Transcript Hydromorphology or Hydrology in an Ever Changing World

Upmanu Lall
Columbia University
How has water influenced the history of man and life on Earth?
How has man determined the history, distribution and
pathways of water?
 How have climate variations and change determined water and
life at different scales, places and times?
 How has water constrained and determined climate?
 When/how will the human induced hydrologic change
dominate that due to climate, and in turn determine aspects of
regional and global climate change and variability?
 How can we assess or predict a hydrologic future for the 21st
century to address impending concerns of water stress for man
and life given potentially dramatic hydrologic changes due to
changes in seasonal and long term climate variability and to
human factors?
 How will we manage such changes?

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A Semi-classical View
Design: Long Term Risk Management
Manage Variability
Operation: Manage Residual Risk
Nonstationarity?
Society Goals
Hydrology
Structure
Curiosity
Processes
Dynamics
Evolution
Planetary Context
(bio-geo-human-systems)
Knowledge
Fluid Mechanics
Stochastic Processes
Do we have
satisfactory
models for long
term evolution?
Challenges:
1. Spatial Heterogeneity, Scales & Continuum, Structure of Turbulence/Transport
2. Long Term Evolution (not much literature, except for climate)
Open or Closed System? Strong Feedbacks with other earth systems
A Restricted View of the Earth System
Climate Dynamics
Ocean-Atmosphere
Dynamics
Weather
Ecological Dynamics
Land Use Dynamics
Geomorphology
Other
processes*
Demographics
Social Dynamics
Think about actual processes involved  time and space scales, thresholds, intermittent
or continuous
* e.g., Tectonic activity, uplift
A Restricted View of the Earth System
Climate Dynamics
Ocean-Atmosphere
Dynamics
Weather
Ecological Dynamics
Land Use Dynamics
Hydrology
Geomorphology
Other
processes*
Demographics
Social Dynamics
Think about actual processes involved  time and space scales, thresholds, intermittent
or continuous
A Restricted View of the Earth System
Climate Dynamics
Ocean-Atmosphere
Dynamics
Hydromorphology
Weather
Ecological Dynamics
Land Use Dynamics
Hydrology
Geomorphology
Other
processes*
Demographics
Social Dynamics
Orgaqnization time and space scales, thresholds, intermittent or continuous
dynamics, system/state boundaries

Non-Autonomous Forced Dynamical System
dx
 f ( x , g ( y ( t ); θ )
dt
A number of inter-acting stores  state variables
Forced by exogenous variables that are time varying (continuous or intermittent)
Spatially averaged, discrete or continuous time
Focus (often): Fluxes, Patterns, Mean Residence Times
Does this system have interesting dynamics?
Suppose we think of this system as a RLC network
Are the internal dynamics of x dominated by y?  dynamics of y?
Analogies -- Role of R? C? L?
Are there strong +ve and –ve feedbacks across x
Nonstationarity in x  changes in y, changes in θ, changes in f(.,.,.) or all

Dominant interest in
 Mean value – statistics of state variables
 Stimulus response modeling (spatial emphasis, short term)
▪ Event Models
▪ Continuous Simulation Models
▪ Components can often be decomposed into separate models
 Slow components (e.g. groundwater) modeled separately (forced by fast
component model) and provide initial conditions for stimulus-response of
faster component
 Cumulative effects modeling is unidirectional and naïve – model formulation
does not explicitly consider full dynamics or interactions across interfaces

Long term Dynamics – either in terms of statistical
properties of state variables or parametrically determined by
statistical properties of exogenous variables
 No good paradigm available for modeling long term dynamics
including feedbacks across key exogenous variables at appropriate
space and time scales (we are in a discovery phase)

Hydrology




“open terrestrial system”
hillslope/basin scales
response function to forcing
forecasts from initial and
boundary value problems
 Prescribed topography, soils,
vegetation, use, climate (rain,
etc)
=> Stationary* probability
distributions whether the
problem is treated
deterministically or statistically
Weather

Hydromorphology
 Interacting planetary “stores” 
hierarchy  “closed system?”
 Regimes in space-time,
predictability, transition, stability
 Parametric evaluation of boundary
value problems
 Boundary conditions/interfaces
evolve -- coupled
=> “holistic?” view of global and local
hydrologic cycle and its
dependence on changing
conditions  non-stationary, unless
conditional probability
Climate

Non-Autonomous Forced Dynamical System
dx
 f ( x , g ( y ( t ))
dt
But ….
Now x includes human population state variables, technology, infrastructure
and income state variables as endogenous to the system
Human, infrastructure and river networks interact to prescribe both the
evolution of the water state variables and the networks themselves
Prediction examples:
Long term evolution of population patterns in the river basin
Long term evolution of water and other infrastructure
Changing biota and landscape

Non-Autonomous Forced Dynamical System?
dx
 f ( x , g ( y ( t ))
dt
Now – as far as the water cycle is concerned, we could have closure
but many, many other “cycles” have to be accounted for
interactions across all planetary stores
human dynamics accounted for as endogenous
External forcing is solar radiation
Example prediction problems:
Gaia – Symbiosis across vegetation, atmosphere and humans through water?
Population density – spatial and temporal variations
The Greenhouse, the Thermohaline Conveyer, Abrupt Climate Change

