Akhila Ram from Lexington, USA is the fifth finalist to be presented for the Children’s Climate Prize 2022

During the fall, the finalists for the Children’s Climate Prize have all been presented and now it’s time for the final one, Akhila Ram, 17 years old from Lexington, USA. Akhila has developed a machine learning model for continuous groundwater monitoring. A solution that has huge potential to create completely new possibilities for planning and monitoring groundwater.

Water scarcity is an increasing problem globally due to climate change, overpumping and poor management. As groundwater is rapidly depleted in many parts of the world, the effects can be catastrophic to local communities, to human health and to the environment. Timely, up-to-date groundwater management is crucial for maintaining the world’s water resources, but current monitoring and data networks are not able to provide sufficient or easily accessible information. Akhila Ram, 17 years old from Lexington, USA wanted to do something about this so she developed a model that uses satellite data to predict detailed changes in groundwater with high accuracy for the United States. A solution that has great potential to be scaled up and have great significance for many people worldwide.

- I am truly honored to be selected as a finalist for the Children's Climate Prize. To win the prize would be an amazing validation of all of the hard work I have put in, says Akhila.

Akhila’s machine learning model has a groundwater monitoring dashboard that utilizes the model predictions to provide an accessible way for everyone to be aware of groundwater trends. With these precise measurements, local officials are equipped with the tools needed to preserve their region’s resources, eliminating excess groundwater depletion.

The winner of the Children's Climate Prize receives a diploma, medal and prize money of SEK 100,000 to continue developing their project. The winner of 2022 will be presented in November.

- I would use the prize money to pay for the article processing costs (APC) of publishing this work in a peer-reviewed journal, purchasing GPU compute to train a larger model, and also towards my college tuition, says Akhila.

Continuous Groundwater Monitoring with Machine Learning
Akhila Ram, 17 years old from Lexington, USA

Jury motivation:
Groundwater monitoring is normally very costly, so Akhila’s solution could create completely new possibilities for planning and monitoring groundwater. Her work is scientifically impressive and the potential scalability of her machine learning model is huge where this kind of data is publicly available. Being able to predict and plan groundwater resources could be useful to both local politicians and to citizens, making a great impact for many.