Awards ceremony of Bando Fondo Rotary Premio alla Ricerca 2015 Fondazione Provinciale della Comunità Comasca

1. Co-adapting water supply and demand to changing climate
in agricultural water management: evidences from a
model-based analysis in Northern Italy
Matteo Giuliani
matteo.giuliani@polimi.it
NRM Polimi

8. Cosa suggeriscono le previsioni
scientifiche?

9. Proiezioni climatiche: incremento delle temperature
Source: IPCC, 2014
Summary
6.0
4.0
2.0
−2.0
0.0
(o
C)
42
32
39
historical
RCP2.6
RCP8.5
Global average surface temperature change(a)
RCP2.6
RCP4.5
RCP6.0
RCP8.5
Mean over
2081–2100
1950 2000 2050 2100
Northern Hemisphere September sea ice extent(b)
10.0
39 (5)

10. Proiezioni climatiche: diminuzione della disponibilita' idrica
Source: Arnell, 2004

11. Proiezioni climatiche: eventi estremi piu' frequenti

12. La dimensione umana del cambiamento globale
Beijing 1977 Beijing 2011
Articles
The Human Footprint
and the Last of the Wild
ERICW. SANDERSON,MALANDINGJAITEH,MARCA. LEVY,KENTH. REDFORD,
ANTOINETTEV.WANNEBO,ANDGILLIANWOOLMER
nGenesis,Godblesseshumanbeingsandbidsusto
takedominionoverthefishin thesea,thebirdsin theair,
andeveryotherlivingthing.Weareentreatedto be fruitful
andmultiply,to filltheearth,andsubdueit (Gen.1:28).The
bad news,and the good news,is thatwe havealmostsuc-
ceeded.
Thereislittledebatein scientificcirclesabouttheimpor-
tanceof humaninfluenceon ecosystems.Accordingto sci-
entists'reports,weappropriateover40%of thenetprimary
productivity(thegreenmaterial)producedonEartheachyear
(Vitouseketal.1986,Rojstaczeretal.2001).Weconsume35%
oftheproductivityoftheoceanicshelf(PaulyandChristensen
1995),and we use 60%of freshwaterrun-off (Postelet al.
1996).Theunprecedentedescalationin bothhumanpopu-
lationandconsumptionin the 20thcenturyhasresultedin
environmentalcrisesneverbeforeencounteredinthehistory
of humankindandtheworld(McNeill2000).E.O.Wilson
(2002) claimsit would now takefour Earthsto meet the
consumptiondemandsof thecurrenthumanpopulation,if
everyhuman consumedat the level of the averageUS in-
habitant.Theinfluenceofhumanbeingsontheplanethasbe-
comeso pervasivethatit ishardto findadultsin anycoun-
trywhohavenotseentheenvironmentaroundthemreduced
innaturalvaluesduringtheirlifetimes-woodlots converted
to agriculture,agriculturallandsconvertedto suburbande-
velopment,suburbandevelopmentconvertedto urbanareas.
The cumulativeeffect of these many local changesis the
globalphenomenonofhumaninfluenceonnature,anewge-
ological epoch some call the "anthropocene"(Steffenand
Tyson2001).Humaninfluenceis arguablythemostimpor-
tantfactoraffectinglifeof allkindsin today'sworld(Lande
1998,Terborgh1999,Pimm2001,UNEP2001).
Yetdespitethebroadconsensusamongbiologistsaboutthe
importanceof humaninfluenceon nature,thisphenomenon
anditsimplicationsarenotfullyappreciatedbythelargerhu-
mancommunity,whichdoesnot recognizethemin itseco-
nomicsystems(Halletal.2001)orinmostof itspoliticalde-
cisions(SoulkandTerborgh1999,Chapinetal.2000).Inpart,
THE HUMANFOOTPRINTISA GLOBAL
MAPOFHUMANINFLUENCEON THE
LANDSURFACE,WHICH SUGGESTSTHAT
HUMANBEINGSARESTEWARDSOF
NATURE,WHETHERWELIKEITORNOT
thislackofappreciationmaybeduetoscientists'propensity
toexpressthemselvesintermslike"appropriationofnetpri-
