The hydrological and biogeochemical processes that operate in catchments
influence the ecological quality of freshwater systems through delivery
of fine sediment, nutrients and organic matter. Most models that seek to
characterise the delivery of diffuse pollutants from land to water are
reductionist. The multitude of processes that are parameterised in such
models to ensure generic applicability make them complex and difficult
to test on available data. Here, we outline an alternative - data-driven
- inverse approach. We apply SCIMAP, a parsimonious risk based model
that has an explicit treatment of hydrological connectivity. we take a
Bayesian approach to the inverse problem of determining the risk that
must be assigned to different land uses in a catchment in order to
explain the spatial patterns of measured in-stream nutrient
concentrations. We apply the model to identify the key sources of
nitrogen (N) and phosphorus (P) diffuse pollution risk in eleven UK
catchments covering a range of landscapes. The model results show that:
1) some land use generates a consistently high or low risk of diffuse
nutrient pollution; but 2) the risks associated with different land uses
vary both between catchments and between nutrients; and 3) that the
dominant sources of P and N risk in the catchment are often a function
of the spatial configuration of land uses. Taken on a case-by-case
basis, this type of inverse approach may be used to help prioritise the
focus of interventions to reduce diffuse pollution risk for freshwater
ecosystems. (C) 2012 Elsevier B.V. All rights reserved.