLIMB – conceptual framework GCM / RCM GCM / RCM GCM / RCM Study Site Characterization 1 2 n Conventional data (soil, DEM, vegetation, water availability Climate Model Socioeconomic Factor and consumption etc.) Audit & Uncertainty Assessment Assessment Remote Sensing Hydrological Hydrological Model 1 Models Parameter retrieval & Hydrological Model 2 Risk Model Data assimilation Audit & Uncertainty Geophysical Data Hydrological Model n Vulnerability Assessment Acquisition & Risk Assessment Dissemination & Stakeholder Interaction (Interviews, WebGIS, Website, CLIMBPortal ) ICTP – Workshop, Trieste, 30 April 2015 6
CLIMB – Structure & Workflow GCM / RCM GCM / RCM GCM / RCM Study Site Characterization 1 2 n Conventional data (soil, DEM, vegetation, water availability Climate Model Socioeconomic Factor Socioeconomic Factor and consumption etc.) Audit & Uncertainty Assessment Assessment Assessment Remote Sensing Hydrological Hydrological Model 1 Models Parameter retrieval & Hydrological Model 2 Risk Model Risk Model Data assimilation Audit & Uncertainty Geophysical Data Hydrological Model n Vulnerability Vulnerability Assessment Acquisition & Risk & Risk Assessment Assessment Dissemination & Stakeholder Interaction (Interviews, WebGIS, Website, Focus Groups etc.) ICTP – Workshop, Trieste, 30 April 2015 7
CLIMB – geophysical data acquisition e.g. Study Site Characterization soil sampling and geostatistical analysis for soil texture Conventional data (soil, DEM, regionalization vegetation, water availability and consumption etc.) Remote Sensing Parameter retrieval & Data assimilation Geophysical Data Acquisition ICTP – Workshop, Trieste, 30 April 2015 8
CLIMB – geophysical data acquisition e.g. Study Site Characterization hydrogeophysical measurements for Conventional data (soil, DEM, the regionalization vegetation, water availability of soil hydraulic and consumption etc.) properties Remote Sensing Parameter retrieval & CONTENUTO IDRICO 3 APRILE CONTENUTO IDRICO 5 APRILE Data assimilation 4362710 4362710 TDR Geophysical Data contenuto linea ERT idrico 4362700 4362700 (-) Acquisition contenuto idrico 4362690 0.3 4362690 (-) 0.28 0.26 0.3 4362680 0.24 4362680 0.28 0.22 UTM northing (m) UTM northing (m) 0.26 0.2 0.24 0.18 4362670 4362670 0.22 0.16 0.2 0.14 0.18 0.12 4362660 4362660 0.16 0.1 0.14 0.08 0.12 4362650 0.06 4362650 0.1 0.04 0.08 0.02 0.06 4362640 0 4362640 a b 0.04 0.02 0 4362630 4362630 508740 508750 508760 508770 508780 508790 508800 508810 508740 508750 508760 508770 508780 508790 508800 508810 UTM easting (m) UTM easting (m) ICTP – Workshop, Trieste, 30 April 2015 9
CLIMB – remote sensing e.g. Study Site Characterization Multitemporal maps of land use for the study sites (e.g. Chiba, Tunisia) Conventional data (soil, DEM, vegetation, water availability 1987 and consumption etc.) 2010 Remote Sensing Parameter retrieval & Data assimilation Geophysical Data Acquisition ICTP – Workshop, Trieste, 30 April 2015 10
CLIMB – remote sensing e.g. Study Site Characterization Multitemporal soil moisture from radar remote sensing (e.g. Thau, France) Conventional data (soil, DEM, vegetation, water availability and consumption etc.) Remote Sensing Parameter retrieval & Data assimilation Geophysical Data Acquisition ICTP – Workshop, Trieste, 30 April 2015 11
CLIMB – remote sensing e.g. Study Site Characterization Retrieval of spatially distributed vegetation parameters (e.g. Noce, Italy & Kocaeli, Turkey) Conventional data (soil, DEM, vegetation, water availability and consumption etc.) Remote Sensing Parameter retrieval & Data assimilation Geophysical Data Acquisition ICTP – Workshop, Trieste, 30 April 2015 12
CLIMB – Structure & Workflow GCM / RCM GCM / RCM GCM / RCM Study Site Characterization 1 2 n Conventional data (soil, DEM, vegetation, water availability Climate Model Socioeconomic Factor and consumption etc.) Audit & Uncertainty Assessment Assessment Remote Sensing Hydrological Hydrological Model 1 Models Parameter retrieval & Hydrological Model 2 Risk Model Data assimilation Audit & Uncertainty Geophysical Data Hydrological Model n Vulnerability Assessment Acquisition & Risk Assessment Dissemination & Stakeholder Interaction (Interviews, WebGIS, Website, Focus Groups etc.) ICTP – Workshop, Trieste, 30 April 2015 13
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 km 2 ) 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) ICTP – Workshop, Trieste, 30 April 2015 14
CMs Auditing & Downscaling – main steps ! Downscaled 1km "precMF" (mm/year): Catchment "riumannu" year 1954 900 39.7 850 39.65 800 39.6 750 39.55 700 39.5 650 39.45 600 39.4 550 39.35 500 39.3 450 ! 39.25 ! 8.95 9 9.05 9.1 9.15 9.2 9.25 9.3 9.35 ICTP – Workshop, Trieste, 30 April 2015 15
CLIMB – Structure & Workflow GCM / RCM GCM / RCM GCM / RCM Study Site Characterization 1 2 n Conventional data (soil, DEM, vegetation, water availability Climate Model Socioeconomic Factor Socioeconomic Factor and consumption etc.) Audit & Uncertainty Assessment Assessment Assessment Remote Sensing Hydrological Hydrological Model 1 Models Parameter retrieval & Hydrological Model 2 Risk Model Risk Model Data assimilation Audit & Uncertainty Geophysical Data Hydrological Model n Vulnerability Vulnerability Assessment Acquisition & Risk & Risk Assessment Assessment Dissemination & Stakeholder Interaction (Interviews, WebGIS, Website, Focus Groups etc.) ICTP – Workshop, Trieste, 30 April 2015 16
Hydrological modeling – Some examples: Chiba 20 60 15 R (mm) 40 1971-2000 P (mm) 10 2041-2070 20 5 0 0 Sept Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug ICTP – Workshop, Trieste, 30 April 2015 17
Hydrological modeling – Chiba: Flow duration curve High Mid- Low Flow Dry Conditions Flow Range Moist Conditions Conditions Discharge (m 3 /s) 1971-2000 2041-2070 Flow Exceedence Percentile (Percentage of time that indicated discharge is equated or exceeded) ICTP – Workshop, Trieste, 30 April 2015 18
Hydrological modeling – Rio Mannu: soil water content ICTP – Workshop, Trieste, 30 April 2015 19 � �
Hydrological modeling – Rio Mannu: Max number of consecutive low flow days ICTP – Workshop, Trieste, 30 April 2015 20
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 ICTP – Workshop, Trieste, 30 April 2015 21
Hydrological modeling – Noce: swow water equivalent map ICTP – Workshop, Trieste, 30 April 2015 22 � �
Hydrological modeling – Noce: average of maximum daily flow Sept Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug ICTP – Workshop, Trieste, 30 April 2015 23
Recommend
More recommend
