DSS for Integrated
Water Resources
Management (IWRM)
Simulation based MC optimization
DDr. Kurt Fedra
[email protected]
ESS GmbH, Austria
http://www.ess.co.at
Environmental Software & Services A-2352 Gumpoldskirchen
River basin scale perspective
EU Directive 2000/60/EC
Basic principle:
Conservation laws (mass, energy) are used
to describe dynamic water budgets.
Basic unit: hydrographic catchment or river
basin, naturally bounded, well defined.
Complications:
• inter-basin transfers
• aquifer across catchment boundaries
• mismatch with administrative units
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Water resource MC optimization
Design or select policies to
• Maximize the benefits
• Minimize the costs
Using multiple criteria in parallel:
1. physical/hydrological
2. monetary (socio-economic)
3. environmental
Economic (participatory) approach:
Assumes that (rational) individuals maximize
welfare (individual and collective utility) as they
conceive it, forward looking and consistently.
G.Becker, 1993
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In summary:
Simulation-based optimization can identify
possibilities for considerable
INCREASES OF NET BENEFITS
•
•
•
(improvements in several criteria)
Globally (entire basin)
Sectorally (e.g., irrigated agriculture)
Geographically (administrative units or
hydrographically by sub-basin)
Mechanisms to distribute benefits equitably
lead to win-win solutions
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Multi criteria optimization:
1. Model the behavior of the system
(river basin) in sufficient detail
(distributed, dynamic, non-linear) to
generate meaningful criteria:
dynamic topological (network) water
resources model with daily timestep, coupled water quality model
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Multi criteria optimization:
1. sufficient detail: all major actors
or stakeholder find themselves
represented
2. meaningful criteria: all criteria
are relevant for the decision,
measurable (quantified, scalar or at
least ordinal)
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A topological model: nodes and reaches
A river basin is represented as a set of
nodes and reaches connecting them.
NODES
produce, consume, store, and
change water quality;
REACHES transport it between nodes
AQUIFERS underlying the network
• Costs
• Benefits
to supply water, damages, shortfall
from satisfied demand, compliance
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Gediz River basin, Turkey:
Semi-arid, 18,000 km2
1,600,000 people
Rapid demographic and economic growth, supports
the city of Izmir, drains into the Bay of Izmir,
shallow, enclosed, vulnerable
• Recurrent droughts
• High level of pollution
• Dominant agricultural water use
• Water fully allocated
• Overexploitation of groundwater
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Gediz River Basin:
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Model structure:
NODES have type specific attributes and
complex, dynamic behavior
Different simulation models describe:
• Behavior of individual nodes
• Behavior of the network
Makes it possible to cascade models:
rainfall-runoff 
water resources  water quality
irrigation

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A topological model: nodes and reaches
START
water input, required start point
generic, well, sping, subcatchment,
transfer, desalination
END
export from the network, required
endpoint for a model
CONFLUENCE combines two inflows, passive
GEOMETRY auxiliar node, no hydraulic function
CONTROL
monitors and records flow,
compares with targets
passiv, MINtarget, MAXtarget,
combined, calibration
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A topological model: nodes and reaches
DEMAND
water demand and use, losses and
consumptive use
generic, municipal, touristic,
industrial, light industry,
commercial, services, irrigation,
agriculture
RESERVOIR reservoirs with dams, and natural
lakes
DIVERSION diversion or bifurcation node, splits
a reach into two branches OR
extracts water from the main stream
RECHARGE adds water to an aquifer
TREATMENT affects only water quality
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A topological model: nodes and reaches
AQUIFERS one or more linked
groundwater bodies underlying NODES
and REACHES, connected through:
• Sources (springs, wells)
• Sinks (losses, seepage)
• Interaction with REACHES
• Recharge:
– Natural (rainfall, temperature, land cover)
– Artificial (recharge wells)
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Benefits and Costs
Nodes are described by cost functions:
– Investment
– Operating cost (OMR)
– Life time of project/structure
– Discount rates
Benefits per unit water supplied and used.
