Academic journal article Journal of the Statistical and Social Inquiry Society of Ireland

Estimating the Effects of Land-Use and Catchment Characteristics on Lake Water Quality: Irish Lakes 2004-2009

Academic journal article Journal of the Statistical and Social Inquiry Society of Ireland

Estimating the Effects of Land-Use and Catchment Characteristics on Lake Water Quality: Irish Lakes 2004-2009

Article excerpt


Surface water resources have a range of important functions. They provide drinking water, sustain biodiversity and constitute an important tourism and recreation resource. Poor water quality impacts on all of these and, thus, maintaining high water quality has a significant value.

Lake water quality is influenced by a variety of factors, natural and anthropogenic, with the latter often associated with detrimental impacts on quality but being more amenable to intervention. Preventing or remediating pollution damage is costly in resources, whether measured in abatement expenditures or opportunity cost. And while identifying the causes of point source pollution is usually easier than for diffuse sources, the most cost efficient approach to remediation may not necessarily be tackling point sources first. Therefore, understanding the relative contribution of various pollutant sources and their cost of remediation is a crucial input into efficient management.

In the European Union, the Water Framework Directive (CEC, 2000) requires member states to restore polluted water bodies to a minimum of 'good status' by 2015, as well as preventing deterioration in the quality status of all water bodies. The Water Framework Directive (WFD) incorporates concepts of economic efficiency by specifying that certain measures to deliver 'good status' be 'cost effective' or not 'disproportionately costly'.

There is an extensive literature on lake water quality and it is generally acknowledged that phosphorus (P) is often the limiting nutrient determining algal growth in lakes (Schindler, 1977; Sondergaard et al, 2001; Moss et al, 2003). A significant correlation has been shown between soil P and P loss to surface water both internationally (Vadas et al., 2005; Pote et al., 1999; Sharpley et al., 1996) and in Ireland (Tunney et al., 2007; Watson et al., 2007; Styles and Coxon, 2006; Kurz et al., 2005; Daly et al., 2001). The loss of P from soils to water is complex and not all soils are equal in their capacity to lose P to water. For instance, mineral soils, particularly those high in iron and aluminium oxides, and soils with high organic matter are less susceptible to P loss (Jordan et al., 2005; Daly and Styles, 2005; Daly et al., 2001; Maguire et al., 2001).

Agriculture, and in particular livestock farming, is often attributed as a primary source of P loss to water but the literature suggests that the relationship between stocking rate and P loss is site-specific, as is evident from the inconclusive nature of the relationship (Capece et al., 2007; Tunney et al., 2007; Schepers and Francis, 1982). Much of the knowledge of P loss to water is from field or small catchment based studies providing site-specific results and while this type of research has been used to develop nutrient cycling models, such as ANIMO, GLEAMS, DAYCENT, and MACRO, these models (or the necessary data) are not sufficiently detailed to model nutrient export at catchment scale in Ireland (Lewis and McGechan, 2002; Heathwaite et al. (2007); Doody et al. (2012)).

The use of multivariate statistical analyses is an alternative approach for investigating how activities within catchments affect water quality. Donohoe et al. (2006) used a spatial statistical analysis to link catchment characteristics with ecological status of rivers, finding that urbanisation, arable farming and the extent of pasturelands are the principal pressures at catchment scale that impact on ecological quality. From a policy perspective more refined explanatory variables than the percentage of catchments under urban, pasture and arable land is necessary to inform pragmatic policy initiatives. O'Donoghue et al. (2010) also combine spatial datasets to examine economic influences on the ecological quality of water and find that forestry, construction activity, population density, agricultural activity and wastewater treatment methods are critical factors affecting water quality. …

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