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Project

Factoring Ecological Significance of Sources into Phosphorus Source Apportionment Phase 2

Farmfields

Models describing the relative contributions of phosphorus (P) from different sources to water bodies (source apportionment) are key tools in determining priorities for mitigation strategies within the River Basin Management Planning process under the Water Framework Directive (WFD). Previous source apportionment was simplistic because it was based on total P loads, even though not all P loading has the same ecological significance due to the form or timing of the loading. In 2014, CREW delivered a descriptive methodology of how Total P loads provided by existing catchment models could be modified to take account of their impact on ecology (Factoring Ecological Significance of Sources into Phosphorus Source Apportionment). This modification works each modelled source (e.g. arable drainflow, urban runoff, grassland drainflow) through a sequential set of provided tables to adjust loads from Total P to bio-available P and then account for residence time and dilution potential.

The modifications used in the original project were based on the outputs from the Diffuse Pollution Screening Tool (DPST). Since completion of the initial project, SEPA have received updated and improved source apportionment (ADAS and the source apportionment-GIS (SAGIS) tool). SAGIS quantifies the loads of pollutants to surface waters (derived from the ADAS model) from a range of point and diffuse sources including waste water treatment works, farmland, soil erosion, mining, septic tanks and industry within GIS framework. Ecological significance of P needs to be factored into this new model and validated using monitoring data sets (e.g., diatoms). 

Project Objectives

  1. Assess the feasibility of incorporating the Phase 1 methodology into the new source apportionment framework. This will include a literature review update since Phase 1.
  2. Develop and trial a method to factor the ecologically significant P (Eco-P) emissions into the SAGIS tool.
  3. Validate the SAGIS predictions after factoring in the ecological significance of P sources against P and diatom monitoring data.