Céline Cattoën-Gilbert


National scale flood forecasting in the world of data, models, HPC and AI – shaping a more resilient tomorrow.
Flooding is the most frequent natural disaster in New Zealand. Two trends have recently emerged in the development of new flood forecasting systems: i) a shift from deterministic to ensemble (probabilistic) streamflow predictions, and ii) a move towards national/continental scale systems that attempt to forecast flows for all streams over a given domain. We will present a selection of NIWA’s work on forecasting flood and hazards, including key aspects of the development of a national short-term flow forecasting system prototype for New Zealand rivers (0-2 days).  The forecast system, running on HPC, is updated every 6 hours and produces river flow forecasts for nearly 60,000 rivers across the hydrologically diverse New Zealand environment. National scale forecasting systems require complex automated workflows, with data assimilating models, and uncertainty quantification techniques.  We will highlight some of the key science and technical challenges of this work, and the role of data, models, HPC and AI, in shaping a more resilient tomorrow.

Dr. Céline Cattoën-Gilbert is a hydrological forecasting scientist at NIWA, a principal investigator of a 2017 Natural Hazards Research Platform fund for “Enhanced probabilistic flood forecasting”, and since 2016, the leader of “floods and hazards”, a NIWA strategic science investment fund.
In 2017, she obtained a NIWA Excellence Awards for Early Career Science runner-up. With an engineering degree in applied mathematics, PhD in theoretical physics, and experience as an HPC support consultant (NeSI) before joining NIWA, she has a passion and drive for interdisciplinary research.
She enjoys developing an active role in the international ensemble flow forecasting research community as science committee member and session co-organiser in conferences (HEPEX, EGU, MODSIM), and more recently as a visiting scientist at IRSTEA in France.

She’s delighted to present her and her team’s exciting work on the NZ river flow forecast research project producing hourly forecast for the next 48 hours, for nearly 60,000 rivers across New Zealand.

Dr Anushia Inthiran


Dr Anushia Inthiran is a senior lecturer in the Department of Accounting and Information Systems at the University of Canterbury. She teaches various information systems subjects ranging from knowledge management to electronic commerce and system development at the undergraduate and postgraduate level. She also supervises postgraduate applied research projects and students conducting PhD research studies. Her research interests lie in interdisciplinary areas of health informatics, human computer information retrieval and human computer interaction. Anushia was awarded the Fundamental Research Grant Scheme by the Malaysian government as Primary Investigator in 2013. This research grant allowed her and her team to examine the information search behaviour of physicians during the practice of evidence based medicine. In 2016, she was awarded the SEED grant as primary investigator which allowed her to use eye tracking technology to describe how older adults view online health webpages. Anushia is an alumna of the New Zealand Women in Leadership Programme.

Roger Moraga & Tammy Steeves 

Roger Moraga graduated from the Autonomous University of Madrid with a degree in Molecular Biology, and entered the world of Bioinformatics through the side door with a Masters. He has been working with High-Throughput sequencing data for more than a decade, and nowadays spends most of his time assembling, reassembling, and playing with the genomes of endangered New Zealand species.

My research interests focus on the ecological and evolutionary processes that contribute to the formation and maintenance of species boundaries, and the application of this knowledge to enhance the recovery of species at risk. I co-lead the Conservation, Systematics and Evolution Research Team (ConSERT) at Te Whare Wānanga o Waitaha/University of Canterbury. In partnership with relevant Māori (indigenous peoples of Aotearoa New Zealand) tribes (iwi or hapū) and in collaboration with conservation practitioners, we use genomic and non-genomic data to co-develop conservation genetic management strategies for some of Aotearoa New Zealand’s rarest taonga (treasured) species.

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