This is the talk given by Giuliano di Baldassarre at the Summer School on Hydrological Modeling kept in Cagliari this here. The topic is very up-to-date and important. He presented an analysis of a few case studies and suggested some literature.

1. Giuliano Di Baldassarre
Uppsala University, Uppsala, Sweden
Centre for Natural Disaster Science, Uppsala, Sweden
UNESCO-IHE Institute for Water Education, Delft, Netherlands
Hydrological Extremes and Human Societies
Cagliari University, July 2017
Visiting Professor Programme

2. WE (HUMANS) ARE UNFAIR.

3. History

4. History
• Early 1960s, Italy
• Construction of the Vajont Dam (280m)

5. Vajont dam disaster
• 9 October 1963 at 22:39
• Landslide into this “brand new” hydroelectric reservoir
• Giant wave

6. Dam
Flood wave
(source: Alberto Viglione, 2012)

7. Vajont dam disaster
• 9 October 1963 at 22:39
• Giant wave raised by a landslide into this “brand new”
hydroelectric reservoir
• The wave affected five towns, killing 1918 people
Longarone (BEFORE 9 October 1963) Longarone (AFTER 9 October 1963)

8. An alternative story

9. • Late 1950s, Italy
• Roberto Camorani, Minister of Public Works
An alternative story

10. • Following the advices of some concerned geologists,
Camorani did NOT authorize the Vajont dam construction
• The Vajont dam disaster did NOT happen
An alternative story
Longarone (BEFORE 9 October 1963) Longarone (AFTER 9 October 1963)

11. An alternative story
• Would the strictness of Roberto Camorani be appreciated?
• Would he be rewarded for avoiding the Vajont disaster?
• Would History actually remember him?
*DISCLAIMER: Roberto Camorani is a fictious name.
The picture of this presentation is of Friedrich August von Hayek, economist and philosopher (Nobel Price, 1974)

12. “everybody knows that you need more prevention than treatment,
but few reward acts of prevention”
N.N. Taleb (2007)

13. This module:
Mutual shaping of
hydrology and society

14. Panta Rhei: Everything flows
IAHS scientific decade (2013-2022)
Over 400 water scientists
This module:
Mutual shaping of
hydrology and society

15. • Introduction
o Human influence and response to hydrological extremes (drought and floods)
• Empirical and theoretical research
o Human-flood interactions
o Human-drought interactions
o Droughts and floods in the Anthropocene
• Case studies
o Vajont, Bangladesh and Rome
This module

16. Introduction
Human influence and response

17. Today: over 100 million people affected per year, more than 25,000 fatalities
and annual economic damages above 15 billion US dollars (UN-ISDR)
Near future: fatalities and economic losses are expected to increase
Risk management: understand past changes and project future trajectories
to reduce negative impacts, while maintaining ecological benefits
Hydrological extremes:
droughts and floods

18. Humans alter frequency, magnitude and distribution of hydrological extremes
• Deliberately (water management): dams and reservoirs, levees, etc.
• Not deliberately (land use): urbanization, deforestation, etc.
• Numerous hydrological studies
Human influence

19. (Kareiva et al., Science, 2007; Savenjie et al., Hydrology and Earth System Sciences, 2014)
• Most river basins are rapidly changing
• Human activities alter the hydrological regime
Human influence

20. Increasing degree of regulation
Dams and reservoirs

21. (Liu et al., Water, 2014)
Urbanization and floods

22. Human response
Hydrological extremes (in turn) trigger demographic and institutional change
• Individuals, communities, institutions
• Informal (spontaneous processes) or formal (disaster risk reduction)
• Numerous socio-economic studies

23. Human response
Los Angeles: Drought and water demand (Garcia et al., HESS, 2016)
1976–1977 1987–1992 (longer drought, persistent impact)

24. Society shapes hydrological extremes,
while (at the same time) hydrological extremes shape society
Mutual shaping
(Di Baldassarre et al., Earth System Dynaics, 2017)
Climate influences
outside the system
Human influences
outside the system
Hydrological extremes
(frequency, magnitude,
spatial distribution)
Society
(demography,
institution, governance)
Impacts and perceptions
Policies and measures
River basins, floodplains or cities as human-water systems

