Hydro_Compound

This repository contains the main scripts to analyse the impacts of hot-dry compound events on hydropower production in Switzerland.

This is achieved using the following steps:

1. We first use machine learning methods to reconstruct long-term time series of hydropower production.
2. Secondly, a probabilistic approach is then used to study how hydropower production reacts to hot and dry weather conditions under current climate conditions.
3. As a final step, the machine learning models are fed with future climate projections and future discharge to obtain projections of hydropower production over the coming century, allowing us to study not only how hydropower production might change as a result of climate change, but also how the impact of hot and dry weather conditions on this production might evolve in the future.

More details about the methodology and results can be found in the paper: https://iopscience.iop.org/article/10.1088/1748-9326/acd8d7.