Space Apps Challenge 2017

Flood Prediction Algorithms

Causes considered:

1. Rivers or any other inland waterbody overflowing.

2. Improper drainage of heavy rainfall due to blocked drains in urban areas.

Algorithm for Cause 1:

1. Input latitude and longitude values of area to be scanned.

2. Divide given area into grids of 1sq km each for individual scanning.

3. Find the least elevation point in each grid using NASA’s earth science data.

4. Find all nearby water bodies from each of these points. (By comparison with a 2d array generated from 1bit map of the world as given here .)

5. For each point measure the difference of elevation between the said point and all nearby water bodies.

6. For each point choose the max of all these differences.

7. Compare the max difference of each point to a predefined set of safety limits that determines the flood risk for each point.

Ex: Consider two predefined static differences of 20m and 40m. Any difference below 20m would low flood risk and above 40 would be high risk. In the middle of both these values would be a medium risk.

8. Code to realize this can be found here .

(The Code has dangling data access lines the purpose of which has been stated in appropriate comments.)

Solution for Cause 2:

1. Place water flow sensors in each major drain outlet in the city.

2. Note a water flow dataset for each outlet under ideal non clogged condition.

3. Compare everyday sensor data to the ideal dataset and measure the difference in water flow.

4. If the difference is far from a predefined safety limits then report to the authorities to clear the drain.

5. This allows the drainage system of the city to work at maximum efficiency to better tackle heavy rainfall conditions.

6. Suggested sensors could be a water level indicator using an Arduino as coded below or an anemometer equivalent for water.

7. Code to realize this can be found here