25. Open questions
How do human-water interactions shape wealth and recovery trajectories?
Wealth
Time
Bouncing back
disaster
Wealth
Time
Bouncing forward
disaster
(Di Baldassarre et al., in preparation)
Wealth
Time
Collapsing
disaster

26. Human-flood interactions

27. Levee effect
Levee building
(less frequent floods)
• Unintended consequences: Risk can increase after raising protection levels!
• Levee paradox, already described by G. White in 1940s
• Self-reinforcing feedback (tends to lock-in)
RIVER FLOODPLAIN
rare-but-catastrophic
disasters

28. Levee/forgetting effect
Rare events associated to increasing vulnerability
Example: Rome, Italy
(Di Baldassarre et al., Advances in Geoscience, 2016)
0
200,000
400,000
600,000
1860 1890 1920 1950 1980 2010
Floodplainpopulation
Levees
1870Flooding

29. (Di Baldassarre et al., Earth System Dynamics, 2017)
Adaptation/learning effect
Frequent events associated to decreasing vulnerability
Example: Bangladesh
1
10
100
1000
1970 1980 1990 2000 2010
Fatalitiesbyfloodedarea

30. Dynamics around the world
(Examples from Kates et al., PNAS, 2006; Wind et al., WRR, 1999; Bohensky et al., 2014; Penning-Rowsell, GR, 1996)
Levee effect
Rare events associated with increasing vulnerability
Adaptation effect
Frequent events associated with decreasing vulnerability

31. • Traditional methods cannot capture these dynamics
• Unrealistic interpretation of past changes and future projections
o Less frequent events don’t necessarily lower risk, e.g. levee effect
o Unintended consequences, e.g. protection paradox and lock-in
New methods accounting for the mutual shaping of hydrology and society
based on interdisciplinary frameworks (e.g. social-ecological systems,
ecological economics, environmental history and socio-hydrology)
Flood risk assessment
time
Extreme events
Societies
risk
Currentapproach
…scenarios
CLIMATE
DEVELOPMENT
Extreme events
Societies
…dynamics
Novelapproach
feedback
CLIMATE
DEVELOPMENT
time
(Di Baldassarre et al., Water Resources Research, 2015)

32. After flooding events, societies build “flood memory”
and respond via:
(a) Non-structural measures (e.g. resettlement)
(b) Structural measures (e.g. levees)
Structural measures (in turn) change
the frequency and magnitude of flooding
Green system
Technical system
Human-flood interactions:
Hypotheses

33. Key concept: Flood memory
• Built after flood events, proportional to losses
• Memory decays over time
(Anastasio et al., 2014; Hanak et al., 2011)
20
40
60
80
100
0 10 20 30 40 50
Percentageretained(%)
Retention interval (years)
Human forgetting data
0,50
0,75
1,00
1,25
1,50
1996 1998 2000 2002 2004 2006 2008
Policiespercapita(%)
Calendar year
California's flood insurance coverage
1997
Flood

34. Conceptualizing
human-flood interactions
Human and flood systems are interlinked and gradually co-evolve
while being abruptly altered by the occurrence of flood events
• Focus on interactions and feedbacks between floods and societies

35. F = flood losses
W = high water level
H = levee height
1. Flooding
• Protection measures change flood levels, and avoid smaller events
• Higher water levels lead to higher flood losses
Empirical studies
Our model
Actual water level
Po River
(Jongman et al., 2012; Di Baldassarre et al., 2009; Heine & Pinter, 2012)
Flood depth
Relativelosses(0-1)

36. 2. Demography
• Floodplain population tends to increase over time
• It decreases after events, but growth resumes as memory decays
Empirical studies
Our model
F = flood losses
D = population density
M = social memory
(Di Baldassarre et al., 2013; Collenteur et al., 2015)
4000
5000
6000
7000
8000
9000
10000
11000
1870 1910 1950 1990
Floodplainpopulation
Calendar year
Occhiobello, Italy
1951
Flood

37. 3. Memory
• Memory is built after events, proportional to flood losses
• Memory decays over time
Empirical studies
Our model
F = flood losses
D = population density
M = social memory
(Hanak, 2011; Anastasio et al., 2014)
0,50
0,75
1,00
1,25
1,50
1996 1998 2000 2002 2004 2006 2008
Policiespercapita(%)
Calendar year
California's flood insurance coverage1997
Flood

