I am a Lecturer at Loughborough University (soon moving to the University of Oxford) and my research focuses on understanding and predicting changes in floods and fluvial systems in the context of contemporary shifts in climate and land cover. My approach is statistical and computational; I use a variety of ‘Big data’ sources to disentangle the different drivers of flooding and fluvial change across a variety of climates and land use types. Using Earth Observation and ensemble Climate Model outputs I also develop probabilistic forecasts to assess how floods and fluvial systems may change over a range of timescales. I have a keen interest in data science and in developing new, interdisciplinary methods for understanding and projecting fluvial and hydro-climatic change. On these webpages you will find updates on my current research (below), Publications, Outreach and Media activities, Conference talks, and a short CV.
Pleased to report that our paper,
Lutz, S., Popp, A., van Emmerik, T., Gleeson, T., Kalaugher, L., Möbius, K., Mudde, T., Walton, B., Hut, R., Savenije, H., Slater, L.J., Solcerova, A., Stoof, C., and Zink, M., Science in today’s media landscape – challenges and lessons from hydrologists and journalists.
has just been accepted in Hydrology and Earth System Sciences and can be downloaded here: https://www.hydrol-earth-syst-sci-discuss.net/hess-2018-13/
Pleased to say that our paper has just been accepted in Geophysical Research Letters.
Slater, L.J., Villarini, G. (2018) Enhancing the predictability of seasonal streamflow with a statistical dynamical approach. doi:10.1029/2018GL077945
Key words: Seasonal forecasting, Streamflow, NMME, Precipitation, Temperature, Land cover.
We’re delighted to announce that the ‘Using R in Hydrology’ workshop will be running again (for a second year) at EGU 2018!
Convener: Louise Slater
Co-Conveners: Shaun Harrigan, Claudia Vitolo, Tobias Gauster, Alexander Hurley, Guillaume Thirel.
- Introduction to the short course – Louise Slater
- Accessing hydrological data using web APIs (a demo of the rnrfa package) – Claudia Vitolo
- Extracting netCDF climate data for hydrological analyses (reading and visualising gridded data) – Louise Slater
- Processing, modelling and visualising hydrological data in R (tidyverse; piping, mapping and nesting) – Alexander Hurley
- Hydrological modelling and teaching modelling (airGR and airGRteaching) – Guillaume Thirel
- Typical hydrological tasks in R (List columns, Leaflet and coordinate transformation, Open Street Maps) – Tobias Gauster
The session is aimed at researchers who are interested in hearing more about R as well as those who are advanced R programmers wanting to discuss recent developments in an open environment.
Our two-day workshop in Loughborough on Seasonal Forecasting of Water Resources – Meeting User Needs (24-25 January) was attended by 43 participants from a diverse range of organisations (CEH, ECMWF, EA, SEPA, NRW, NCAS, National Farmers’ Union, Canal & River Trust, SMHI, Civil Protection Agency), water agencies/ consultancies (Anglian Water Services, Scottish Water, CH2M, South West Water Ltd), and universities (Maynooth, Reading, Coventry, Loughborough, Colima, Newcastle, West of England, WSL), with delegates from six countries (UK, Ireland, Mexico, Italy, Switzerland, Sweden). The event was co-sponsored by the RCUK Drought Programme, Water@Loughborough, Water@Reading, and the British Hydrological Society.
We are planning to write a summary of the meeting for the British Hydrological Society’s newsletter Circulation, a Letter to NERC, and an opinion paper.
For more pictures of the event, please see the #SeasonalForecasting hashtag on Twitter!
We have just heard that our NERC/ESRC/DFID proposal on ‘Financial planning for natural disasters: the case of flood risk in Central Java’ was successful.
We will soon be advertising a two-year senior Research Associate (Postdoctoral) position to work on Flood risk and Financial planning (with me), starting early in 2018. Please do get in touch if you are interested. Advanced programming (R or Python) and GIS skills strongly desirable!
I highly recommend using Publons, so all of those reviews don’t go unrecognised…