Computation of NPV (net present value) for
comparison of scenarios
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Benefits and Costs
Direct monetary:
• Investment, operations, damage,
producer benefits (irrigation)
Non-monetary: based on (contingent)
valuation (hypothetical markets):
• Shortfall costs, penalties, benefits of
compliance (in stream use, environmental use)
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Process representation:
Sources of water, inputs: START NODES
– Tributaries (simulated by the rainfall-runoff model),
– Wells and well fields,
– Inter basin transfer,
– Desalination,
– Water harvesting,
– Direct rainfall (reservoirs, reaches)
– Lateral inflow to reaches
– Groundwater recharge
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Process representation:
Water use, DEMAND NODES
Irrigation districts, settlements, industries,
wetlands
• Conveiance losses
• Consumptive use
• Evaporation and seepage
• Bypass or spill
• Return flow losses
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Process representation:
Water storage, RESERVOIR NODES
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•
•
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•
•
Evaporation and seepage
Direct precipitation
Local catchment
Dynamic storage
Release
Spillage
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Process representation:
Water allocation, DIVERSION NODES
• Constant ratio (fixed weir) or controlled
diversion (target) flow, possibly demand
driven (real-time control)
• Allocation priorities (downstream
requirements)
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Process representation:
Flow constraints, CONTROL NODES
Constant or dynamic constraints:
• Minimum flow requirements
• Maximum flow: flooding
(non-linear damage)
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Process representation:
Groundwater, AQUIFERS
• Natural recharge, evaporative (through soil
moisture) losses, deep percolation
• Artificial recharge (recharge nodes)
• Recharge from all seepage losses
• Provide input to start nodes:wells
(pumped) or natural springs
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Process representation:
Water flow, REACHES
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•
•
•
•
Simple routing (Muskingum, variable time step)
Lateral inflow
Direct precipitation
Evaporation
Seepage (groundwater exchange)
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Optimization: STEP 1
CONSTRAINTS:
Specify an acceptable system performance
in terms of lower and upper bounds of
criteria:
• Minimum amount of water available
• Maximum costs acceptable
• Minimum Benefits expected
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Water resources systems optimization:
Definition of optimality:
• Acceptability, satisficing
• Requires a participatory approach:
– Identification and involvement of major
actors, stakeholders
– Shared information basis
– Easy access, intuitive understanding
– Web based, local workshops
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Water resources systems optimization:
Acceptability, satisficing:
Easier for stakeholders to define
several fixed targets as
constraints than multiple
objectives and trade offs,
weights, preferences, etc.
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System performance criteria:
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•
•
•
•
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Supply/Demand, availability
Reliability of Supply (%)
Efficiencies (water, economic)
Sustainability (content change)
Water quality
Costs and benefits
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System performance criteria:
• Diversion performance (%): the
percentage of all "events" (summed over all
diversion nodes and days) where the
diversion target can be met;
• Allocation efficiency (%): the percentage of
supply diverted to supply nodes that
matches demands; all supply beyond
demand is "wasted" and decreases
allocation efficiency,
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System performance criteria:
• Unallocated (%): the total amount of water that
is unallocated at reservoirs (spilled), diversions
(beyond diversion and downstream targets),
control nodes (exceeding a minimum flow
constraint), expressed as a percentage of the
total amount of water the passes through these
nodes.
• Water Shortfall: the total amount of water
"missing" from the total demand, summed
overall all reservoir, demand, diversion, recharge
and control nodes, over all days, expressed as a
percentage of all stated "demands" including
releases, diversions, and in-stream flow
constraints.
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System performance criteria:
• Content Change: change of water value,
expressed as a percentage from the initial state
at the beginning of the current (water) simulation
year: measure of sustainability
• Flooding days: days of flooding; a flood occurs if
at any control node the flow exceeds a
maximum flow constraint.
