Practice Missing Rainfall Data – Estimation (10) - Missing Rainfall Data – Estimation

Practice: Missing Rainfall Data – Estimation

Lesson 10Missing Rainfall Data – Estimation

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9 questions

Flashcard drill
4 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
3 questions · about 2 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
Name one cause for missing rainfall data.
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Think about failures.
Question 2.
Why is estimating missing rainfall data important?
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Consider the impact on analysis.
3Question 3.
Which method is appropriate for uniform rainfall?
- Arithmetic Mean Method
- Normal Ratio Method
- Inverse Distance Weighting
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Think about what method averages out data.
4Question 4.
True or False: Data consistency is not important for accurate estimations.
- True
- False
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Reflect on how consistent data supports good results.
Question 5.
Given data from three stations: Station A (100mm), Station B (110mm), Station C (90mm), estimate the missing value for Station D using the Arithmetic Mean Method.
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Look for the average of provided data.
Question 6.
Using the Normal Ratio Method, if Station X has a normal rainfall of 120mm, and your missing station, Station Y, has normals of 90mm and 100mm respectively from two near stations, find the estimated rainfall for Station Y.
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Think about how you can scale the estimated observation against another's normal.

5 more questions in this section. Enroll free to practise them all.