『Abstract
Phosphorus (P) concentration and flow data gathered during the
1990s for a range of British rivers were used to determine the
relative contributions of point and diffuse inputs to the total
P load, using the Load Apportionment Model (LAM). Heavily urbanised
catchments were dominated by sewage inputs, but the majority of
the study catchments received most of their annual phosphorus
load from diffuse sources. Despite this, almost 80% of the study
sites were dominated by point source inputs for the majority of
the year, particularly during summer periods when eutrophication
risk is greatest. This highlights the need to reduce sewage P
inputs to improve the ecological status of British rivers. These
modelled source apportionment estimates were validated against
land-use data and boron load (a chemical marker for sewage).
The LAM was applied to river flow data in subsequent years, to
give predicted P concentrations (assuming to change in P source
inputs), and these estimates were compared with observed concentration
data. This showed that there had been significant reductions in
P concentration in the River Thames, Aire and Ouse in the period
1999 to 2002, which were attributable to the introduction of P
stripping at sewage treatment works (STW). The model was then
used to forecast P concentrations resulting from the introduction
of P removal at STW to a 2 or 1 mg l-1 consent limit.
For the urbanised rivers in this study, the introduction of phosphorus
stripping to a 1 mg l-1 consent level at all STW in
the catchment would not reduce P concentrations in the rivers
to potentially limiting concentrations. Therefore, further sewage
P stripping will be required to comply with the Water Framework
Directive. Diffuse P inputs may also need to be reduced before
some of the highly nutrient-enriched rivers achieve good ecological
status.
Keywords: Nutrient; Eutrophication; Water Framework Directive;
Load Apportionment Model; LOIS』
1. Introduction
1.1. Data set and study area
2. Methodology
2.1. Load apportionment modelling
2.2. Load coefficient descriptions
2.3. Model assumptions and potential errors
2.4. Model predictions
2.5. Model testing
3. Results and discussion
3.1. Phosphorus concentration/flow relationships
3.2. Load apportionment
3.3. Model testing
3.3.1. Correlation of estimated point source load with urban
land-use area
3.3.2. Correlation of estimated point source load with boron
load
3.4. Model predictions
4. Conclusions
Acknowledgements
References