WATER DEMAND AND POPULATION FORECASTINGSHIVANGI SOMVANSHIASSISTANT PROFESSORAMITY UNIVERSITY

WATER DEMAND While planning a water supply scheme, it is

necessary to find out not only the total yearly water demand but also to assess the required average rates of flow and the variations in these rates. The following quantities are therefore generally assessed and recorded.

1. Total annual volume in Litres or million litres. (1MLD = 106L/d)

Annual Average rate of flow in litres per day , i.e. V/365

Annual average rate of flow in litre per day per person (l/c/d), called per capita demand.

CLASSES OF WATER DEMAND

CLASSES OF WATER DEMAND

WATER REQUIREMENT FOR DIFFERENT USES

PER CAPITA DEMAND It is the annual average amount of daily

water required by one person and includes the domestic use, industrial and commercial uses, public use, wastes etc. It may therefore be expressed as:

Per capita demand (q) in l/d/h or l/c/d = Total yearly water requirement of the city in litres (V) / 365 X Design population

FACTORS AFFECTING PER CAPITA DEMAND

Size of the city Climatic conditions Types of habitat of people Industrial and commercial activities Quality of water supplies Pressure in the distribution system Development of sewage facilities

DESIGN PERIODDesign period may be defined as:

“It is the number of years in future for which the given facility is available to meet the demand.”

Or“The number of years in future for which supply will be more than demand.”

Why Design period is provided ?Design period is provided because

It is very difficult or impossible to provide frequent extension.

It is cheaper to provide a single large unit rather to construct a number of small units.

POPULATION FORECASTINGDesign of water supply and sanitation scheme is based on the projected population of a particular city, estimated for the design period. Any underestimated value will make system inadequate for the purpose intended; similarly overestimated value will make it costly. Changes in the population of the city over the years occur, and the system should be designed taking into account of the population at the end of the design period. Factors affecting changes in population are:

increase due to births decrease due to deaths increase/ decrease due to migration increase due to annexation.

The present and past population record for the city can be obtained from the census population records. After collecting these population figures, the population at the end of design period is predicted using various methods as suitable for that city considering the growth pattern followed by the city.

POPULATION FORECASTING Arithmetic Increase method Geometric Increase Method Incremental Increase Method Decrease Rate of Increase Method Simple Graphical Method Comparitive Graphical Method

ARITHMETIC INCREASE METHOD This method is suitable for large and old city with

considerable development. If it is used for small, average or comparatively new cities, it will give lower population estimate than actual value. In this method the average increase in population per decade is calculated from the past census reports. This increase is added to the present population to find out the population of the next decade. Thus, it is assumed that the population is increasing at constant rate.

Hence, dP/dt = C i.e., rate of change of population with respect to time is constant.

GEOMETRIC INCREASE METHOD

INCREMENTAL INCREASE METHOD

GRAPHICAL METHOD In this method, the populations of last few decades are

correctly plotted to a suitable scale on graph. The population curve is smoothly extended for getting future population. This extension should be done carefully and it requires proper experience and judgment. The best way of applying this method is to extend the curve by comparing with population curve of some other similar cities having the similar growth condition.

COMPARATIVE GRAPHICAL METHOD

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EXTRAPOLATION TECHNIQUES Real Estate Analysts - faced with a difficult task

long-term projections for small areas such as Counties Cities and/or Neighborhoods

Reliable short-term projections for small areas Reliable long-term projections for regions

countries Forecasting task complicated by:

Reliable, Timely and Consistent information

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SOURCES OF FORECASTS

Public and Private Sector Forecasts Forecasts may be based on large

quantities of current and historical data

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PROJECTIONS ARE IMPORTANT

Comprehensive plans for the future Community General Plans for

Residential Land Uses Commercial Land Uses Related Land Uses

Transportation Systems Sewage Systems Schools

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PROJECTIONS VS. FORECASTS

The distinction between projections and forecasts are important because: Analysts often use projections when they

should be using forecasts. Projections are mislabeled as forecasts Analysts prepare projections that they

know will be accepted as forecasts without evaluating the assumptions implicit in their analytic results.

