How AI is Improving Global Access to Reliable Flood Forecasts
Posted: Sat Mar 23, 2024 1:51 pm
Hello HONOR Fam!
I'm back with another interesting topic to discuss,
In this blog, we'll delve into how Google's innovative use of artificial intelligence (AI) is quietly revolutionizing the way we predict and prepare for floods. Let's discover how these advancements are not only making flood forecasts more accurate but also more accessible to vulnerable communities around the globe.
Introduction:
- Floods pose significant challenges globally, with annual financial damages exceeding $50 billion, driven partly by climate change.
- Around 1.5 billion people, constituting 19% of the global population, face substantial risks from severe flood events.
- Strengthening early warning systems is crucial for mitigating these risks and saving lives.
Innovative Flood Forecasting Initiative:
- Google initiated a comprehensive flood forecasting effort in 2017, focusing on developing accurate and accessible forecasting systems.
- Collaborations with diverse partners, including academia, governments, international organizations, and non-profits, have been integral to this initiative.
- A real-time operational flood forecasting system has been integrated into various Google platforms, such as Search, Maps, Android notifications, and the Flood Hub.
- Published groundbreaking research in Nature, showcasing the transformative potential of machine learning (ML) in enhancing global-scale flood forecasting.
- ML technologies have significantly extended the reliability of global nowcasts, providing forecasts up to five days in advance on average and matching European standards in regions with limited data.
- The Flood Hub now delivers real-time river forecasts up to seven days ahead, covering over 80 countries.
Revolutionary Hydrological Models and ML Integration:
- ML-driven hydrological models, particularly those based on LSTM neural networks, have outperformed traditional models, ensuring more accurate flood forecasts.
- Collaborations with academic institutions have led to the development of sophisticated methods for uncertainty estimation in river forecasts and data synthesis from multiple sources.
- In a commitment to open science, a community-driven dataset for large-sample hydrology was released in Nature Scientific Data in 2023.
State-of-the-Art River Forecast Model:
- The river forecast model leverages LSTM neural networks sequentially to predict river floods, incorporating historical and forecasted meteorological data, static watershed attributes, and daily streamflow values for training.
- Comparative assessments have demonstrated comparable or superior accuracy to GloFAS, the current global flood forecasting standard.
- Google's flood forecasting endeavor is aligned with its broader Adaptation and Resilience initiatives, aimed at addressing climate change and bolstering global community resilience.
- Collaborations with international aid organizations and the World Meteorological Organization (WMO) are ongoing to provide actionable flood forecasts and support early warning systems.
- Future endeavors include expanding global flood forecasting coverage, integrating additional flood-related event types, and sustained collaboration with partners to realize these objectives.
How we are using AI for reliable flood forecasting at a global scale
- AI helps provide more accurate riverine flood information up to 7 days in advance.
- Flood forecasting is now available in 80 countries, covering 460 million people.
- AI-based forecasting improves flood predictions in regions with scarce data.
- Flood Hub platform provides free real-time forecasts to vulnerable communities.
- Collaboration with academia, governments, and organizations is key to advancing flood forecasting.
Thank You
Aarya Bhavsar