Water Resources System: Planning and Managment

Water Resources Systems: Planning
and Management (WREn6021)
12/25/2020 Water Resources Systems _ (WREn6021) Tew
Introduction
1

1.1 Availability of water on earth and water use
12/25/2020 Water Resources Systems _ (WREn6021) Tew 2
• The availability and demand for water have emerged as a prior agenda for the last century as a
result of:
• Highers standards for living
• Depletion of resources of acceptable quality
• Excessive water pollution due to agricultural and industrial expansions
• Increase in population
• e.t.c
• a question that should be addressed is whether future water resources development could be done
in a way that:
• Environmentally sustainable (keep ecological integrity)
• Economically feasible (maintain social equity)
• Technically acceptable (safe and within the state of the current technology)
• Politically sound (work under the legal framework)

Cont…
• Planning for sustainable development of water resources means:
• Water conservation
• Waste and leakage prevention
• Improved efficiency of water systems
• Improved water quality
• Water withdrawal and usage within the limits of the system
• A level of water pollution within the carrying capacity of the streams
• Water discharge from groundwater within the safe yield of the system
• In other words, we are seeking a balance among:
• Our physical being
• Our ability to manage our resources
• Limitations imposed by the environment
• In general, water resource development studies can be classified into:
• Planning
• Operation
• Management

Cont…
• Steps in the water resource planning process can be classified into the following phases:
• Problem definition, data collection and processing
• Modelling
• Decision making
• Construction
• Continuous monitoring of the system
• Data collection and processing are important parts of this process and include:
• Climatic, hydrologic, hydraulic, and environmental characteristics of the study area affecting the
supply and the demands
• Economic, institutional, and legal conditions affecting water allocation policies
• Structural and physical characteristics of the rives and reservoirs and their appurtenant facilities
that have impacts on the carrying capacity of the system

Cont…
• A reservoir used only for hydro power (or water supply) performs
better at full condition.
• A reservoir used only for flood control performs best when left
empty until the flood comes.
• A single reservoir serving all the three purposes (hydropower, water
supply and flood control) is to be managed better by knowing how
much water to store and how it is operated.
• Conflicts exist where demands are more than supplies.
• Finding ways to manage and resolve these conflicts over time and
space is one more reason for planning.

1.2 System definition and properties
• System:
• Any structure or device, including different interactive components (real or abstract), that causes an
output reference to a specific input in a given time can be called a system
• The common characteristics of any system in general, and water resources systems specifically can
be summarized as:
• All systems have some structure and organization
• Systems are all generalizations, abstractions, or idealizations of the real world with different
levels of complexities
• Functional and structural relationships exist between components of the system
• All systems show some degree of integration
• Input-output relations and the nature of them are important characteristics of systems

Cont…
• System:
• Specification of systems can be classified as:
• Inputs
• Governing physical laws
• Initial and boundary conditions
• outputs
• Inputs, outputs, and major characteristics of the systems are usually defined by:
• Variable:
• Is a system characteristics that assumes different values measured at different times
• Parameter:
• Is also a system characteristic, but it normally does not change with time

Cont…
• System:
• Variables or parameters can be classified as:
• Lumped:
• Which do not change in space
• Distributed:
• Which vary in one or more space dimensions
•Memory:
• another important characteristic of a system
• Is the length of time in the past for which the input could have an impact on the output
• A system may have different levels of memory:
• Zero memory: the state and output depend only on the input in the present time
• Finite memory: the state, output, and behaviour depend only on the history of the system for a specific time
span (memory)
• Infinite memory: the state and output depend on the entire history of the system

Cont…
• System:
• Systems are classified as deterministic or stochastic:
• Deterministic system: the same input gives the same output
• Stochastic system: contains one or more elements for which the relationship between input and
output is probabilistic rather than deterministic
• There are other detailed classifications of systems, these are:
• Continuous systems – the output is produced continuously
• Discrete systems – the output changes after finite intervals of time
• Quantized systems – the output values change only at certain discrete intervals of time and
hold a constant value between these intervals
• Natural systems – the input and outputs and other state variables are measurable and are not
controlled
• Devised systems – the input may be both controllable and measurable
• Simple systems – no feedback mechanisms exist in these systems
• Complex systems – feedback is built into these systems

Cont…
• System:
• Adaptive systems – these systems learn from their past history to improve their performance
• Causal systems – an output cannot occur earlier than the corresponding input (cause and effect)
• Simulation systems – these are realization systems and are similar to causal systems
• Stable systems – if the input is bounded, the output is also bounded and vice versa
• Damped systems – the output of the system dies out without ever crossing the time scale
Note: most hydrologic systems are stable and causal systems and are heavily damped
Figure 1.2: outputs of continuous, discrete and quantized systems