• Flooding extent: the percentage of all "floods"
(summed over all control nodes with a maximum
flow constraint and days) as a percentage of all
"events";
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System performance criteria:
• Economic efficiency: the total benefit
per water available/supplied
in €/m3
• Economic efficiency, direct: the
direct, monetary benefit per unit water
available/supplied
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System performance criteria:
• Benefit/Cost: ratio of all benefits divided
by all costs accounted, including nontangible elements and penalties.
• Benefit/Cost, direct: ratio of all direct
monetary benefits over all direct monetary
costs.
• Net benefit: Total benefit minus total cost,
per capita.
• Total Benefit: Sum of all benefits, per
capita.
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System performance criteria:
• Total Cost: Sum of all costs, per
capita.
• Direct net benefits: Sum of all direct
monetary benefits minus sum of all
direct monetary costs, per capita.
• Direct benefit: Sum of all direct
monetary benefits, per capita.
• Total Cost, direct.: Sum of all direct
monetary costs, per capita.
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System performance criteria:
• Water Cost: Total cost of water, per m3:
Sum of all costs divided by the total
amount of water supplied against
demands at demand nodes, (diversions,
control nodes)
• Water Cost, direct: Total direct monetary
costs of water: as above, but considering
only direct monetary costs.
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Optimization STEP 1:
CONSTRAINTS:
GLOBAL: apply to some general, aggregate
measure for the entire basin
SECTORAL: apply to a sector like agriculture
industry, domestic, environment only
LOCAL (node specific):
At LOCATION node FROM day – TO day
CONCEPT (flow, cost, benefit, ratio)
Must be between MIN – MAX
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Optimization STEP 2:
INSTRUMENTS:
1. Select instruments for different NODE
CLASSES (demand, supply, reservoir,
diversion) from the data base;
2. Assign to specific NODES
3. Configure the specific techno-economic
data (efficiency, economics)
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Optimization STEP 3:
How it works: the MC optimization
1. Selects COMBINATIONS of
INSTRUMENTS, starting with the a priori
weights/probabilities;
2. Applies them to the base scenario, as
incremental changes
3. Evaluates the consequences (CRITERIA)
4. Compares with all the CONSTRAINTS
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Optimization STEP 3:
5. Rejects INFEASIBLE solutions
6. Retains FEASIBLE solutions as the
starting point for new trials, “learning” to
improve the CRITERIA values (genetic
algorithms, adaptive heuristics)
7. Continues the trials until:
a. The maximum number of trials has been
reached (1000 - 1,000,000);
b. The required number of feasible solutions
has been found
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Optimization STEP 4:
1. Export the set of FEASIBLE solutions to
the discrete multi-criteria DSS tool (DMC)
2. Rank solutions by individual criteria
3. Plot solutions on plains of two criteria
4. Manipulate PREFERENCES (set of
criteria, constraints, reference point) to
obtain a preferred (compromise) solution
5. Involve all stakeholders where feasible.
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Decision Support (multi-attribute)
Reference point approach:
utopia
criterion 2
A4
A5
efficient
point
A2
A6
A1
dominated
A3
nadir
criterion 1
better
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Finding a compromise solution:
Direct stakeholder involvement:
• Add or delete criteria
• Introduce (secondary)
constraints
• Change the reference point:
default is UTOPIA
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Optimization STEP 5:
1. Re-introduce the efficient solution to the
simulation models, re-run
2. Test all details of the systems behaviour
and performance to re-assure all
stakeholders that THEIR specific
requirements are being met;
3. Obtain agreement and consensus on the
distribution/allocation of benefits:
document the agreement, and have
everybody sign on the dotted line….
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In summary:
Simulation-based optimization can identify
possibilities for considerable
INCREASES OF NET BENEFITS
•
•
•
(improvements in several criteria)
Globally (entire basin)
Sectorally (e.g., irrigated agriculture)
Geographically (administrative units or
hydrographically by sub-basin)
Mechanisms to distribute benefits equitably
lead to win-win solutions
63