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Local Changes in Flood Frequency due to
Urbanization/Land Use Change etc
Climate induced Changes in Floods 
Nature, 2002
Nature,
2003
Atmospheric River
generates flooding
CZD
Russian River, CA Flood Event
of 18-Feb-04
Slide from Paul Neiman’s
talk
Russian River flooding in Monte Rio, California
18 February 2004
IWV
(cm)
GPS IWV data from near CZD: 14-20 Feb 2004
Atmospheric
river
Cloverdale
10” rain at CZD
in ~48 hours
IWV (inches)
IWV (cm)
Bodega
Bay
photo courtesy of David Kingsmill
10 largest Floods
10 smallest Floods
Washington
Oregon
SST Composites for Extreme Floods
Coast of Western US
Look for what happens by latitude
N. California
C. California
S. California
60 years per station, 50 stations
Wavelet Analysis of 1000 year sample of annual maximum NINO3 from a 110,000 year
integration of the Cane-Zebiak Model with stationary forcing ( Clement and Cane, 1999)
2005 Headline
BOOTSTRAP SEVERITY WAVELET
xx 10
Colorado
River Compact Failure
in the Absence
of Lake Powell
WITH
Lake Powell
10
13
7
18
16
2
14
12
1.5
Relative
Variance
POWER
POWER
10
8
1
6
4
0.5
2
0
0
111
22
33
44
555
66
77
10
20
30
Recurrence Period
80 100
200
10 12
12 14
14 17
17 20
20 23
23 28
28 33
33 39
39 47
47 56
56 66
66 79
79 94
94 111
111132
132157
157187
187222
222264
264 314 374 445 529
88 10
FrequencyFrequency
Development
Utilization
Allocation
Hypothesis: In a given climate and technology, position on the river network has
been a determinant of human population and its infrastructure development
Role of mean supply vs role of variability in space and time
Scale and Direction of Human Feedbacks

Population in Billions
Global Population Growth
10
8
6
4
2
Most ecological species (w/o predators)
have population growth dynamics that
are not too different from logistic, with
carrying capacity determined by local
resources. Is water a likely resource
constraint?
If yes, is it a local or global constraint?
0
0
200 400 600 800 1000 1200 1400 1600 1800 2000 2200
How is it manifest?
YEAR (AD)
Scoping the feedback, as a function of
scale……….
Urban Forest Management
(evapotranspiration rates)
Ring Porous Wood Only
• assume 15 sq mi forest SLC
• ~3 MG per day
• SLC indoor ~44 MG per day
Diffuse Porous
Ring Porous
Average Daily Vapor Pressure Deficit (kPa)
From: S. Bush & D. Pataki
Source: Craig Forster
Marshall et al, 2001
S. Florida – draining
the swamps changes
regional moisture
recycling -desertification
Water Table Decline
>400 ft
Rivers have undergone
significant degradation
in flow and quality as
well
Width of Ganges at the
confluence with Yamuna
is now typically 3 to 4
km smaller
With all these benefits, it is not surprising that farmers and entrepreneurs have
invested around US$12 billion in groundwater pump structures. This sum is huge,
especially when compared with the US$20 billion of public money spent on surfacewater irrigation schemes over the last 50 years
Large Scale Irrigation changes the
Monsoon?
Irrigation  changed water vapor
flux
A Proposal to Link
Major Indian River
Systems:
$160 Billion Capital Cost
33 Dams (9 Major)
30 Major Canals covering
12,500km
34 million hectares to be
irrigated (12x Area of
Bangladesh) =30% of current
34GW of hydropower
Flood Control
Navigation
VIRTUAL WATER FLOWS (1995)
measured in crop ET, cereals
EU (15) excluding intra-trade
Primary Challenge:
What is important, when, where and how?
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How to develop and test a suitable low order dynamical modeling system to
understand the currency of water in global evolution
How can data sets be developed to support hypothesis development for
long term evolution of the Gaia system
How can we learn and build from integrated hydrology structure-evolution
modeling and data sets
Decomposition of Climate and Human Factors:
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Low frequency climate oscillations translate into systematically changing frequency
and intensity of precipitation and aquifer recharge/discharge.
How are these manifest in natural and modified hydrology in different climate zones?
What are the dominant frequencies of response of different hydrologic components?
How do they depend on spatial scale and the spatial distribution of development in the
system?
What are key climatic or development thresholds that lead to abrupt hydrologic
change?

Water and the Development of Societies – Agent/Environment
Interaction:
 Does human “control” and development of surface and subsurface water
fluxes superposed on the pattern of climatic exigencies lead to emergent and
predictable patterns or cycles of infrastructure development, hydrologic
modification and climate impact?
 Is the observed scaling of population density with area related to position on
the drainage network, and the seasonal and interannual variation of
hydrologic fluxes over the drainage network?
 What is the role played by agriculture and ecosystems in determining water
use and human population density?
 How does the population distribution and scaling with area change as storage
infrastructure and other technological innovations change the variability and
scaling of hydrologic fluxes with area?

From Human to Water to Climate:
 How have regional hydrologic changes induced by human activity modified
regional climate?
 How does changing planetary temperature, terrestrial biota and land use
translate into changes in atmospheric water composition and the hydrologic
cycle?
 How do these changes determine a future planetary climate?