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PROCEDURE Using Aggregate data from the past to project the

future. Data Aggregated in two ways:

total populations or employment without identifying the subcomponents of local populations or the economy I.e.: age or occupational makeup

deals only with aggregate trends from the past without attempting to account for the underlying demographic and economic processes that caused the trends.

Less appealing than the cohort-component techniques or economic analysis techniques that consider the underlying components of change.

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WHY USE AGGREGATE DATA?

Easier to obtain and analyze Conserves time and costs Disaggregated population or employment

data often is unavailable for small areas

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EXTRAPOLATION: A TWO STAGE PROCESS

Curve Fitting - Analyzes past data to identify overall

trends of growth or decline

Curve Extrapolation - Extends the identified trend to project the

future

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ASSUMPTIONS AND CONVENTIONS

Graphic conventions Assume: Independent variable: x axis Dependent variable: y axis

This suggests that population change (y axis) is dependent on (caused by) the passage of time!

Is this true or false?

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Assumptions and Conventions Population change reflects the change in

aggregate of three factors: births deaths migration

These factors are time related and are caused by other time related factors: health levels economic conditions

Time is a proxy that reflects the net effect of a large number of unmeasured events.

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Caveats The extrapolation technique should never be

used to blindly assume that past trends of growth or decline will continue into the future. Past trends observed, not because they will always

continue, but because they generally provide the best available information about the future.

Must carefully analyze: Determine whether past trends can be expected to

continue, or If continuation seems unlikely, alternatives must

be considered

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Alternative Extrapolation Curves Linear Geometric Parabolic Modified Exponential Gompertz Logistic

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Linear Curve

Formula: Yc = a + bx a = constant or intercept b = slope

Substituting values of x yields Yc Conventions of the formula:

curve increases without limit if the b value > 0 curve is flat if the b value = 0 curve decreases without limit if the b value <

0

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Linear Curve

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Geometric Curve Formula: Yc = abx

a = constant (intercept) b = 1 plus growth rate (slope)

Difference between linear and geometric curves: Linear: constant incremental growth Geometric: constant growth rate

Conventions of the formula: if b value > 1 curve increases without limit b value = 1, then the curve is equal to a if b value < 1 curve approaches 0 as x

increases

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Geometric Curve

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Parabolic Curve Formula: Yc = a + bx + cx2

a = constant (intercept) b = equal to the slope c = when positive: curve is concave upward

when = 0, curve is linear when negative, curve is concave downward growth increments increase or decrease as the x

variable increases Caution should be exercised when using for long

range projections. Assumes growth or decline has no limits

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Parabolic Curve

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Modified Exponential Curve Formula: Yc = c + abx

c = Upper limit b = ratio of successive growth a = constant

This curve recognizes that growth will approach a limit Most municipal areas have defined areas

i.e.: boundaries of cities or counties

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Modified Exponential Curve

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Gompertz Curve Formula: Log Yc = log c + log a(bx)

c = Upper limit b = ratio of successive growth a = constant

Very similar to the Modified Exponential Curve Curve describes:

initially quite slow growth increases for a period, then growth tapers off

very similar to neighborhood and/or city growth patterns over the long term

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Gompertz Curve

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Logistic Curve

Formula: Yc = 1 / Yc-1 where Yc-1 = c + abX c = Upper limit b = ratio of successive growth a = constant

Identical to the Modified Exponential and Gompertz curves, except: observed values of the modified exponential curve

and the logarithms of observed values of the Gompertz curve are replaced by the reciprocals of the observed values.

Result: the ratio of successive growth increments of the reciprocals of the Yc values are equal to a constant

Appeal: Same as the Gompertz Curve

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Logistic Curve