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Estimates of Water Demands
Overview
We need to know only two things, how many people and
industries we must serve, and how much water each will
demand. We would also like to know the influence of the
price of water and the influence of wet and dry periods.
First population projections
Demography - the science of population
Large variability in population density in U.S.
Standard Metropolitan Statistical Areas
What are the drivers of population?
An important factor is the availability of employment
How can this be predicted?
Techniques
We would like procedures more sophisticated than
simple extrapolation.
Why do we perform water demand forecasts
1.
Baseline forecasting
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2.
Predicting impacts of policy intervention
3.
Balancing use and supply
Demand and Requirements
Demand is used in terms of supply/demand curve
Requirements are in terms of what must be delivered
Demand Elasticity
Short-term - Response to immediate price changes
Long-term - Response to changes envisioned
A
P
0
P1
C
B
Q0
Q1
3
Price is Set in the Open Market
Does not allow centrally planned decision
Does not take advantage of economies of scale
By administrative decision
how high
how it is varied in time and space
Temporal variability of demand and supply
Methodological Framework
Statistical
Engineering
These approaches involve two different approaches that
model process differently, require different amounts of
information, and appeal to different needs.
Statistical approach looks to define significant parameters
then regress these to find correct "equation"
Engineering approach is more directly causal
General form of statistical models
Q = ao + a1X1 +... + anXn + u
1n Q = bo +b1X1 +... + bnXn + u
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Q = co c11n X1 +...cn1n Xn + u
Four other categories
1.
Trending - extend or extrapolate past events into the
future,
this can be done for aggregate or user groups.
List bad assumptions
2.
Per capita sector projections - involve extra element
of customer disaggregation and forecaster judgment.
Break things into better sub-groups.
3.
Econometric Models - identify and estimate the
effects of specific factors on water use. Relate use to
income, price, employment, weather, etc. Determine
significance and elasticity.
4.
Large scale use of models like IWR-Main, Municipal
and Industrial Needs model. Uses previous methods,
but uses highly disaggregated detail. Lost of built in
values.
Why choose a particular approach
How variable is the future?
How good an answer do you need?
How characteristic is the region?
What are important factors?
What are likely to be important parameters
1. Price and Bill Impacts
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Average rates, marginal rates
This usually addresses classes of customer
2.
Other Economic
Real income
Employment
3.
Demographic Growth and Change
Employment
There is a warning against just population but to look
at changes in how water use is applied in each sector
4.
Household Type and Mix
Single, Multiple, Non residential
Weather
How do we include this
Seasonal yes but what else
Average temperature
Cooling degree days
Irrigation precipitation
5.
6.
Customer Learning Curve
How quick do consumers respond
7.
Conservation and Ethics
8.
Behavioral Changes
Seattle Model
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Geographic Disaggregation
Inside city/outside city
Also one for each purveyor
Customer Class Disaggregation
Residential Single Family
Residential Duplex
Residential Multi-family
Small Commercial
Large Commercial
Industrial
Irrigation
Government and Education
For Purveyors
Residential Single Family
Residential Multi-family
Government and Education
Commercial and Industrial
Water Use Determinants
Water and Sewer plus water prices with lagged
response patterns (all sectors)
Household Income (SF, MF, and Duplex)
Sector or Total Employment (all but residential)
Cooling Degree Days (all except industry)
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Irrigation Precipitation days (residential)
Number of Households (residential)
SEATTLE Model
(1) Demand Y,t = exp[X1 * ln(Annual DemandY *
Monthly Factort) + X2 * ln(Rainfallt)
+ X3 * ln(Tempt) + Const]
(2) Demand Y,t = (Annual DemandY * Monthly Factort)
* (Rainfallt) X1* (Tempt)X2 *exp( Const)
(3) Demand Y,t = exp[X1 * ln(Annual DemandY *
Monthly Factort) + X2 * ln(Rainfallt)
+X3 * ln(Tempt) + X4 * ln(Rainfallt-1)
+ Const]
(4) Demand Y,t = (Annual DemandY * Monthly Factort)
*(Rainfallt) X1* (Tempt)X2 *(Rainfallt-1)X3 *
(Tempt-1)X4 *exp( Const)