maryproductivity"or"exponentialpopulationgrowth,"ab-
stractionsthatrequiresometrainingtounderstand.Itmay
beduetohistoricalassumptionsaboutandhabitsinherited
fromtimeswhenhumanbeings,asagroup,haddramatically
lessinfluenceon thebiosphere.Nowtheindividualdeci-
Eric
W.
Sanderson(e-mail:esanderson@wcs.org)is associatedirector,and
GillianWoolmerisprogrammanagerand GISanalyst,in theLandscape
EcologyandGeographicAnalysisProgramat theWildlifeConservationSo-
cietyInstitute,2300SouthernBlvd.,Bronx,NY10460.KentH.Redfordisdi-
rectoroftheinstitute.MalandingJaitehisa researchassociateandGISspe-
cialist,MarcA.Levyisassociatedirectorforscienceapplications,andAntoinette
V Wanneboisseniorstaffassociateat theCenterforInternationalEarthSci-
enceInformationNetwork(CIESIN),ColumbiaUniversity,61Route
9W,
Pal-
isades,NY10964.Sanderson'sresearchinterestsincludeapplicationsofland-
scapeecologyto conservationproblemsand geographicaland historical
contextsfor modernconservationaction;hehasrecentlypublishedscientific
articleson conservationplanningfor landscapespeciesand rangewidecon-
servationprioritiesforthejaguar.Woolmer'sresearchinterestsincludetheap-
plicationofgeographicinformationsystemsandothertechnologiesforfieldand
broad-basedconservationactivities.Redfordhaswrittenextensivelyaboutthe
theoryandpracticeofconservation.Levy,apoliticalscientistwitha background
ininternationalrelationsandpublicpolicy,conductsresearchoninternational
environmentalgovernance,sustainabilityindicators,andenvironment-security
interactions.Jaiteh'sresearchinterestsincludeapplicationsofremotesensing
and geographicinformationsystemstechnologiesin human-environment
interactions,particularlythedynamicsoflanduseandcoverchangeinAfrica.
Wannebo'sresearchinterestsincludedetectinglanduseandlandcoverchanges
usingremotesensing.@2002AmericanInstituteofBiologicalSciences.
October 2002 / Vol.52 No. 10 * BioScience 891
The Human Footp
and the Last of the
ERICW. SANDERSON,MALANDINGJAITEH,MARCA. LEVY,KENTH.
ANTOINETTEV.WANNEBO,ANDGILLIANWOOLMER
nGenesis,Godblesseshumanbeingsandbidsusto
takedominionoverthefishin thesea,thebirdsin theair,
andeveryotherlivingthing.Weareentreatedto be fruitful
andmultiply,to filltheearth,andsubdueit (Gen.1:28).The
bad news,and the good news,is thatwe havealmostsuc-
ceeded.
Thereislittledebatein scientificcirclesabouttheimpor-
THE
MA
LAN
HUM
The Human Footprint
and the Last of the Wild
ERICW. SANDERSON,MALANDINGJAITEH,MARCA. LEVY,KENTH. REDFORD,
ANTOINETTEV.WANNEBO,ANDGILLIANWOOLMER
nGenesis,Godblesseshumanbeingsandbidsusto
takedominionoverthefishin thesea,thebirdsin theair,
andeveryotherlivingthing.Weareentreatedto be fruitful
THE HUMANFOOTPRINTISA GLO
MAPOFHUMANINFLUENCEON T
The Human Footprint
and the Last of the Wild
ERICW. SANDERSON,MALANDINGJAITEH,MARCA. LEVY,KENTH. REDFORD,
ANTOINETTEV.WANNEBO,ANDGILLIANWOOLMER
nGenesis,Godblesseshumanbeingsandbidsusto
takedominionoverthefishin thesea,thebirdsin theair,
andeveryotherlivingthing.Weareentreatedto be fruitful
andmultiply,to filltheearth,andsubdueit (Gen.1:28).The
bad news,and the good news,is thatwe havealmostsuc-
ceeded.
Thereislittledebatein scientificcirclesabouttheimpor-
THE HUMANFOOTPRINTISA GLO
MAPOFHUMANINFLUENCEON TH
LANDSURFACE,WHICH SUGGEST
HUMANBEINGSARESTEWARDSOF

