FloodGuard: Integrating Rainfall Time Series and GIS Data for Flood Prediction and Waterbody Forecasting in Bangladesh

This Omdena Local Chapter Challenge runs for 8 weeks and is a unique experience to try and grow your skills in a collaborative and safe environment with a diverse mix of people from all over the world. 

You will work on solving a local problem, initiated by Bangladesh Chapter.

The problem

The aftermath of flooding in Bangladesh results in immediate and long-term challenges, including loss of lives, destruction of crops, damage to infrastructure, and displacement of communities. Timely and accurate flood prediction and waterbody forecasting are crucial for reducing the impact of floods, enabling better disaster preparedness, and facilitating effective resource allocation.

The goals

The goal of this project is to leverage time series rainfall data and Geographic Information System (GIS) data to develop a predictive model that can forecast flood occurrences and waterbody behavior across Bangladesh. The project will involve collecting open-source rainfall data and GIS data, performing exploratory data analysis (EDA), training predictive models, and developing an application to provide alerts and forecasts to residents in proximity to water bodies.

Why join? The uniqueness of Omdena Local Chapter Challenges

Omdena Local Chapter Challenges are not a competition or hackathon but a real-world project that will grow your experience to a new level. A unique learning experience with the potential to make an impact through the outcome of the project. You will go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment. And the best part is that you will join the global and collaborative community of Omdena with tons of benefits to accelerate your career.

Read more on how Omdena´s Local Chapters work