UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Predicting surface water critical loads at the catchment scale

Kernan, Martin; (1998) Predicting surface water critical loads at the catchment scale. Doctoral thesis (Ph.D), UCL (University College London). Green open access

[thumbnail of Predicting_surface_water_criti.pdf] Text
Predicting_surface_water_criti.pdf

Download (18MB)

Abstract

Current applications of the critical loads concept are geared primarily towards targeting emission control strategies at a national and international level. In the UK maps of critical loads for freshwaters are available at 10km 2 resolution based on a single representative site in each grid square. These maps do not take variations of water chemistry within mapping units into account and are therefore of limited use for application to non-mapped sites. This thesis describes the development of an empirical statistical model, which uses nationally available secondary data, to predict freshwater critical loads for catchments lacking the appropriate water chemistry information. A calibration exercise using data from 78 catchments throughout Scotland is described. Water chemistry for each catchment has been determined and each catchment is characterised according to a number of attributes. Multivariate statistical analysis of these data shows clear relationships between catchment attributes and water chemistry and between water chemistry and diatom critical load. The key variables which explain most of the variation in critical load relate to soil, geology and land use within the catchment. Using these variables (as predictors) in a regression analysis diatom critical load could be predicted across a broad gradient of sensitivity (R2adj= c.0.8). The predictive power of the model was maintained when different combinations of explanatory variables were used. This accords the model a degree of flexibility in that model paramaterisation can be geared towards availability of secondary data. There are limitations with the model. These relate to the nature of the predictor variables and the ability of the model to predict critical loads for more sensitive sites. Nevertheless the ability of the model to differentiate between sensitive and non-sensitive sites offers considerable scope for environmental managers to undertake national inventories of catchment sensitivity and specific assessments of individual catchments.

Type: Thesis (Doctoral)
Qualification: Ph.D
Title: Predicting surface water critical loads at the catchment scale
Open access status: An open access version is available from UCL Discovery
Language: English
Additional information: Thesis digitised by ProQuest.
Keywords: Applied sciences; Earth sciences; Catchments
URI: https://discovery.ucl.ac.uk/id/eprint/10099909
Downloads since deposit
56Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item