Water-Energy Model Coupling for Climate-Resilient Hydropower Assessment

Hydropower has the flexibility to support the energy market during low and high seasons through daily and hourly energy demand. However, the future resiliency of hydropower is a function of two main drivers: climate change and power market demand. Most hydropower and their reservoirs have been designed based on the available hydro-climatology and energy market information at the design time or even a few years before commissioning. Due to CC, a new river flow pattern will emerge, and the available water for hydropower generation will be influenced. Furthermore, variations in energy demand and price on the different temporal scales exert more pressure on hydropower operation and ecological conditions downstream in the context of the hydropeaking flow regime. This PhD position focuses on the crucial integration of terrain analysis, energy, and hydrological models to better assess the resilience of hydropower systems against climate change.

We invite applications for a PhD position focusing on developing advanced modeling techniques to enhance the resilience of hydropower systems against climate change. This project aims to integrate terrain analysis, hydrological modeling, GIS (Geographic Information Systems), and energy models to improve hydropower operations’ efficiency, reliability, and sustainability. The successful candidate will contribute to cutting-edge research that addresses critical challenges posed by climate variability and seeks innovative solutions for sustainable energy production.

The ideal candidate will have a Master’s degree in Environmental Sciences, Civil Engineering, Water Resources Engineering, or a related field, complemented by a strong academic record. They should possess solid knowledge of hydrological modeling and the application of GIS in water resources management. A good understanding of the operation mechanisms of hydropower and the challenges posed by climate change is essential. Proficiency in programming languages relevant to environmental modeling, such as Python, R, and MATLAB, is required. Familiarity with energy systems and models will be considered an advantageous asset. The candidate should also exhibit excellent analytical, research, and communication skills, and have the capability to work both independently and as part of a collaborative research team.

SYKE

Water, energy and environmental engineering

Ali Torabi Haghighi

Hannu Martilla

Noora Veijalainen

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