Cont…
• System:
• System analysis: could face several different types of problems:
• Design problems – inputs and system are known and the output must be quantified
• System identification problems – inputs and outputs are known and the system itself must be
identified
• Detection problems – system and outputs are known and inputs must be identified
• Synthetic problems (simulation) – inputs and outputs are known and the performance of
models must be tested
Note: Hydrologist primarily deals with design and synthetic problems

Cont…
• Hydrologic Systems and Modelling approach:
• Complex systems can be decomposed into subsystems, each having an input-output linkage as a
component
•hydrologic systems:
• Can be considered as a subsystem of water resources representing the physical functioning of
that system in a region
• It is defined as a structure or volume in space, surrounded by a boundary, that accepts water
and other inputs, operates on them internally, and produces them as outputs (Chow et al. 1988)
• Two approaches can be used for modelling hydrologic systems:
• Theoretical approach – focuses on modelling the physics of the system
• Empirical approach – focuses on using historical observations of different components of
the hydrologic cycle

Cont…
•Models:
• Are simplified representation of systems
• Mathematical models are classified into:
• Empirical Vs. theoretical
• Lumped Vs. distributed
• Deterministic Vs. stochastic
• Linear Vs. nonlinear
Note: the holistic view of water resources planning and management could only be meaningful if it
is observed within the context of the hydrologic cycle, at least in a catchment scale.

1.3 System components, planning scale and
sustainability
•System Components:
• Water resources management involves the interaction of three interdependent subsystems:
• The natural river subsystem:
• In which the physical, chemical and biological process take place
• The socio-economic subsystem:
• Which includes human activities related to the use of the natural river system
• The administrative and institutional subsystem:
• In which legislation, regulation, decision, planning and management processes takes place

Cont…
•System Components:
Figure 1.3: interactions between subsystems

Cont…
•Planning Scale:
• There are two important concepts in relation to scale in the planning and management of water
resources development:
• Spatial scale for planning and management:
• Watersheds or river basins are usually considered logical regions for water resource planning and
management
• How land and water are managed in one part of a river basin can affect the land and water in other
parts of the basin
• Examples:
• The discharge of pollutants or the clearing of forests in the upstream portion of the basin may
degrade the quality and increase the variability of flows and sedimentation downstream
• The construction of a dam or weir in the downstream part of a river may prevent fish from
travelling upstream

Cont…
•Planning Scale:
• Temporal scale for planning and management:
• Water resource planning require looking into the future
• Decisions recommended for the immediate future should take account of their long-term impacts
• Impacts may also depend on economic, demographic and physical conditions now and on into the
distant future
• Water resources plans need to be periodically updated and adapted to new information, new
objectives, and updated forecasts of future supplies, demands, costs, and benefits
• Examples:
• Irrigation planning and summer season water recreation planning may require a greater number
of within-year periods during the summer growing and recreation season than might be the case
if one were considering only municipal water supply planning
• Assessing the impacts of alternatives for combined surface and groundwater management, or for
water quantity and quality management, require attention to processes that take place on
different spatial and temporal scales

Cont…
•Sustainability:
• Sustainable water resources systems are:
• those designed and managed to best serve people living today and in the future
• Those designed and operated in ways that make them more adaptive, robust and resilient to an
uncertain and changing future
• Those capable of functioning effectively under conditions of changing supplies, management
objectives and demands
• Sustainable systems, like any other, may fail, but when they fail they must be capable of recovering and
operating properly without undue costs
• The concept of environmental and ecological sustainability has largely resulted from a growing concern
about the long-run health of our planet
• Sustainable development:
• “development by using renewable natural resources in a manner that does not eliminate or
degrade them or otherwise diminish their renewable usefulness for future generation...” (Karamouz,
1993)

1.4 Planning and Management aspects of WRS
•Technical Aspects:
• Technical aspects of planning include:
• Hydrological assessments
• Engineering structures for making better use of scarce water
• Canals and water-lifting devices
• Dams and storage reservoirs that can retain excess water from periods of high-flow for use
during the periods of low-flow
• Open channels and pressure conduits
• Diversion structures, ditches, pipes and other engineering facilities necessary for the effective
operation of irrigation and drainage systems
• Municipal and industrial water intakes, including water purification plants and transmission
facilities
• Hydroelectric power storage, run-of-river or pumped storage plants
• River channel regulation works, bank stabilization, navigation dams and barrages, navigation
locks and other engineering facilities for improving a river for navigation, etc.