38. 4. Technology
• Flood protection level is updated after major events
• Protection measures decay over time
Empirical studies
Our model
( )
0=
-+= --
R
HHWR HT xe
Actual water level
Adige River
(Da Deppo & Datei, 1997; Di Baldassarre et al., 2013)
R = levee heightening
H = levee height

39. Flood system
Human system
F = flood losses
W = high water level
H = levee height
D = population density
R = levee heightening
M = flood memory
Modeling
human-flood interactions
(Di Baldassarre et al., Water Resources Research, 2015)

40. Numerical experiment
to explore plausible trajectories in case of
increasing flood levels
e.g. climate change or sea level rise
Comparison between:
• Green system
• Technical system
Increasing flood levels
Green system
Technical system

41. Results
Capture emerging patterns
• Memory as a primary
mechanism
• Suggest data needs
• Make tests and re-iterate
(Di Baldassarre et al., WRR, 2015)
Green system
Technical system

42. Results 2/2
Diagrams show outcomes
with decreasing memory
decay rate
Keeping memory high is
crucial, especially in
technical systems

43. Model evaluation
(Ciullo et al.,Hydrological Sciences Journal, 2017)

44. e.g. uncertainty due to differences in sequence of floods only
0 1000 2000 yrs
Log(wealth)
Probability
Initial
condition
Bimodal distribution
(Viglione et al., Journal of Hydrology, 2014)
Models as hypotheses
Not predictions!

45. Case studies

47. The River Tiber
and the Foundation of Rome
About 2,700 years ago, the King of Alba Longa, Amalius, abandoned to die the
newborn twins Romulus and Remus in the Tiber river
Luckily, flooding occurred at the same time and Amalius did not manage to
abandon them in the main river channel
Instead, he had to abandon them in the calmer waters of the floodplain
A she-wolf (“lupa”) rescued (and breastfed) the twins
Some years after, Romulus and Remo founded the city of Rome
Romulus was the first King of Rome
This is a myth, but it shows the long
“love-hate relationship of Rome and the Tiber”
(Aldrete, 2007)

48. Rome and the Tiber:
over centuries
• The ancient Rome mostly developed on (seven) hills
• Tiber’s floodplain was mainly exploited for agricultural purposes
• Small communities settled in the riparian areas of the Tiber, but they had a
peaceful relationships with the frequent occurrence of flooding events
• Over centuries, flood events have been part of the history of Rome and its
relationship with the Tiber river
• Inundation risk influenced the city's landscape development
Number of flooding events in Rome (over 25 centuries!)
(Aldrete, 2007)

49. Rome and the Tiber:
today
• Nowadays, more than 600,000 people live in the Tiber’s floodplain, often
unaware of their exposure to potentially catastrophic flooding
(Academy Award’s winning movie “The Great Beauty”, Sorrentino, 2013)

50. Tiber’s floodplain as fully coupled human-water system
(McDonald, 1997; Di Baldassarre, HESS, 2015)
Socio-hydrological dynamics in Rome
hydrological processes
(flood changes)
human interventions
(policies, structures)
human experience
(memory, learning)
socio-economic processes
(population changes)

51. Observations
hydrological processes
(flood changes)
human interventions
(policies, structures)
human experience
(memory, learning)
socio-economic processes
(population changes)
Social information
• People’s “relationship” with
the river and flooding
• Historical studies
Demographic data
• Urbanization and land-use
• Official census by districts
Hydrological data
• Number of flooding events
• High water marks
• Maximum water levels
Policy information
• Engineering works
• Building policies

52. Turning or tipping point?
1870: Rome experiences a large flooding event
1871: Rome becomes Italy’s Capital

53. Flood defence:
the walls (”muraglioni”)
• Discussion on possible options to mitigate flooding in Rome
• Garibaldi was for a flood-relief channel
• Following examples of other European capitals, such as London and Paris,
embankments/walls were designed and built
• Walls’ level at 18,45 m a.s.l. (1870’s maximum flood level was 17,22 m a.s.l.)
• The walls were built at the end of the century
• Rome and its relationship with the Tiber river were significantly transformed