13. Proiezioni demografiche: stabilizzazione improbabile a fine
secolo
Source: Gerland, 2014

14. Proiezioni demografiche: concentrazione della popolazione in
aree urbane
US
246.2
Urban population in millions
81%
Urban percentage
Mexico
84.392
77%
Colombia
34.3
73%
Brazil
162.6
85%
Argentina
35.6
90%
Ukraine
30.9
68%
Russia
103.6
73%
China
559.2Urban population in millions
42%Urban percentage
Turkey
51.1
68%
India
329.3
29%
Bangladesh
38.2
26%
Philippines
55.0
64%
Indonesia
114.1
50%
S Korea
39.0
81%
Japan
84.7
66%
Egypt
33.1
43%
S Africa
28.6
60%
Canada
26.3
Venezuela
26.0
Poland
23.9
Thailand
21.5
Australia
18.3
Netherlands
13.3
Peru
21.0
Saudi Arabia
20.9
Iraq
20.3
Vietnam
23.3
DR Congo
20.2
Algeria
22.0Morocco
19.4
Malaysia
18.1
Burma
16.5
Sudan
16.3
Chile
14.6
N Korea
14.1
Ethiopia
13.0
Uzbekistan
10.1
Tanzania
9.9
Romania
11.6
Ghana
11.3
Syria
10.2
Belgium
10.2
80%
94%
62%
33%
89%
81%
73%
81%
67%
27%
33%
65%
60%
69%
32%
43%
88%
62%
16%
37%
25%
54%
49%
51%
97%
Nigeria
68.6
50%
UK
54.0
90%
France
46.9
77%
Spain
33.6
77%
Italy
39.6
68%
Germany
62.0
75%
Iran
48.4
68%
Pakistan
59.3
36%
Cameroon
Angola
Ecuador
Ivory
Coast
Kazakh-
stan
Cuba
Afghan-
istan
Sweden
Kenya
Czech
Republic
9.5
9.3
8.7
8.6
8.6
8.5
7.8
7.6
7.6
7.4
Mozam-
bique
Hong
Kong
Belarus
Tunisia
Hungary
Greece
Israel
Guate-
mala
Portugal
Yemen
Dominican
Republic
Bolivia
Serbia &
Mont
Switzer-
land
Austria
Bulgaria
Mada-
gascar
Libya
Senegal
Jordan
Zimbabwe
Nepal
Denmark
Mali
Azerbaijan
Singapore
El
Salvador
Zambia
Uganda
Puerto
Rico
Paraguay
UAE
Benin
Norway
New
Zealand
Honduras
Haiti
Nicaragua
Guinea
Finland
Uruguay
Lebanon
Somalia
Sri Lanka
Cambodia
Slovakia
Costa Rica
Palestine
Kuwait
Togo
Chad
Burkina
Ireland
Croatia
Congo
Niger
Sierra Leone
Malawi
Panama
Turkmenistan
Georgia
Lithuania
Liberia
Moldova
Rwanda
Kyrgyzstan
Oman
Armenia
Bosnia
Tajikistan
CAR
Melanesia
Latvia
Mongolia
Albania
Jamaica
Macedonia
Mauritania Laos
Gabon
Botswana
Slovenia
Eritrea
Estonia
Gambia
Burundi
Papua New Guinea
Namibia
Mauritius
Guinea-Bissau
Lesotho E Timor
Bhutan
Swaziland
Trinidad & Tobago
The earth reaches a momentous
milestone: by next year, for the first time
in history, more than half its population
will be living in cities. Those 3.3 billion
people are expected to grow to 5 billion
by 2030 — this unique map of the world
shows where those people live now
At the beginning of the 20th
century, the world's urban
population was only 220
million, mainly in the west
By 2030, the towns and
cities of the developing
world will make up 80%
of urban humanity
The new urban world
Urban growth, 2005—2010
Predominantly urban
75% or over
Predominantly urban
50—74%
Predominantly rural
25—49% urban
Predominantly rural
0—24% urban
Cities over 10 million people
(greater urban area)
Key
Tokyo
33.4
Osaka
16.6
Seoul
23.2
Manila
15.4
Jakarta
14.9
Dacca
13.8
Bombay
21.3
Delhi
21.1 Calcutta
15.5
Karachi
14.8
Shanghai
17.3
Canton
14.5
Beijing
12.7
Moscow
13.4
Tehran
12.1
Cairo
15.9
Istanbul
11.7
London
12.0
Lagos
10.0
Mexico
City
22.1
New York
21.8
Sao Paulo
20.4
LA
17.9
Rio de
Janeiro
12.2
Buenos
Aires
13.5
3,307,950,000The world’s urban population — from a total of 6,615.9 million SOURCE: UNFPA GRAPHIC: PAUL SCRUTONAfrica Asia Oceania Europe
0.1%
Eastern Europe
-0.4%
Arab States
Latin America
& Caribbean North America
3.2%
2.4%
1.3%
2.8%
1.7%
1.3%

