Practice Inverse Distance Weighting Method (IDW) - 10.4.3 | 10. Missing Rainfall Data – Estimation | Hydrology & Water Resources Engineering - Vol 1
K12 Students

Academics

AI-Powered learning for Grades 8–12, aligned with major Indian and international curricula.

Professionals

Professional Courses

Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.

Games

Interactive Games

Fun, engaging games to boost memory, math fluency, typing speed, and English skills—perfect for learners of all ages.

Typing
Memory
Math
English Adventures
Knowledge

10.4.3 - Inverse Distance Weighting Method (IDW)

Enroll to start learning

You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is the main purpose of the Inverse Distance Weighting Method?

💡 Hint: Think about why geographic distance matters.

Question 2

Easy

Explain why IDW uses distance squared in its formula?

💡 Hint: What happens to weight when distance increases?

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

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

💡 Hint: Remember how distance affects the influence of station data.

Question 2

IDW may not function well in regions with significant what?

  • True
  • False

💡 Hint: Think of areas with hills, valleys, or varied elevations.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

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.

💡 Hint: What does the IDW formula tell you about weighting?

Question 2

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.

💡 Hint: What external factors could distort data readings?

Challenge and get performance evaluation