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Presented By:
Athulya C S
TJALECE014
Guided By:
Ms. Ayana V S
Assistant Professor ,
Department of Civil Engineering
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Water is the essence of life
Important to both society and ecosystems
We depend on a reliable, clean supply of drinking water
We need water for agriculture, energy production,
navigation, recreation, and manufacturing
INTRODUCTION
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WATER SUPPLY SYSTEM
Water supply systems provide water in sufficient quantity
and quality
It is an essential requirement for all people
3 components:
Source
Treatment
Distribution
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Source of water refers to the surface water and
groundwater
Depending on the raw water quality, the treatment
objectives and the costs of operation, different water
treatments are provided
Water Supply System Continues...
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Comprises of :
Storage facilities
Pumping stations
Interconnected series of pipes
Water Supply System Continues...
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The failure occurs when the system is unable to meet the
water quantity and quality requirements
Risks:
• Change in precipitation
• Temperature
• Climate change
• Population
Water Supply System Continues...
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Changes are expected to differ from region-to-region
It will be directly impacted by changes in atmospheric
condition, topographical features,etc.
Any change will result in corresponding regional
changes in runoff
i. Precipitation
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Influences water availability
It cause increase in evaporation may result in droughts
Results in melting of glaciers
ii.Temperature
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The effects will be felt particularly through changes in
the water cycle
Water supply and sanitation infrastructure and
management systems are vulnerable to current climate
related threats
It determines how much water is available and how
much water we need in the short and long term
iii.Climate change
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Major factors that define the performance of a water
supply system
A major contributor to water scarcity
As the world’s population grows, the demand for water
mounts and pressure on finite water resources increses
iv.Population
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Growth in populations means competition for water for
domestic, industrial, and municipal water uses
Limits the amount of water available per person
Population Continues...
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Risk is defined as a measure of the probability and
severity of adverse effects
Risk in water supply systems lays in the principle
components of the system
Need of Risk Assessment
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Includes :
Mechanical, operational, or structural failure
Treatment
Distribution system components
Need of Risk Assessment Continues…
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Risk found in a water supply system focused on the risk
of water shortage due to population growth and climate
change
There are three primary types of risk:
Objective
Subjective
Perceived risk
Need of Risk Assessment Continues…
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Reliability, Resiliency, and Vulnerability can be used to
describe the performance of a water resource system
a. Reliability
•Probability that a system operates within specified
conditions during a specified period of time
•Probability of a system in its satisfactory state
Need of Risk Assessment Continues…
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b. Resiliency
How quickly a system recover a failure
Measured by system’s average recovery rate
The expected maximum severity of an overall system
c. Vulnerability
Need of Risk Assessment Continues…
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WATER DEMAND MODELLING
To forecast these future risks, one of the best methods is
to construct a stochastic model
The advantage of the stochastic approach is to capture
the uncertainties found in natural climate variability
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General Circulation Models (Global Climate Models)
are a class of computer models developed primarily for
weather forecasting and climate change
Water Demand Modelling Continues...
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A computer-based model is constructed to estimate the
performance indices of a water supply system
Examines the impacts of population growth and
fluctuating climate conditions on the water supply system
Water Demand Modelling Continues...
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MODEL ARCHITECTURE
In most failure mode or risk analysis studies, the
potential failure to a system is first determined and
analyzed
Artificial Neural Network models are becoming
prominent for water demand forecasting
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ANN model interpret the relationship found between the
input and output data
ANN is suitable to perform a function by using multiple
parameters on the existing information and predict the
possible relationships
Artifitial Neural Network Continue...
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ANN has the ability to map out and reproduce the
complex relationships underlying the water consumption
data
Artifitial Neural Network Continue...
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The network training process involves three major steps:
Data selection
Input variable selection
Best net selection
Artifitial Neural Network Continue...
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ANN could compute a variety of system outputs, such
as energy costs as a function of water source and
treatment
ANN system used to minimize operational costs
without violating regulatory and environmental
constraints
Artifitial Neural Network Continue...
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Structure of simulation model schematic for
Reliability, Resilience, and Vulnerability assessment
process are:
Model Archetecture Continue...
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Stimulation Model
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Monte Carlo Simulation involves generating random
values of stochastic parameters from their corresponding
probability distribution
Steps are:
• Generation of basic events
• Simulation of effect
• Cumulation of performance statistics
Monte Carlo Simulation Continue...
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MCM to generate two time series measures by
probability distributions and utilizes ANN to calculate the
daily water demand
Examines all the possible outcomes and assesses the
impact of risk for better decision making
Monte Carlo Model Continues...
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Monte Carlo Simulation assists organizations that allow
supply chain to forecast any number of potential obstacles,
cause disturbance
Monte Carlo Model Continues...
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CONCLUSION
Climate change a complex issue, more work is needed to
establish reliable practices for incorporating it into water
utility decisions and planning
ANN model in combination with MCM, arrives the
advantages of a simple functional form and accuracy
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The simulation model takes climatic variables and water
consumption patterns from historical records and projects
The model is used to estimate the effects of water
efficiency management programs and system expansion
on improving the system
Conclusion Continue...
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REFERENCES
1. Beatrice Biau Yung, Bryan A. Tolson, and Donald H. Burn, “Risk
Assessment of a Water Supply System under Climate Variability:
A Stochastic Approach”, Canadian Journal of Civil Engineering,
July 2011, pp.252-262.
2. Guy Howard, Katrina Charles, Kathy Pond, Anca Brookshaw,
Rifat Hossain and Jamie Bartram, “Securing 2020 vision for
2030: climate change and ensuring resilience in water and
sanitation services”, Journal of Water and Climate Change, 2010.
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3. M.Nirmala Ian Beauregard, Guillaume Talbot, Daniel Caya,
and Sebastien Binerb, “Modeling and Predicting the Monthly
Rainfall in Thamilnadu as a Seasonal Multivariate Arima
Process”, International Journal of Computer Engineering and
Technology, May-June 2010, ISSN 0976-6367, Vol.1, No.1, pp.
103-111.
4. M. R. Najafi, and H. Moradkhani, “A hierarchical Bayesian
approach for the analysis of climate change impact on runoff
extremes”, Hydrological Processes, November 2013.
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5. Philip W. Mote, and Eric P. Salathe Jr, “Future climate in the
Pacific Northwest”, Climate Change , March 2010.
6. “Climate Change Vulnerability Assessments: A Review of
Water Utility Practices”, Office of Water Environmental
Protection Agency, August 2010.
7. http://www.goldsim.com/Web/Introduction/Probabilistic/Mo
nteCarlo.
8. http://www.cses.washington.edu/db/pdf/palmerhahnportland111.pdf
9. http://www.waterrf.org/PublicReportLibrary/4340.pdf
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