Kunal Anil Rustagi, Vipul Gote, Mahesh Mote, Jayesh Kothawade, Varsha Patil

Since ages, we know that rainfall is a very important factor in deciding the fate of a country. In an agrarian country like India where more than 70% of rural households are dependent on agriculture, agriculture contributes to nearly 17% GDP of the country and is directly dependent on rainfall. Excessive rainfall can lead to floods, landslides, soil erosion and no rainfall can lead to drought-like conditions. Too much or too little rain can cause great havoc to the farmers. In order to prevent this damage to land and crops, rainfall prediction is the need of the hour. It can help us in future planning and preparing for the worst condition i.e. natural calamities like cloudbursts, floods, etc., thereby saving human life, vegetation, flora and fauna. Infrastructural losses worth billions can be avoided. In this paper, we tried to use one of the models provided in the rainymotion open-source library to predict rainfall in the nowcasting mode. The model is based on optical flow, a simple digital image processing technique, which tries to gauge the motion of the pixels, thereby creating a velocity field which is finally used to extrapolate the results. Using some verification methods, we have tried to predict the rainfall movement for over 60 to 80 minutes.