HIL Seminars
Influence of El Niño Southern Oscillation on global hydropower production
Stefano Galelli
Assistant Professor, Singapore University of Technology and Design
DEIB - Seminar room
December 20th, 2016
11.30 am
Contact:
Matteo Giuliani
Research Line:
Planning and management of environmental systems
Stefano Galelli
Assistant Professor, Singapore University of Technology and Design
DEIB - Seminar room
December 20th, 2016
11.30 am
Contact:
Matteo Giuliani
Research Line:
Planning and management of environmental systems
Sommario
On December 20th, 2016 at 11.30 am, "Influence of El Niño Southern Oscillation on global hydropower production" seminar will take place at DEIB Seminar Room, as new appointment of HIL Seminars.
El Nin~o Southern Oscillation (ENSO) strongly influences the global climate system, manifesting in periodic droughts and floods across many regions of the world. Whist the impacts of ENSO on precipitation and runoff have been studied extensively, the effects on global hydropower production remain unclear. To assess these impacts, we simulate the operations and storage dynamics of about 1,600 hydropower dams, representing more than half of the world’s existing hydropower capacity. Results show that approximately 35% of the world’s hydropower dams exhibit reliable anomalies in power production in at least one of the two ENSO phases of El Nin~o and La Nin~a. When aggregated at the global level, positive and negative anomalies effectively cancel each other out, resulting in a weak and statistically insignificant global-scale anomaly in hydropower production for both ENSO phases. Negative anomalies in inflows resulting from ENSO are often weakened in the hydropower production time series, indicating the role of long-memory reservoirs in smoothing the effects of climate variability.
Further information is available at http://us13.campaign-archive2.com
El Nin~o Southern Oscillation (ENSO) strongly influences the global climate system, manifesting in periodic droughts and floods across many regions of the world. Whist the impacts of ENSO on precipitation and runoff have been studied extensively, the effects on global hydropower production remain unclear. To assess these impacts, we simulate the operations and storage dynamics of about 1,600 hydropower dams, representing more than half of the world’s existing hydropower capacity. Results show that approximately 35% of the world’s hydropower dams exhibit reliable anomalies in power production in at least one of the two ENSO phases of El Nin~o and La Nin~a. When aggregated at the global level, positive and negative anomalies effectively cancel each other out, resulting in a weak and statistically insignificant global-scale anomaly in hydropower production for both ENSO phases. Negative anomalies in inflows resulting from ENSO are often weakened in the hydropower production time series, indicating the role of long-memory reservoirs in smoothing the effects of climate variability.
Further information is available at http://us13.campaign-archive2.com
Biografia
Dr. Stefano Galelli graduated in Environmental and Land Planning Engineering at Politecnico di Milano in 2007, and received a Ph.D. in Information and Communication Technology from the same university in early 2011. Before joining SUTD as Assistant Professor, he spent two years as Post-Doctoral Research Fellow at the Singapore-Delft Water Alliance (National University of Singapore), where he led the Hydro-informatics group. Dr. Galelli was visiting scholar at MIT (US), Deltares (NL) and University of Western Australia. He is a member of Environmental Modelling & Software editorial board; he also serves as Associate Editor for the Journal of Water Resources Planning and Management. He received the Early Career Research Excellence Award (2014) by the international Environmental Modelling & Software society, and the Outstanding Reviewer Award by the Journal of Water Resources Planning and Management (2015) and Environmental Modelling & Software (2011). He collaborates with several universities and research institutes, including MIT, Technion, CSIRO and National University of Singapore.