54. Flood defence:
the walls (”muraglioni”)
(Raccolta Roma Sparita; Sacca et al., 2015)

55. Floodplain development
Many modern districts were created in the Tiber’s floodplain:
e.g. Prati in 1887 and 1934

56. Flood levels
Level of flood protection
Floodplain population
Shift from frequent flooding (3-6 inundation events per century)
to rare (1-in-200 years?), but potentially catastrophic events (“levee effect”)
Data analysis

57. • Is Rome safe from flooding now? (as, for instance, Wikipedia suggests!)
• Last (big) flooding was in 1870, Rome is mainly perceived as “flood-proof”
Historical analysis helps raise risk awareness
e.g. levels of flood protection is 18.45m, which is above 1870 flood levels (17.22m),
but below the maximum historical level of 1598 (19.56m)!
Map of flood extent in 1870 (green) and 1598 (blue)
Is Rome safe from flooding?

59. Bangladesh: flows of water and people
• Bangladeshi cities are rapidly growing, economies expanding
• People continuously move to cope with hydrological changes, such as salt
water intrusion, river erosion and flooding events
• Videos…
Giuliano Di Baldassarre, Kun Yan, Luigia Brandimarte and Md Ruknul Ferdous. IAHS Bologna 2014

60. Bangladesh: Salt water intrusion
• Gridded Population of the World (1990-2000, 2000-2010)
• Population change (%)
• Migration from Southwest region –why?

61. Southwest region

62. Current narratives
Flooding
Cyclones
Saline intrusion
Migration
Conflicts
Climate change
Sea level rise
(IPCC, 2007; Reuveny, Political Geography, 2007; World Bank and UN reports)
0
3
6
9
12
15
18
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
SalinityHW(ppt)
Yearly maximum salinity at Khulna
3,0%
3,5%
4,0%
4,5%
5,0%
5,5%
6,0%
1881 1901 1921 1941 1961 1981 2001
RatioofPopulatiom
Years
Ratio of Population (Study area vs Bangladesh)

63. Human activities, upstream
• Farakka Barrage at Ganges River in India, since 1974
0
500
1 000
1 500
2 000
2 500
3 000
1930 1950 1970 1990 2010
Discharge(m3/s)
Years
Minimum Discharge at Hardinge Bridge
0
3
6
9
12
15
18
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
SalinityHW(ppt)
Yearly maximum salinity at Khulna

64. Human activities, SW region
• Polders (1960-1970)
India
-0,5
0,5
1,5
2,5
3,5
4,5
1940 1950 1960 1970 1980 1990 2000 2010 2020
WaterLevel(mPWD)
Water Level of Rupsa-Pussur at Khulna
Polder crest level
-1,5
-0,5
0,5
1,5
2,5
3,5
4,5
1960 1970 1980 1990 2000 2010
WaterLevel(mPWD)
Water Level of Rupsa-Pussur at Mongla
High water level
Low water level
Polder crest level
High water level
Low water level
Increased
3 mm/yr

65. Human experience and migration
• Census data (Ruknul Ferdous, 2014)
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
1,0
Migratedpopulation
Millions
Parmanent net migration from the Khulna Division
Data
missing

66. Survey, interviews
2%
22%
33%
43%
0%
10%
20%
30%
40%
50%
18-30 31-45 46-60 > 60
Numberofhouseholds
Age Groups
9
4
2
1
16
6
3
9
25
21
13
9
7
75
0 10 20 30 40 50 60 70 80
Businessman
Service holder
Rural Doctor
Labor
Others
Fisherman (Rivers)
Fisherman (Rivers and sea)
Fisherman
Medium Farmer (land 2.5 -7.49 acres)
Small Farmer (land 0.5 -2.49 acres)
Landless Farmer
Marginal Farmer (land 0.05 -0.49 acres)
Large Farmer (land > 7.5 acres)
Farmer
House hold numbers

67. Results
• Do people perceive hydrological changes? How?
• Do people move? Where do they move? And why?
– Migration is not a more response, but a way to cope with changes
– Most time is about temporary, seasonal, or short-term movement
– Permanent migration is rare
(see also Penning-Rowsell et al., ESP, 2012)
2
22
41
65
3
5
10
17
35
0 20 40 60 80
Due to salinity
Lost everything in cyclones
Lost everything in floods
Bio-physical and hydrological
After 1971 war
Political reasons
Looking for better opportunities
Hindu-Muslim conflict
Social, political and environmental
% of people migated
Reasons for the migration
86,2%
94,2% 97,9%
13,8%
5,8% 2,1%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Khulna Bagerhat Satkhira
Migration from the Districts
Living within the district Parmanent migrants
Permanent
Permanent
Permanent