15. Quanto lontane nel tempo sono
queste previsioni?

16. Cambiamenti osservati: riduzione dei poli

17. Cambiamenti osservati: scioglimento dei ghiacciai
Pederse Glacier, Alaska
1917 2005

18. Cambiamenti osservati: espansione dell'agricoltura
Cairo, Egypt
1972 2003

19. Cambiamenti osservati: sovrasfruttamento delle risorse disponibili
Lake Urmia, Iran
2000 2010 2014

20. Coupled Human Natural Systems
timePRESENT
natural system human system
exogenous drivers

21. Coupled Human Natural Systems
timePRESENT FUTURE
natural system human system
exogenous drivers
SPM
Summary for Policymakers
Figure SPM.7 | CMIP5 multi-model simulated time series from 1950 to 2100 for (a) change in global annual mean surface temperature relative to
1986–2005, (b) Northern Hemisphere September sea ice extent (5-year running mean), and (c) global mean ocean surface pH. Time series of projections
and a measure of uncertainty (shading) are shown for scenarios RCP2.6 (blue) and RCP8.5 (red). Black (grey shading) is the modelled historical evolution
using historical reconstructed forcings. The mean and associated uncertainties averaged over 2081−2100 are given for all RCP scenarios as colored verti-
cal bars. The numbers of CMIP5 models used to calculate the multi-model mean is indicated. For sea ice extent (b), the projected mean and uncertainty
(minimum-maximum range) of the subset of models that most closely reproduce the climatological mean state and 1979 to 2012 trend of the Arctic sea
6.0
4.0
2.0
−2.0
0.0
(o
C)
42
32
39
historical
RCP2.6
RCP8.5
Global average surface temperature change(a)
RCP2.6
RCP4.5
RCP6.0
RCP8.5
Mean over
2081–2100
1950 2000 2050 2100
Northern Hemisphere September sea ice extent(b)
RCP2.6
RCP4.5
RCP6.0
RCP8.5
1950 2000 2050 2100
10.0
8.0
6.0
4.0
2.0
0.0
(106
km2
)
29 (3)
37 (5)
39 (5)
1950 2000 2050 2100
8.2
8.0
7.8
7.6
(pHunit) 12
9
10
Global ocean surface pH(c)
RCP2.6
RCP4.5
RCP6.0
RCP8.5
Year
natural system human system
exogenous drivers

22. Il sistema del Lago di Como

23. Matteo Giuliani
Il sistema del Lago di Como
Area del bacino = 4,500 km2
Capacita' di invaso attiva = 254 Mm3
Capacita' serbatoi alpini = 515 Mm3
Area agricola = 1400 km2
elevation
in [m]
8
4000
0 5 10 20 30 km
Como
Milano
Lake
Como
Adda
River
Muzza
irrigation
district

