Options
Deakin, Jenny
Preferred name
Deakin, Jenny
Official Name
Deakin, Jenny
Research Output
Now showing 1 - 2 of 2
- PublicationNutrient Load Apportionment to Support the Identification of Appropriate Water Framework Directive Measures(Royal Irish Academy, 2016)
; ; ; ; A model for predicting the sources of nutrient loads (phosphorus and nitrogen) to water has been developed to support Water Framework Directive (WFD) implementation. This model integrates catchment data and pressure information to enable characterisation of Source-Pathway-Receptor relationships. The Source Load Apportionment Model (SLAM) is a flexible framework for incorporating national data and research to quantify nutrient losses from both point discharges (urban wastewater, industry and septic tank systems) and diffuse sources (pasture, arable, forestry, peatlands etc.). Hydrogeological controls have a strong impact on nutrient fluxes, particularly in agricultural catchments, and have been incorporated into the diffuse agricultural model, the Catchment Characterisation Tool (CCT). This paper describes the SLAM framework, including the CCT, along with the data inputs and assumptions. Results for the Suir catchment matched the measured loads of nitrogen and phosphorus well, and showed that pasture is the dominant source of nitrogen across all sub-catchments. The main sources of phosphorus in sub-catchments varied between diffuse agriculture, wastewater and industrial discharges. A relatively small proportion (13%) of the Suir catchment area requires a reduction in phosphorus emissions to achieve Good Status. In these areas, model results can be used in conjunction with knowledge from local authorities and investigative assessments gathered through the WFD characterisation process to identify significant pressures that contribute excessive nutrient loads. An example of assessing load reduction scenarios is presented to illustrate how modelling can support catchment scientists and managers in identifying appropriate measures.911Scopus© Citations 11 - PublicationSources of nitrogen and phosphorus emissions to Irish rivers and coastal waters: Estimates from a nutrient load apportionment framework(Elsevier, 2017-12-01)
; ; ; ; ; More than half of surface water bodies in Europe are at less than good ecological status according to Water Framework Directive assessments, and diffuse pollution from agriculture remains a major, but not the only, cause of this poor performance. Agri-environmental policy and land management practices have, in many areas, reduced nutrient emissions to water. However, additional measures may be required in Ireland to further decouple the relationship between agricultural productivity and emissions to water, which is of vital importance given on-going agricultural intensification. The Source Load Apportionment Model (SLAM) framework characterises sources of phosphorus (P) and nitrogen (N) emissions to water at a range of scales from sub-catchment to national. The SLAM synthesises land use and physical characteristics to predict emissions from point (wastewater, industry discharges and septic tank systems) and diffuse sources (agriculture, forestry, etc.). The predicted annual nutrient emissions were assessed against monitoring data for 16 major river catchments covering 50% of the area of Ireland. At national scale, results indicate that total average annual emissions to surface water in Ireland are over 2700 t yr- 1 of P and 82,000 t yr- 1 of N. The proportional contributions from individual sources show that the main sources of P are from municipal wastewater treatment plants and agriculture, with wide variations across the country related to local anthropogenic pressures and the hydrogeological setting. Agriculture is the main source of N emissions to water across all regions of Ireland. These policy-relevant results synthesised large amounts of information in order to identify the dominant sources of nutrients at regional and local scales, contributing to the national nutrient risk assessment of Irish water bodies629Scopus© Citations 99