68. Discussion
Need to go beyond current narratives
• Human activities matter
• Societal dynamics, not a mere response
• Socio-hydrology
– Societies shape physical processes
(human activities)
– Physical processes shape societies
(human experience)
Flooding
Cyclones
Saline intrusion
Migration
Conflicts
Climate change
Sea level rise

69. Conclusions and perspectives
• Need to understand the interplay between changes in hydrology and society
to explain the emerging dynamics
Flooding
Cyclones
Saline intrusion
human activities
(policies, structures)
human experience
(damage, memory)
Wealth
Migration
Conflicts
Climate change
Sea level rise
Other drivers
of societal
changes

70. Human-drought interactions

71. Nile River
Example: the Nile River Basin
• World’s longest river (6670 km)
• Basin covers about 10% of Africa
• 11 African countries
• River flow from Ethiopia (Blue Nile)
and Lake Victoria (White Nile)

72. Hydrology of the Nile
Ancient Egyptian civilization
River flows vital to
Egyptian agriculture (nutrients, fertility)
The hydrological behavior of the Nile river led to
one of the first scientific questions
Thales of Miletus (624-546 BC)
tried to understand
the “hydrological paradox” of the Nile
Why does flooding occur in summer
when it does not rain in Egypt?

73. Hydrological data
Nilometers:
River gauge stations along the Nile river in Egypt
measuring river flows (i.e. water depth)
Nile flows to determine the levels of tax to be paid
10
12
14
16
18
20
Abundance
Security
Happiness
Suffering
Hunger
Disaster
NILOMETERREADINGINELLS
1ELL=1.1m
(floods)(droughts)
(Eagleson et al., 1991)

74. Future water availability: part of the mystique of the
Ancient Egyptian priesthood
Predictions based on observations
(no runoff models at that time!)
Example: Roda Nilometer (near Cairo)
Annual minimum flows from 700 to 800 AD
Linear regression (red line) > Negative trend
800
1000
1200
1400
1600
700 710 720 730 740 750 760 770 780 790 800
Year
Minimumflow(m
3
s
-1
)
Drought predictions

75. Drought predictions
800
1000
1200
1400
1600
700 710 720 730 740 750 760 770 780 790 800
Year
Minimumflow(m
3
s
-1
)
?
Let’s assume we are in the 800AD. What would you predict?
A) Minimum flows will stabilize at the level of 800AD
B) Minimum flows will further drop (even more droughts)
C) Minimum flows will rise (less droughts)

76. “Prediction is very difficult,
especially about the future!”
Niels Bohr (1885-1962)

77. Roda Nilometer
One of the longest time series of hydrological data
Annual minimum flows from 622 AD to 1284 AD
25-year moving average (red line)
Climate Variability
800
1000
1200
1400
1600
622 722 822 922 1022 1122 1222
Year
Minimumflow(m
3
s
-1
)
700-800
(Di Baldassarre et al., Hydrological Sciences Journal, 2011)
Roda Nilometer, full series

78. meteorological
drought
soil moisture
drought
hydrological
drought
climate
variabilitydrivers
consequences ecological impacts
socio-economic
impacts
Human-drought interactions
(Van Loon et al., Nature Geoscience, 2016)

79. meteorological
drought
soil moisture
drought
hydrological
drought
climate
variability
human
activitiesdrivers
consequences
land use
irrigation
dam building
water abstraction
ecological impacts
socio-economic
impacts
responses
anthropogenic
climate change
(Van Loon et al., Nature Geoscience, 2016)
Human-drought interactions

80. Dams and reservoirs
• Water shortages: Supply-below-demand events
• Reservoirs’ intended benefits: Secure water supply
• More than 50% in GRaND database
(Source: Jim Wilson/The New York Times, Hoover Dam in Colorado)

