Cite this dataset as
Radbourne, A.D.; Elliott, J.A.; Maberly, S.C.; Ryves, D.B.; Anderson, N.J. (2018). Potential future scenarios of nutrient and climate change using the model PROTECH at Rostherne Mere, Cheshire, UK (2016-2100). NERC Environmental Information Data Centre. https://doi.org/10.5285/2f0eae1c-1512-4823-9cbe-cb54f05ee996
Import this citation into your reference management software:
BibTeX | Reference Manager (RIS) | Endnote
This dataset will be available under the terms of the Open Government Licence 
This dataset includes the PROTECH validation output against a yearlong monitoring study conducted during 2016 in the lake and catchment of Rostherne Mere and the PROTECH output files following changes in internal and external nutrient loads and future climate scenarios based on the UK Climate Projections (UKCP09) data. These data were collected to demonstrate the future possible trajectories of change with alterations in air temperature, internal nutrient loads and external nutrient loads. Validation data is presented as daily model outputs, while all future projection data is presented as collated annual average model output data for each future change scenario.
The PROTECH model (Phytoplankton RespOnses To Environmental CHange) simulates the in situ dynamics of phytoplankton in lakes and reservoirs, specialising in predicting phytoplankton species, particularly Cyanobacteria (blue-green algae)
The work was carried out as part of a Natural Environment Research Council (NERC) funded PhD [grant number NE/L002493/1].
Publication date: 2018-08-09
This dataset is part of the following
Between January 2016 and January 2017, water samples from the lake (surface and at depth) and catchment were collected approximately every three weeks for analysis of phosphorus, nitrogen, silicate and phytoplankton concentrations. Furthermore, inflow and outflow discharge rates were calculated for conversion of nutrient concentrations into total loads. PROTECH simulates the responses of a number of phytoplankton populations distributed in a 1 dimensional vertical water column at daily time steps, but also calculates key physical limnological parameters such as thermocline development, stratification pattern and nutrient concentrations. The model was run and compared to the observed data recorded from the lake during 2016 to first validate to model, then to re-run the calibrated 2016 simulation as a baseline with progressive changes to air temperature and nutrient load. The data was collated to Excel spreadsheets held by the lead author at Loughborough University.
For ingestion into the Environmental Information Data Centre data was converted from Excel spreadsheets to comma separated files.
https://orcid.org/0000-0003-3167-5783