Flood Prediction and Recommendation System

Introduction

Disasters are serious disruptions to society caused by either man-made or natural. They are those who need to be keenly noticed and be made aware of at early stages for society. Prevention is better than cure but to prevent predicting at earlier stages is the most important aspect. Nature is always unpredictable. Nobody or any system can predict nature. Predictions can never be accurate. It's that we can't stop natural disasters but we can arm ourselves with prior knowledge. Creating awareness among every kind of person in society would be the first step to work with. Making even the commoners knowledgeable about the change in climatic conditions that would lead to disasters and the catastrophic damage that they could cause.

There are different types of disasters: wildfires, earthquakes, droughts, hurricanes, floods, and many others shall join the list. These create terrifying catastrophic damage to society. It is said that people who face or live through a disaster can handle emotional distress. This makes people strong mentally. All these days there would have been millions of loss of lives due to sudden natural disasters. Mishaps occur most of the time leading to unrecoverable damage. The effect that it leaves back on society is unimaginable. Fatality or physical injury is the main effect that a flash flood or sudden natural disaster can cause in society. People could lose their homes, possessions, food, and community. Food would be a major problem for the people. The availability of food grains would be scarce and in such conditions, people would face or die of hunger due to the unavailability of food. Therefore, Disasters are a great threat to society that needs to have a discussion.

Predicting their arrival to take preventive measures and protect society from the effects disasters imprint on society is the immediate action that the society needs. Natural disasters are of different types but looking into the particular fact of rains and floods, proper predictionsand preventive actions are needed. Pouring rain is completely unpredictable. But with the historic rainfall data, prediction can be made easy to an extent. In such a way, creating a model with accurate predictions is the utmost need for society.

With the irregular change in climate patterns, it's been difficult to predict the occurrence of floods using traditional methods leading to massive destruction. Thus to cope with flash floods and to handle critical situations new methodologies are invented to overcome such difficulties. Technology has to be more aware to reduce the loss that a flash flood would make. In the modernizing era, it's made even easier to predict the occurrence of floods and recommend nearby evacuation areas. Hazard areas that are prone to destruction and devastating loss are monitored regularly and the rainfall readings are collected, integrated from multiple resources, curated, mined, analyzed and prediction is done over patterns. With the prediction, recommendation areas are listed for the society.

Safety needs to be the utmost goal for any societal issue. Providing safety measures is one of the main aspects for an Engineer and one of the major issues faced by natural disasters. Landslides, earthquakes, floods, droughts, forest fires, and many such factors occur continuously throughout the globe. Natural calamities are unpredictable. People can never judge climate. They leave an ever-recoverable impact on society. They can't be prevented but the effects can be controlled. Going against nature backfires most of the time. Hence agreeing with nature's conditions prevention and protection methods can be taken. Thus, to reduce the effect or impact they cause on the environment, human life, and livestock, predicting the occurrence of natural calamities is one effective way to prepare to fight against them. One such natural calamity is flooding. The main aspect of this work is to create a recommendation system by predicting the arrival of floods using rainfall data. The rainfall data is collected and by analyzing the data, prediction is made using the machine learning algorithm. With the help of the result evacuation areas are recommended in the hazard areas.