Part 1: Project Overview & Architecture

1. Project Overview

1.1 Welcome & Introduction

Floods are among the most devastating natural disasters, claiming thousands of lives and displacing millions every year. Traditional flood warning methods often fail to analyze complex atmospheric changes in time, resulting in delayed advisories.

Rising Waters is a machine learning-powered Flood Prediction System that resolves this challenge. By analyzing regional weather variables—such as temperature, relative humidity, cloud cover, and seasonal rainfall offsets—the system calculates the exact probability of a flood event. Early predictions enable disaster relief coordinators and local authorities to issue evacuation advisories, mobilize resources, and save lives.

1.2 System Architecture Flow Diagram

Here is how data flows through the application:

graph TD
    A[1. flood_prediction.csv Dataset] --> B[2. Data Cleaning & Jupyter EDA]
    B --> C[3. StandardScaler Scaling & train.py comparison]
    C --> D[4. Save Models & Scalers as Joblib files]
    D --> E[5. Flask Web Server app.py]
    E --> F[6. HTML/CSS/JS Frontend Form UI]