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| What is GREAT-ER | GREAT-ER Output | Application Examples | Model Validation | What's Next? | |
Model Validation
Validation or 'evaluation' of the GREAT-ER model is an essential and integral element of the project. The overall aim of GREAT-ER is to accurately predict PECs within a factor 2 to 3 as compared to monitoring data at the same site. This implies an unprecedented accuracy for chemical risk assessment models, and experience shows that this can be achieved.
To evaluate the accuracy of GREAT-ER, a 2-year monitoring programme was conducted in the four UK catchments (Yorkshire), in Italy (Lambro) and in Germany (Itter). Over 2000 river water and over 600 waste water treatment effluent samples were analysed for the surfactant LAS and for Boron.
A monitoring programme for the Rupel catchment (Belgium) was done in 2001, and for the Llobregat river (Catalunia) in 2003-2004.
Most catchments released by the GREAT-ER organisations are accompanied by a field validation.
Read more about validation in the GREAT-ER publications and reports listed in the Download Section.
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Validation Example
GREAT-ER simulations were run for the detergent ingredients LAS (Linear Alkylbenzene Sulfonate) and B (Boron) in several catchments. Input parameters (detergent sales, WWTP removal rates, river die-away rates, etc.) were available and fixed by an expert team prior to the simulation. Results show excellent agreement for B (left chart), and very good agreement for LAS (right chart).
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Monitoring Strategy
The stochastic element of GREAT-ER based on multi-year river flow distribution curves requires a monitoring campaign to cover a variety of flow conditions (i.e. wet and dry periods). A random sampling strategy (in time), spread over several months, and with fixed sampling points well distributed over the basin or river is therefore recommended.
GREAT-ER is a steady-state model and in case of intermittent input of chemicals, time-composite sampling is required.
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