81. Dams and reservoirs
• Unintended consequences
• Supply-demand cycle
• Reservoir effect

82. River basins as human-water systems
• Intended benefits (short term)
• Unintended consequences (medium-long term)
Our hypothesis
Water
Shortage
Economic
Losses
Public
Pressure
Reservoir
Storage
Water
Supply
Water
Demand
Agricultural, industrial
or urban expansion
VulnerabilityDependency
+
+
+
+
+
+
+
_
+
+
+
Intended Benefits
Supply-Demand Cycle
Reservoir effect

83. (Kallis, Ecological Economics, 2007)
Supply-demand cycle
• Increasing water supply generates (per se) increasing water demand
• In the medium-long term this can offset the initial benefits of reservoirs
Example: Athens, Greece
• Spiral of increasing supply and demand (co-evolution)
time
1940
Population
1.1 million
1961
Population
1.8 million
1981
Population
3 million
1971
Population
2.5 million
1931
Completion of
Marathon dam
1941
Water
shortage
1951
Repeated
Water shortages
1958
Completion of
Iliki aqueduct
1944
Proposal for
Lake Iliki transfer
1954
Decision for
Lake Iliki transfer
1968
Decision for
Mornos project
1974
Water system
bought back by State
1980
Completion of
Mornos dam
1990-1992
Repeated
Water shortages
1941
German occupation
1949
End of Civil War
1967
Military dictatorship
1974
Democracy
1989-1991
Repetitive elections

84. Global analysis
Reservoir capacity vs. water demand (worldwide)
• GRanD database
• World Bank
(GRanD database; Lehner et al. 2012)

85. Global analysis
Reservoir capacity vs. water demand (worldwide)
• 1960s and 70s: Faster growth in reservoir capacity
• From 1980s: Faster growth in water demand (likely more shortages)
0,5
1,0
1,5
2,0
2,5
1960 1970 1980 1990 2000 2010
NormalizedValues
Reservoir Capacity
Water Demand

86. River basins as human-water systems
• Intended benefits (short term)
• Unintended consequences (medium-long term)
Our hypothesis
Water
Shortage
Economic
Losses
Public
Pressure
Reservoir
Storage
Water
Supply
Water
Demand
Agricultural, industrial
or urban expansion
VulnerabilityDependency
+
+
+
+
+
+
+
_
+
+
+
Intended Benefits
Supply-Demand Cycle
Reservoir effect

87. Reservoir effect
From frequent events to rare-but-catastrophic disasters
Example: Maja collapse
• Additional storage of water brought benefits and allowed agricultural growth,
but increased dependence on water making people more vulnerable
• Prolonged drought conditions as a plausible hypothesis for collapse
(Aimers & Hodell, Nature, 2011; Lucero, Am Anthropol, 2002; Kuil et al., WRR, 2016)

88. Counterargument?
Frequent shortages might erode local resilience
• Systems under frequent stress might get closer and closer to a tipping point,
and potentially catastrophic shifts
(Rockström, 2003; Proença and Fernández-Manjarrés, 2015)
What are the circumstances in which
these two opposite dynamics emerge?

89. Drought and Floods in the
Anthropocene

90. Drought and floods
in the Anthropocene
Hydrological change triggered by social change, and vice versa
• Empirical and theoretical research
• Social, engineering and natural sciences
• Both flood and drought events (why both?)
Climate influences
outside the system
Human influences
outside the system
Hydrological extremes
(frequency, magnitude,
spatial distribution)
Society
(demography,
institution, governance)
Impacts and perceptions
Policies and measures
River basins, floodplains or cities as human-water systems
(Di Baldassarre et al., Earth System Dynamics, 2017)

91. Flood trends
(Di Baldassarre et al., Geophysical Research Letters, 2010)
0
3000
6000
9000
12000
15000
1950-1969 1970-1989 1990-2009
Floodfatalities
Population growth as main driver of increasing flood losses and fatalities in Africa,
while climate change has so far played a smaller role

92. (Winsemius et al., Nature Climate Change, 2016; Di Baldassarre et al., Earth System Dynamics, 2017)
Longer or more severe drought conditions, might have triggered the tendency to
increase river proximity and therefore made more people exposed to flooding
(hypothesis, still to be tested)
What about drought?
0
3000
6000
9000
12000
15000
1950-1969 1970-1989 1990-2009
Floodfatalities

