Snow acts as a natural seasonal reservoir across many regions of the world. Water that falls as snow can be stored through winter and often released later during spring and summer, sustaining river flows, ecosystems, hydropower and water supplies. As the climate warms, however, more precipitation may fall as rain, snow melt timing may change, and seasonal snowpacks are changing in coverage. These changes are already widespread, but their consequences for rivers and water resources are surprisingly difficult to understand.
A key reason is that losing the same amount of snow does not have the same effect everywhere. In some catchments, large areas of the landscape lie close to the climatic boundaries, meaning that even modest warming can fundamentally change how water is stored and released. Elsewhere, snow occurs mainly at high elevations and may be less sensitive. Groundwater, lakes and other catchment stores can further buffer, or even amplify, the effect of changing snowmelt on river flow.
This PhD will investigate when and where changes in snow translate into important changes in river runoff and water availability. It will build on major Northern Hemisphere snow datasets and analysis framework published and developed by the supervisory team and collaborators, combining these with additional large datasets on climate, landscape, and river discharge.
The PhD students will be able to examine a large spectrum of snow observations and river catchments spanning contrasting climates and mountain environments. They will be able to directly test how landscape, temperature gradients, precipitation patterns and water-storage characteristics control the sensitivity of snow accumulation, melt timing and seasonal runoff to warming.
The broad structure of the project will be to progress from observed relationships to new conceptual frameworks and future climate experiments, with plenty of scope for incorporating individual student interests within this. This project will not rely only on complex hydrological simulations, but rather seek simple and transferable explanations for why some rivers are much more vulnerable to declining snow than others.
This project will provide an exciting opportunity for a PhD student interested in working on new frameworks for identifying the snow sensitivity of river systems and emerging water resource hotspots under climate change, with relevance from local catchment management to continental and hemispheric scale assessments of future water availability.
This project does not offer a CASE studentship
Each host has a slightly different application process.
Find out how to apply for this studentship.
All applications must include the CENTA application form.
Choose your application route
This project will combine large observational datasets, geospatial analysis and some simple hydrological modelling. Existing Northern Hemisphere snow datasets developed by the research team will be linked with gridded climate data, digital elevation models and large river-flow datasets. Catchment hypsometry and other landscape characteristics will be derived using GIS and Earth-observation products. Statistical analyses will identify how snow accumulation, melt timing and river-flow seasonality vary across climate and topographic gradients. The student will be able to compare a hierarchy of models, from simple elevation-based snow and runoff representations to established catchment models, to determine which processes are required to reproduce observed sensitivity. Controlled warming and precipitation experiments will be used to identify thresholds and nonlinear responses before applying future climate projections. Results will be tested across contrasting catchment datasets and regions to assess how transferable the resulting relationships are.
DRs will be awarded CENTA Training Credits (CTCs) for participation in CENTA-provided and ‘free choice’ external training. One CTC can be earned per 3 hours training, and DRs must accrue 100 CTCs across the three and a half years of their PhD.
The student will gain advanced training in hydrology, snow and climate science, Python/R programming, GIS, Earth observation, statistical analysis and environmental modelling. They will learn to manage and analyse very large environmental datasets and work with climate-model and reanalysis products. Training will also cover reproducible research, uncertainty analysis, scientific visualisation and communication. There will also be a priority on attending relevant conferences and workshops, both for expanding networking and scientific communication skills.
Through established international collaborations in snow and hydrology research, the student will have extensive opportunity to engage with (and potentially visit) researchers working across snow hydrology, catchment science and climate impacts, providing opportunities for research visits, conference participation and collaborative publication.
Year 1: Where and when does snow matter? This year will assemble snow, climate, river datasets, characterise catchment DEMs and snow regimes, establish observed relationships among elevation, climate, snow storage and runoff seasonality.
Year 2: What controls sensitivity? This year will broadly develop and test the landscape framework, quantify snow accumulation and melt sensitivity to warming, compare theory with observed catchment behaviour, identify important departures caused by precipitation patterns, groundwater and other storage.
Year 3: From snow change to river-flow change. This year will develop the runoff-response framework, analyse thresholds and nonlinearities, classify catchments according to snow and hydrological sensitivity.
Fontrodona-Bach, A., Schaefli, B., Woods, R., Teuling, A.J. and Larsen, J.R. (2023) NH-SWE: Northern Hemisphere Snow Water Equivalent dataset based on in situ snow depth time series, Earth System Science Data, 15, pp. 2577–2599. doi:10.5194/essd-15-2577-2023.
Fontrodona-Bach, A., Schaefli, B., Woods, R. and Larsen, J.R. (2026) Estimating robust melt factors and temperature thresholds for snow modelling across the Northern Hemisphere, Hydrology and Earth System Sciences, 30, pp. 2613–2636. doi:10.5194/hess-30-2613-2026.
Berghuijs, W.R., Woods, R.A. and Hrachowitz, M. (2014) A precipitation shift from snow towards rain leads to a decrease in streamflow, Nature Climate Change, 4, pp. 583–586. doi:10.1038/nclimate2246.
Barnett, T.P., Adam, J.C. and Lettenmaier, D.P. (2005) Potential impacts of a warming climate on water availability in snow-dominated regions, Nature, 438, pp. 303–309. doi:10.1038/nature04141
For any enquiries related to this project please contact Joshua Larsen, University of Birmingham, [email protected].
To apply to this project:
Applications must be submitted by 23:59 GMT on Wednesday 6th January 2027.