Cont…
•Economic and Financial Aspects:
• Water has an economic value in all its competing uses and should be recognized as an economic
good (the Dublin principle)
• The principle addresses:
• the need to extract the maximum benefits from a limited resource
• the need to generate funds to recover the costs of investments
• The need to recover costs for operation and maintenance of system
• Many past failures in water resources management are attributable to the fact that has been – and
still is – viewed as a free good
• Charging for water at less than full cost means that the government, society, and/or environment
‘subsidizes’ water use and leads to sub-optimal use of the resource
• The overriding financial component of any planning process is to make sure that the recommended
plans and projects are able to pay for themselves
• Planning must identify equitable cost and risk-sharing policies and improved approaches to
risk/cost management

Cont…
•Institutional Aspects:
• The first condition for successful project implementation is to have an enabling environment
• There must exist national, provincial and local policies, legislation and institution that make it
possible for the right decisions to be taken and implemented correctly
• The role of the government is crucial, the reasons are:
• Water is a resource beyond property right – water rights can be given to persons or companies,
but only the rights to use the water and not to own it
• Water is a resource that often requires large investment to develop
• Water is a medium that can easily transfer external effects – the use of water by one person
often has negative effects on others
• An insufficient institutional setting and the lack of a sound economic base are the main causes of
water resource development project failure, not technical inadequacy of design and construction

A Typical Water Resource System

• Stakeholders involved in river basin planning and
management, each having different goals and
information needs

Modelling Techniques
• Modelling or system analysis techniques - Developed during the Second World War to deploy limited
resources in an optimum manner
• These techniques were aided for military operations - known as operation research techniques
• Popular operations research techniques include
• Optimization methods
• Simulation
• Game theory
• Queuing theory etc
• Among, these, the popular ones in water resources field are optimization and simulation.
24

Optimization
• Science of choosing the best amongst a number of possible alternatives
• Identify the best through evaluation from a number of possible solutions
• Driving force in the optimization is the objective function (or functions)
• Optimal solution is the one which gives the best (either maximum or minimum) solution under all
assumptions and constraints
• An optimization model can be stated as:
Objective function: Maximize (or Minimize) f(X)
Subject to the constraints
gj(X) ≥ 0, j = 1,2,..,m hj(X) = 0, j = m+1, m+2,.., p
X is the vector of decision variables; g(X) are the inequality constraints; h(X) are the equality constraints.
25

Classification of Optimization Techniques
Optimization problems can be classified based on the
• Type of constraints
• Nature of design variables
• Physical structure of the problem
• Nature of the equations involved
• Permissible value of the design variables
• Deterministic/ Stochastic nature of the variables
• Separability of the functions and number of objective functions
26

Classification based on existence of constraints
• Constrained optimization problems: Subject to one or more constraints
• Unconstrained optimization problems: No constraints exist
27

Classification based on physical structure of the problem
Optimization problems are classified as optimal control and non-optimal control problems.
(i) Optimal control problems
• Problem involving a number of stages
• Each stage evolves from the preceding stage in a prescribed manner.
• Defined by two types of variables: the control or design and state variables.
• Control variables define the system and controls how one stage evolves into the next
• State variables describe the behavior or status of the system at any stage
• Problem is to find a set of control variables such that the total objective function (also known as the
performance index, PI) over all stages is minimized, subject to a set of constraints on the control and state
variables.
28

Classification based on the physical structure of the problem…
An OC problem can be stated as follows:
Find X which minimizes
Subject to the constraints
where xi is the ith control variable, yi is the ith state variable, and fi is the contribution of the ith stage to the
total objective function. gj, hk, and qi are the functions of xj, yj ; xk, yk and xi, yi , respectively, and l is the
total number of states.
(ii) Problems which are not optimal control problems are called non-optimal control problems.
29

Classification based on the nature of the equations involved
Optimization problems can be classified as
(i) Linear programming: Objective function and all the constraints are ‘linear’ functions of the design
variables
(ii) Nonlinear programming : Any of the functions among the objectives and constraint functions is
nonlinear
(iii) Geometric programming : Objective function and constraints are expressed as polynomials
(iv) Quadratic programming: Best behaved nonlinear programming problem with a quadratic objective
function and linear constraints and is concave (for maximization problems)
30