93. (Di Baldassarre et al., Earth System Dynamics, 2017)
Sequence effect
Response to drought exacerbates the impact of floods (and vice versa)
Example: Brisbane, Australia
• Flood retention reservoir built upstream Brisbane in the 1970s
• Prolonged multi-year drought period, Millennium Drought (2001-2010)
• Reservoir operation rules changed to mitigate drought conditions
• Not “optimal" to mitigate the 2011 flood, which was devastating

94. Daniel Kahneman (Nobel Prize, 2002)
o Humans are NOT rational 
o Prospect theory
o Cognitive biases and heuristics
• Confirmation bias
• Anchoring effect
• Availability heuristic
Cognitive biases and heuristics

95. • Theoretical background
o Decision makers estimate probabilities not only on robust evidence,
but also “by the ease with which relevant instances come to mind”
o Availability heuristic (Tversky and Kahneman, 1973)
o Humans are not “rational”
• Fundamental hypothesis
o Memories built after events, and then decays
• Modelling Example
o Feedback mechanisms in reservoir operation
Modeling example

96. Modeling feedback mechanisms
in reservoir operation
Human-modified outflow (Q) derived from the “natural” inflow (QN)
using a linear reservoir approximation with a variable storage coefficient (k)
Variables Units Description
Mf [.] flood memory
Md [.] drought memory
Q [L3/T] human-modified outflow
Parameters Units Description
kf [T] coefficient to cope with flood
kd [T] coefficient to cope with drought
μ [1/T] memory decay rate
a [T] overflow coefficient
b [.] bias parameter
(Di Baldassarre et al., Earth System Dynamics, 2017)

97. Example and results
• Brisbane streamflow data as “natural” inflows into the reservoir
• Diagram shows the resulting outflows
(Di Baldassarre et al., Earth System Dynamics, 2017)
0
10
20
30
40
50
60
1973 1983 1993 2003 2013
MeanAnnualFlow(m3s-1)
Coping with Flood
Coping with Drought
Human-modified Outflow
Millennium
drought
Modeling feedback mechanisms
in reservoir operation

98. Summary and perspectives

99. • Empirical and theoretical work
• Dynamics emerging from the mutual shaping of hydrology and society
• Levee and adaptation effects, supply-demand cycle and sequence effect
• Understanding past changes and projecting future trajectories to support the
making of strategies for sustainable water management, disaster risk reduction,
and climate change adaptation
Summary

100. • Open questions:
o Site-specific dynamics or generic patterns?
o What can(not) be generalized?
o What are the social and hydrological conditions in which they emerge? Why?
o How do they change across scales?
• Empirical and theoretical studies, as well as global comparative analyses
• Unprecedented opportunity: “flood” of global data and archives
o Human influence (e.g. dams and reservoirs, irrigation, protection standards)
o Human response (e.g. proxies of economic activity, population density)
Perspectives
Nightlights
Reservoirs and Dams

101. Giuliano Di Baldassarre
Uppsala University, Uppsala, Sweden
Centre for Natural Disaster Science, Uppsala, Sweden
UNESCO-IHE Institute for Water Education, Delft, Netherlands
Hydrological Extremes and Human Societies
Cagliari University, July 2017
Visiting Professor Programme

102. Debate

103. What are these?
What do they have in common?!

104. Black Swans
• Black Swan event is a surprise (to the observer)
• Black Swan event has a major impact
• Black Swan event appears as if it could have been expected
(retrospective predictability)

105. Black Swans
(observer)

106. Debate
• Small group discussion (1 hour)
– Was the Vajont dam disaster a black swan event?
– If so, for whom? And, why?
– Could it be prevented? How?
– “Local knowledge” versus “experts”
• Group “leader” present
– 2/3 slides (5/10 minutes)
• Debate -be open!

107. We can’t predict everything,
but we can still reduce losses!

108. Unrepeatable chain of events
and cascade of contingencies
0
2
4
6
8
10
12
1920 1930 1940 1950 1960
FloodLevels(mabovedatum)
Human-water system
SURPRISE!
Example: Piave River at Ponte delle Alpi (Italy)
(Di Baldassarre et al., Hydrlogical Sciences, Journal, 2016)

109. Top-down and bottom-up approaches
(source: Bloeschl et al., 2013)(Bloeschl et al., Climate Vulnerability, 2013)