Population forecasting with the logistic curve In the logistic (S-shaped) population growth model for a developing city, the initial portion of the curve represents a period of:

Introduction / Context:
Population forecasting methods guide demand estimation for water-supply systems. The logistic curve portrays growth that accelerates initially, then decelerates as environmental and infrastructural constraints appear, approaching a saturation level (carrying capacity).

Given Data / Assumptions:

• Developing city undergoing early expansion.
• Logistic curve with lower asymptote, inflection point, and upper asymptote.

Concept / Approach:
The logistic function starts with relatively small numbers but an increasing rate of growth because resources and space are initially abundant. Growth rate peaks near the inflection point (mid-curve), then slows as limiting factors (space, economy, resources) reduce the net growth rate, approaching a steady upper limit.

Step-by-Step Solution:

Verification / Alternative check:
Fitting historical census data to a logistic model typically shows upward curvature initially (increasing growth), validating the interpretation.

Why Other Options Are Wrong:

• Decreasing or constant growth contradict the S-curve’s initial acceleration.
• Random fluctuations or sudden decline do not reflect the systematic logistic behaviour.

Common Pitfalls:
Confusing “growth rate” with “population level.” The early phase has both increasing population and increasing growth rate.

Final Answer:
Increasing growth