Category
Environmental models
Capabilities
The Eutrophication Risk Model is a process model based on real observations of water biogeochemistry (hourly monitoring of nutrients, flow, temperature and algae) in the River Thames, southern England, to understand thresholds for algal blooms to develop. The UKCEH Load Apportionment Model (LAM) provides inputs to the Eutrophication Risk Model which, for any observed or projected biogeochemical data input, estimates the timing and duration of algal blooms at daily timesteps. It can be used for current river management and to inform future planning based on climate projection data, derived from the UKCEH Future Flows and eFlag climate and river flow datasets.
Lifecycle
The Eutrophication Risk Model was co-developed in 2017 by UKCEH for and with the Environment Agency (EA). Further applications were developed for Thames Water in 2021-22, to inform their Strategic Resource Management including water transfers to the Thames catchment. The model is still being developed and refined by UKCEH.
Uniqueness
The Eutrophication Risk Model is novel and reliable because it is based on real observations and unique understanding of the causes of algal blooms in the River Thames system; and it can be extended to other catchments where adequate data exists.
Partners
The Eutrophication Risk Model was co-developed by UKCEH with the Environment Agency.
Access
Access to the Eutrophication Risk Model was initially restricted to Environment Agency and Thames Water. By late 2023 the model will become open access: available for research use at no cost, with support, by request to the model owner.
Funding sources
Underpinning observations and understanding of algal bloom thresholds were funded by: UKRI-NERC National Capability programmes (ASSIST; UK-SCAPE); Thames Initiative; Endows. Development and application of the Eutrophication Risk Model was funded by: Environment Agency; Thames Water.
Users
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The Eutrophication Risk Model is used by UKCEH researchers with Environment Agency and Thames Water.
Last updated
11 November 2022 16:28