Classification based on the permissible values of the decision variables
Objective functions can be classified as integer and real-valued programming
(i) Integer programming problem: Some or all of the design variables of an optimization problem are
restricted to take only integer (or discrete) values
(ii) Real-valued programming problem: Minimize (or maximize) a real function by systematically
choosing the values of real variables from within an allowed set. When the allowed set contains only
real values, it is called a real-valued programming problem
31

Classification based on deterministic/ Stochastic nature of the variables
Optimization problems can be classified as deterministic or stochastic programming problems
(i) Deterministic programming problem: In a deterministic system, for the same input, the system will
produce the same output always. In this type of problems all the design variables are deterministic.
(ii) Stochastic programming problem: In this type of problem, some or all the design variables are
expressed probabilistically (non-deterministic or stochastic).
32

Classification based on separability of the functions
Optimization problems can be classified as separable and non-separable programming problems
(i) Separable programming problems: In this type of problem, the objective function and the
constraints are separable.
Function is said to be separable if it can be expressed as the sum of n single-variable functions,
,
i.e.
(ii) Non-separable programming problems: Objective function is not separables
33
( ) ( ) ( )
n
n
i x
f
x
f
x
f ,...
, 2
2
1
( )
∑
=
=
n
i
i
i x
f
X
f
1
)
(

Classification based on the number of objective
functions
Objective functions can be classified as single-objective and multi-objective programming problems.
(i) Single-objective programming: There is only a single objective function.
(ii) Multi-objective programming: A multiobjective programming problem can be stated as follows:
Find X which maximizes/ minimizes
Subject to gj(X) ≤ 0 , j = 1, 2, . . . , m
where f1, f2, . . . fk denote the objective functions to be maximized/ minimized simultaneously
34
( ) ( ) ( )
X
f
X
f
X
f k
,...
, 2
1

Simulation
• Simulation process duplicates the system’s behaviour by designing a model of the system and conducting
experiments for a better understanding of the system functioning in various probable scenarios
• Simulation reproduces the response of the system to any imposed future conditions
• Main advantage of simulation is its ability to accurately describe the reality
• Operating policies can be tested through simulation before implementing in actual situations
• Water resources systems are too complex to be expressed in any analytical expression.
• Simulation model duplicates the system’s operation with a defined operational policy, parameters, time series of
flows, demands etc
• Design parameters and the operation policy are evaluated through the objective function or some reliability
measures.
35

Steps in Simulation
1. Problem definition: Define the goals of the study
2. System definition: Identify the water resources system components and its hydrological aspects.
Identify the performance measures to be analysed.
3. Model design: Understand the behavior of actual system. Decide the model structure by determining
the variables describing the system, its interaction and various parameters of structures. Decide the
inputs (time series of flows, demands of the system, operation policies etc) and outputs (hydrological
variables and design variables).
4. Data Collection: Determine the type of data to be collected. New/ Old data is collected/ gathered.
5. Validation: Test the model and apply the model to the problem
36

Classification of Simulation models
• Simulation models can be
i. Physical (e.g. a scale model of a spillway)
ii. Analog (system of electrical components such as resistors or capacitors arranged to act as an analog to the
hydrological components) or
iii. Mathematical (action of a system expressed as equations or logical statements.
• Simulation models can be
i. Static (fixed parameters and operational policy) or
ii. Dynamic (takes into account the change in the parameters of the system and the operational policy with time) in
nature.
37

Classification of Simulation models…
• Simulation models can be deterministic or stochastic
• Simulation models can be statistical or process oriented, or a mixture of both.
• Pure statistical models are based solely on data (field measurements). Regressions and artificial neural networks are
examples
• Pure process oriented models are based on knowledge of the fundamental processes that are taking place. In this,
calibration using field data is required to estimate the parameter values in the process relationships.
• Hybrid models incorporate some process relationships into regression models or neural networks.
38

Comparison between Optimization and Simulation
• Optimization models eliminate the worst solutions.
• Simulation tools evaluate the performance for various configurations of the system; but they are not effective for
choosing the best configuration.
• Simulation simply addresses ‘what-if’ scenarios – what may happen if a particular scenario is assumed or if a
particular decision is made. Users have to specify the value of design or decision variables for conducting
simulation.
• Simulation is not feasible when there are too many alternatives for decision variables, which demand an enormous
computational effort.
• Optimization will determine the best decision; but the solution is often based on many limiting assumptions.
• Full advantage of systems techniques: Optimization should be used to define a relatively small number of good
alternatives that can later be tested, evaluated and improved by means of simulation.
39

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