Water Demand - Environmental Engineering - Civil Engineering (CE)

Fire Demand

Fire demand is the quantity of water required for fire fighting in a community or a particular area. It is treated separately from normal domestic and industrial demands and is usually estimated by empirical formulae that relate required flow to population, built-up density, type of occupancy and recurrence of fires.

1. As per GO Fire Demand

   Q = 100(P)^1/2

   In this expression P denotes population; the formula gives an approximate flow rate for fire fighting based on population.

2. Kuichling's Formula

   Kuichling proposed an empirical relation for fire demand based on observed data. The formula is shown below.

Where, Q = Amount of water required in litres per minute.
P = Population in thousand.

3. Freeman Formula

   Freeman gave an empirical expression for fire demand. The formula is provided below.

4. National Board of Fire Underwriters Formula

   This set of recommendations gives differing design flows according to city type and building characteristics.

   (i) For a central, congested, high-valued city:

   (a) Where population < 200,000

4. (b) Where population > 200,000

   Q = 54,600 litres/minute for the first fire.

   Q = 9,100 to 36,400 litres/minute for a second fire depending on area and building density.

   (ii) For a residential city:

   (a) Small or low buildings: Q = 2,200 litres/minute.

   (b) Larger or higher buildings: Q = 4,500 litres/minute.

   (c) High-value residences, apartments, tenements: Q = 7,650 to 13,500 litres/minute.

   (d) Three-storeyed buildings in densely built sections: Q = 27,000 litres/minute.

5. Buston's Formula

   Buston's empirical relation incorporates the probability of occurrence of a fire and was developed from observed water consumption during fire fighting for Jabalpur city in India.

The probability of occurrence of a fire, which depends upon the type of city served, has been taken into consideration in developing the above formula on the basis of actual water consumption in fire fighting for Jabalpur city of India. The formula is given as

Where, R = Recurrence interval of fire (i.e., period of occurrence of fire in years). This recurrence interval will be different for residential, commercial and industrial areas and is used to adjust the design fire demand for the likelihood of occurrence.

Per Capita Demand (q)

Per capita demand is the average quantity of water used per person per unit time (commonly expressed as litres per capita per day, lpcd). It depends on climatic conditions, standard of living, water-using appliances, institutional and industrial uses, and conservation measures in the community.

Design of potable water supply systems commonly uses an appropriate value of per capita demand for the planning horizon. Values are adjusted for peak day and peak hour factors, losses and unaccounted-for water.

Assessment of Normal Variation

Water demand varies with time of day, day of week and season. Assessment of normal variation is essential for sizing storage, pumps and mains. Typical considerations are:

• Daily (diurnal) variation: Variation within a 24-hour period; used to determine peak hour and base loads.
• Seasonal variation: Higher demands in summer than winter in many areas.
• Design (peak) day: The day in a year when demand is highest; systems are often designed for a peak day demand or a peak day factor applied to average day demand.
• Peak hour factor: Ratio of the peak hour demand to the average hourly demand on the design day; important for storage and pump capacity.
• Diversity factor: Reduction in total maximum demand due to the probability that not all consumers use their maximum simultaneously; used when aggregating demands of different zones or consumer groups.

Graphical and statistical methods, including load curves and frequency analysis, are used to characterise normal variation and to select appropriate peak factors for design.

Population Forecasting Methods

Population forecasts are required to estimate future water demands. Several methods of forecasting are commonly used; the choice depends on available census data and observed population trends.

1. Arithmetic Increase Method

   Assumes that population increases by a constant absolute amount each decade.

   Formula is based on the arithmetic mean of past decadal increases and projects forward linearly.

Where, prospective population after n decades is obtained from the present (last known census) population plus n times the average decadal increase.

2. Geometric Increase Method

   Assumes population increases at a constant percentage (compound growth) each decade.

Where, P₀ = Initial population, P_n = Population after n decades, and r = assumed growth rate per decade (as a decimal): P_n = P₀ (1 + r)ⁿ.

To obtain r from two known populations, P₁ and P₂, separated by t decades, use the relation shown above to solve for the growth rate.

3. Incremental Increases Method

   This method analyses past absolute increases in successive decades and projects future increases by averaging the known increments or the increments of increments.

Where the average increase of population of known decades and the average of incremental increases are computed and used to forecast future decadal increases.

4. Decreasing Rate of Growth Method

   This method is used when the rate of growth shows a consistent downward trend as a city approaches saturation. The average decrease in the percentage increase is worked out and subtracted from the latest percentage increase for each successive decade to obtain projected growth.

   This approach gives rational results when historical data show a steady decline in percentage growth rates.

5. Logistic Curve Method

   The logistic (or S-curve) method recognises an upper limit or saturation population and models growth as slowing as the population approaches that limit.

Where, P_o = population at the start point, P_s = saturation population, P = population at time t from the origin, and k is a constant defining the growth rate. The logistic curve is useful where growth initially appears exponential but slows as limiting factors operate.

Notes on Applying Forecasts to Water Demand

• Choose the population forecasting method that best matches historical trend and local conditions; combine methods or use professional judgement when trends are inconsistent.
• Apply appropriate per capita rates, peak day and peak hour factors and add allowances for institutional, commercial, industrial and unaccounted-for water to obtain total design demand.
• Include separate allowance for fire demand when sizing mains, reservoirs and pump capacity; fire demand can be provided from dedicated hydrant systems, elevated reservoirs, or by ensuring transmission mains and storage can provide the required flow and duration.
• Re-evaluate forecasts and design assumptions periodically as new census and consumption data become available.