Practice Inverse Distance Weighting Method (idw) (10.4.3) - Missing Rainfall Data – Estimation

Practice: Inverse Distance Weighting Method (IDW)

Lesson 10.4.3Missing Rainfall Data – Estimation

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10 questions

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6 sample questions

Question 1.
What is the main purpose of the Inverse Distance Weighting Method?
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Think about why geographic distance matters.
Question 2.
Explain why IDW uses distance squared in its formula?
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What happens to weight when distance increases?
3Question 3.
What is the primary benefit of using IDW?
- A. It is the simplest method
- B. It uses distance to weight proximity
- C. It does not require any data
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Remember how distance affects the influence of station data.
4Question 4.
IDW may not function well in regions with significant what?
- True
- False
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Think of areas with hills, valleys, or varied elevations.
Question 5.
You have rainfall data from three stations; A (30mm, 1km), B (60mm, 5km), and C (80mm, 3km). Estimate rainfall at a new station using IDW. Explain your calculations.
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What does the IDW formula tell you about weighting?
Question 6.
Consider a scenario where you have a missing rainfall reading at a station surrounded by six others. After applying IDW, you notice the estimate is significantly lower than expected. Discuss the possible reasons.
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What external factors could distort data readings?

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