The UK Centre for Ecology and Hydrology is the Natural Environment Research Council's research centre for freshwater science. UKCEH coordinates internationally leading research and expertise in freshwater sciences and provides infrastructure, training and leadership to the UK hydrological community. The Hydro-JULES programme will build a three-dimensional, open source, community model of the terrestrial water cycle to support and enable collaborative work across the research and academic communities in hydrology and land-surface science.
Coronavirus update: The 2020 summer internship programme has now been CANCELLED due to COVID-19. We plan to run this again in 2021 and will update the website with further details early next year.
The purpose of the Hydro-JULES Summer Student Programme is to allow graduate or 2nd year and upwards undergraduate students to visit UKCEH to work on specific projects with a member of the Hydro-JULES team in one of the following environmental research fields:
- quantification of hydro-meteorological risks,
- using high-resolution climate predictions for hydrological applications,
- calculation the impacts of environmental change on evaporation, transpiration, and soil moisture,
- modelling flood inundation over large areas,
- representing anthropogenic interventions in the water cycle, and
- application of new techniques including Earth observation and data assimilation.
For the duration of their summer internship, up to eight weeks, students will be paid at the B8 rate (£19,700k p.a., pro-rata). Interns from last year said:
I thoroughly enjoyed my summer placement at CEH. As a Physics undergraduate, I really enjoyed using the mathematical skills I already had, to try to understand and pick apart the equations describing a completely new area of science. My supervisor was very supportive of me trying out new things, and so I was able to spend time exploring the things that interested me most. If ever I had a problem, there were always people around keen to help and share their knowledge so I never got too lost! A highlight was presenting my work at the Hydro-JULES conference at the Royal Society, a great opportunity to chat to experts in the Hydrology field and hear about the most up-to-date research. (Eleanor)
The internship really improved my understanding of running complex earth system models and analysing large datasets. This will be invaluable as I take my DPhil further, investigating how future climate and landcover change will impact hydrological systems in the UK. (Marcus)
Applicants should note that:
1. Applicants need a letter of support from their supervisor, tutor, director of studies or equivalent confirming that they are content for the applicant to undertake the proposed summer internship.
2. Funding is not available under this scheme for work included in the core deliverables of the Hydro-JULES programme, which are funded in the normal way.
3. If successful, the applicant will be required to demonstrate that they have the right to work in the UK and must agree to:
- provide a one-page report to the Project Manager describing the visit and its accomplishments within 30 days of completion of the visit;
- appear in publicity and promotion materials for UKCEH;
- acknowledge the support of Hydro-JULES funds in any publications or presentations arising from the visit.
4. Successful candidates will be required to agree the exact dates and duration of their studentship with the supervisor before starting.
Applications must be received by Friday 17th April 2020 and will be considered by the Hydro-JULES Steering Committee soon after the closing date (Please allow up to two weeks for a decision about your application).
To apply, please submit the following information in an e-mail to firstname.lastname@example.org:
- A cover letter explaining briefly your motivation for applying to the programme, and indicating the project(s) for which you wish your application to be considered.
- A short curriculum vitae indicating educational and professional experience, and publications.
- A letter of support from their supervisor, tutor, director of studies or equivalent confirming that they are content for the applicant to undertake the proposed summer internship.
Hydro-JULES Summer Student Projects 2020
1. Studentship to develop inundation mapping techniques for evaluation of Hydro-JULES models over India
Supervisors: France Gerard, Chris Taylor, Doug Clark
Hydro-JULES is developing improved representations of the hydrological impacts of extreme rainfall and fluvial inundation – including new treatments of infiltration, standing water and overbank flooding. There is a need for corresponding observation-based estimates of inundation with which to evaluate our models, particularly on the timescale of a few days over which many extreme events unfold. Similar interests and needs exist in other projects across UKCEH and the wider academic community, including the CASPER project (funded under WCSSP India) which is focused on the development of a coupled land-atmosphere-ocean 4km resolution forecast model over India, and the forecast of hazards associated with extreme events such as tropical cyclones. Preliminary work in CASPER has highlighted a lack of appropriate, off-the-shelf Earth observation (EO) datasets which could be used to evaluate JULES simulations of this process. Existing products are either at a monthly time scale, or require cloud-free conditions rarely met during the Indian monsoon. At the same time, through collaborations with our Indian partner ATREE as part of the KFD project (https://www.monkeyfeverrisk.ceh.ac.uk/about-monkeyfeverrisk, funded under GCRF MRC), the ability of Sentinel-1 SAR to overcome these issues and provide snapshots of sub-monthly inundation has been demonstrated. The aim of this internship will be to apply existing codes for processing Sentinel-1 SAR data, and explore, in collaboration with members of the Hydro-JULES and CASPER project teams, the utility of the resulting inundation maps for evaluating offline JULES simulations. This will involve comparisons with existing EO datasets (e.g. JRC monthly inundation maps, all-weather land surface temperature data) and will feed directly into model development. India is the focus of this studentship, but the aim is to develop methods that can subsequently be employed in other regions. We seek a student who is proficient in coding (python), capable of running existing processing chains involving large datasets on JASMIN, and is enthusiastic about applying those skills to researching the physical environment.