24. Regime idrologico
snowwaterequivalent(Mm)3
0
500
1000
waterflows(m/s)3
400
200
0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
inflow
snow water equivalent
estimated by ARPA
water
demand
snow-dominated
spring peak rain-dominated
fall peak
water deficit

25. Observed trends
0 50 100 150 200 250 300 350
50
100
150
200
250
300Averagednetinflowrate[m3
/s]
[ 1946 - 1966 ] [ 1990 - 2010 ]
reduction of
summer flow

26. Matteo Giuliani
elevation
in [m]
8
4000
0 5 10 20 30 km
Como
Milano
Lake
Como
Adda
River
Muzza
irrigation
district
Principali interessi
Irrigation supply
Flood control in Como

27. Modello integrato del sistema
Lake Como
Upstream catchment
Adda River and main
irrigation canals
Muzza agricultural
district

28. Modello integrato del sistema
Decisions of Lake
Como operator
Decisions of Farmers
Lake Como
Upstream catchment
Adda River and main
irrigation canals
Muzza agricultural
district

29. Opzioni di adattamento
Decisions of Lake
Como operator
Decisions of Farmers
Lake Como
Upstream catchment
Adda River and main
irrigation canals
Muzza agricultural
district
• Baseline = situazione attuale (no coordinamento)
• Unilateral adaptation (demand) = solo modifica scelta colture
• Unilateral adaptation (supply) = solo modifica regolazione lago
• Co-adaptation = modifica colture con conseguente rinnovo licenze e modifica regolazione lago

30. Opzioni di adattamento
Decisions of Lake
Como operator
Decisions of Farmers
Lake Como
Upstream catchment
Adda River and main
irrigation canals
Muzza agricultural
district
• Baseline = situazione attuale (no coordinamento)
• Unilateral adaptation (demand) = solo modifica scelta colture
• Unilateral adaptation (supply) = solo modifica regolazione lago
• Co-adaptation = modifica colture con conseguente rinnovo licenze e modifica regolazione lago

31. Opzioni di adattamento
Decisions of Lake
Como operator
Decisions of Farmers
Lake Como
Upstream catchment
Adda River and main
irrigation canals
Muzza agricultural
district
• Baseline = situazione attuale (no coordinamento)
• Unilateral adaptation (demand) = solo modifica scelta colture
• Unilateral adaptation (supply) = solo modifica regolazione lago
• Co-adaptation = modifica colture con conseguente rinnovo licenze e modifica regolazione lago

32. Opzioni di adattamento
Decisions of Lake
Como operator
Decisions of Farmers
Lake Como
Upstream catchment
Adda River and main
irrigation canals
Muzza agricultural
district
• Baseline = situazione attuale (no coordinamento)
• Unilateral adaptation (demand) = solo modifica scelta colture
• Unilateral adaptation (supply) = solo modifica regolazione lago
• Co-adaptation = modifica colture con conseguente rinnovo licenze e modifica regolazione lago

33. Risultati

34. Validazione del modello: operatore del lago
0
1
2
3
lakelevel[m]
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
0
200
400
600
800
lakerelease[m3
/s]
historical observation
model simulation
historical observation
model simulation
flooding threshold
water demand

35. Validazione del modello: scelte dei contadini

36. coadaptation
baseline
Il valore del co-adattamento: produttivita' dell'acqua in condizioni
attuali
+59%limited
improvement

37. Afflussi futuri in condizioni di cambiamento climatico
panel (b)
2001
2002
2003
2004
2005
50
100
150
200
250
300
350
400
450
500
550
scenario
1
scenario
2
scenario
3
scenario
4
scenario
5
inflow
[m3
/s]
crop growing period
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

38. baseline
unilateral adaptation (demand)
coadaptation
unilateral adaptation (supply)
panel (b)
2001
2002
2003
2004
2005
50
100
150
200
250
300
350
400
450
500
550
scenario
1
scenario
2
scenario
3
scenario
4
scenario
5
inflow
[m3
/s]
crop growing period
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Il valore del co-adattamento: profitto dei contadini in condizioni
di cambiamento climatico
coadaptation
+10M€ /y
wrt baseline