2. Study of rainfall intensity distribution
Supervisors: Eleanor Blyth, Emma Robinson, Elizabeth Cooper, Hollie Cooper
The intensity of rainfall has a strong effect on whether the water gets intercepted by vegetation, infiltrates the soil or just runs off the land into the river system. It is represented in models as a statistical distribution that only varies with rainfall type (convective or large-scale rain). Meanwhile, newly available 1 minute rainfall data from sites all around the UK may give us the essential detail of how this important hydrological variable changes across the country and in different seasons.
This internship will analyse the 1 minute rainfall data from 40 sites across the UK, fitting it to the distribution model of rainfall used the UK weather forecast model. If we have time, we can then quantify the difference this makes to essential hydrological functions of infiltration and interception.
Skills needed: numerate. Undergraduate engineering, geography, physics or maths.
3. UK-wide analysis of surface energy balance and water fluxes
Supervisors: Hollie Cooper, Eleanor Blyth, Ross Morrison
The UK Centre for Ecology & Hydrology (UKCEH) operates a national network of eddy covariance (EC) stations under the ASSIST and UK-SCAPE research programmes. This network delivers direct and continuous observations of water, energy and CO2 fluxes in near real-time from a range of ecosystem types (croplands, grasslands, peatlands) distributed across the UK. In summer 2019, data from the EC flux tower network were augmented with new a surface energy balance dataset derived from micrometeorological measurements collected by the national COSMOS-UK soil moisture network. Collectively, this dense network of stations represents a globally unique resource to advance knowledge on the spatial and temporal dynamics and drivers of land surface energy and water balance. In this project, the student will: (i) process, quality control and analyse observational data from eddy covariance and COSMOS-UK sites; (ii) derive a long term (2013 to 2020) surface energy balance dataset; (iii) use flux observations to validate the JULES land surface model and/or remotely-sensed (e.g. MODIS) data products; and (iv) contribute to scientific and technical publications. The student must have experience with a scientific programming language (ideally R and/or Python). Familiarity with the eddy covariance technique is desirable but not essential as training can be provided by UKCEH scientists.
4. Using data assimilation to improve soil moisture predictions
Supervisors: Rich Ellis, Elizabeth Cooper
Accurate soil moisture predictions are fundamentally important in a number of areas including agriculture, flood forecasting, and climate and weather systems. Land surface models such as the Joint UK Land Environment Simulator (JULES) make predictions of soil moisture, and JULES is used as part of the UK weather forecasting system. The UKCEH COSMOS-UK network now provides a new and exciting dataset of soil moisture measurements across the UK mainland, making use of innovative Cosmic Ray Neutron Sensors.
This project would build on a system which uses data assimilation to combine soil moisture predictions from the JULES model with observations from the COSMOS-UK network in order to improve soil moisture predictions, but also to better understand the representation of soil-water physics processes in the JULES model. The project would involve using an existing data assimilation test-bed to examine the sensitivities of soil moisture forecasts to different assumptions in the model and observations.
The candidate would work closely with hydrologists and land modellers and would require experience working with a unix-like system (linux / ios) and the python programming language.
5. Data Assimilation for Improved Seasonal Hydrological Forecasting
Supervisors: Katie Smith, Michael Eastman
Seasonal hydrological forecasts are hugely beneficial for water resources management, particularly during periods of prolonged extreme weather. The UK has experienced two major drought events in the last decade that have terminated with periods of unusually persistent rain, resulting in severe flooding. In order to forecast water availability, hydrological models are employed, either driven by seasonal meteorological forecasts, or by ensembles of past climate data (known as Ensemble Streamflow Prediction, ESP; Day et al., 1985). The use of hydrological models brings inherent uncertainties, including the assignment of model parameter values, and uncertainties in the observed data. We have identified that hydrological models, even when calibrated to provide satisfactory river flow estimates over the observed past, can suffer from biases in the flow values simulated at the start of the forecast (initial conditions). Recent research has advanced several methods of data assimilation (DA), that can improve model initial conditions, thus improving the skill of the forecast (Liu et al., 2012).
Therefore, the aims of this project are to:
- Identify DA technique(s) that are appropriate for seasonal hydrological forecasting in the UK, and
- Test them on the existing Hydrological Outlooks UK ESP forecasting system (Harrigan et al 2016) for a number of UK catchments.
This research will inform future applications of the Hydro-JULES modelling framework in seasonal hydrological forecasting. It is also hoped that the outputs of this research will be applied directly to improve the forecasts produced for the UK Hydrological Outlook, making use of newly available access to Environment Agency real-time river flow data.
The student will require good numeracy/statistical skills, experience using the R programming language, and an undergraduate degree in earth/environmental sciences or other relevant scientific discipline.
Day, G. N.: Extended Streamflow Forecasting Using NWSRFS, J. Water Resour. Plan. Manag., 111, 642–654, 1985
Harrigan, S., Prudhomme, C., Parry, S., Smith, K., and Tanguy, M.: Benchmarking ensemble streamflow prediction skill in the UK, Hydrol. Earth Syst. Sci., 22, 2023–2039, https://doi.org/10.5194/hess-22-2023-2018, 2018.
Liu, Y., Weerts, A. H., Clark, M., Hendricks Franssen, H.-J., Kumar, S., Moradkhani, H., Seo, D.-J., Schwanenberg, D., Smith, P., van Dijk, A. I. J. M., van Velzen, N., He, M., Lee, H., Noh, S. J., Rakovec, O., and Restrepo, P.: Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities, Hydrol. Earth Syst. Sci., 16, 3863–3887, https://doi.org/10.5194/hess-16-3863-2012, 2012.