39. Conclusioni
• Gli effetti dei cambiamenti climatici sono gia' visibili nei nostri sistemi e richiedono lo studio e
l'implementazione di strategie di adattamento a tale cambiamento
• Abbiamo bisogno di modelli di simulazione avanzati che descrivano la componente naturale e
quella umana per rappresentare la situazione attuale e fornire proiezioni credibili sulla
evoluzione futura del sistema
• Meccanismi di coordinamento rappresentano opzioni di adattamento efficaci per mitigare
potenziali impatti negativi dei cambiamenti climatici

40. Ricerche future
SOft path WATer management adaptation to CHanging climate
DAFNE1
: A Decision-Analytic Framework to explore the water-e
NExus in complex and transboundary water resources systems of
Decision-Analytic Framework to explore
water-energy-food NExus in complex and transboundary
water resources systems of fast growing countries
: Rozwojowa 79, 05-300 Mińsk Mazowiecki, Poland
us times: http://warszawa.jakdojade.pl/?locale=en
For more info:
riverpiotr@gmail.com
i.r.dodkins@swansea.ac.uk
Adaptive Management of Barriers in European Rivers
Optional Excursions:
4th
July: Biebrza River Val
7th
July: AMBER case stud
controversial Vistula River
(notify riverpiotr@gmail.c
interested, before end of M
At Hotel Ekwos (right),
Mińsk Mazowiecki, Poland.
Reservations:
Email: ekwos@ekwos.com.pl
(write AMBER in subject)
€27 single room
€35 double (2 people)
€42 triple
Includes breakfast
10 ha of land with small pond, spo
facilities (tennis courts, beach ball,
volleyball), fitness room, sauna and
outside jacuzzi. Nearby woodland
Optional Excursions:
4th
July: Biebrza River Valley Dam
7th
July: AMBER case study;
controversial Vistula River Dam
(notify riverpiotr@gmail.com if yo
interested, before end of May)
Adaptive M
E
At Hotel Ekwos (right),
Mińsk Mazowiecki, Poland.
Reservations:
Email: ekwos@ekwos.com.pl
(write AMBER in subject)
€27 single room
€35 double (2 people)
€42 triple
Includes breakfast
10 ha of land with small pond, sport
facilities (tennis courts, beach ball,
volleyball), fitness room, sauna and
outside jacuzzi. Nearby woodland
Optional Excursions:
4th
July: Biebrza River Valley Dam
7th
July: AMBER case study;
controversial Vistula River Dam
(notify riverpiotr@gmail.com if you are
interested, before end of May)
Travel by air
From Modlin (Warsaw) airport, a bus to a railway station
and train to Wschodnia (eastern) station. Trains are cash
only.
http://en.modlinairport.pl/modlin-en-
new/web/passenger/access/koleje-mazowieckie-
trains.html.
From Chopin Airport easier - train is accessible direct from
the building and goes to Wschodnia (every 30 minutes).
From Wschodnia station catch train to Mińsk Mazowiecki
(MM)
From MM station phone hotel reception for special rate
taxi +48 25 752 54 10
(We are also proposing to arrange shuttle from MM at
around 14:20 and 16:20 on 5th).
by GPS: Rozwojowa 79, 05-300 Mińsk Mazowiecki, Poland
train/bus times: http://warszawa.jakdojade.pl/?locale=en
Main objectives:
integration of activities to ensure efficient deliverables
distribution of project reference documents
European Rivers
start 18:00 hrs on 5
th
- finish 11:00 hrs on 7
th
For more info:
riverpiotr@gmail.com
i.r.dodkins@swansea.ac.uk
gestione della risorsa idrica
www.fondazionecariplo.it
COMUNITÀBENESSERE GIOVANI
Improve our forecasting capability of hydrological extremes for
multiple economic sectors, including hydropower and farmers

41. thank you
ACKNOWLEDGEMENTS:
@MxgTeo
@NRMPolimi
http://giuliani.faculty.polimi.it
www.nrm.deib.polimi.itYu Li Andrea Castelletti Claudio Gandolfi
Matteo Giuliani
matteo.giuliani@polimi.it