Predictive Capability in Estimating Changes in Water Quality: Long-Term Responses to Atmospheric Deposition

This study reassesses the application of the geochemical model MAGIC in the prediction of long-term changes of water quality in response to changes in atmospheric deposition. It does so within the Monte Carlo based GLUE methodology in which it is possible to evaluate the performance of sets of model parameters in predicting the available observations as a means of constraining the uncertainty in current and future predictions. This work was prompted by previous work which showed that, for a typical upland site in Wales, MAGIC predictions were dominated by the depositional scenario used. Uncertainties in the depositional scenario are taken into account by using estimates of uncertainty for the different depositional sources including European anthropogenic sources as produced by the HARM model. The results show almost no change in predictive uncertainty bounds, in the form of 5th and 95th percentiles of the likelihood-weighted distributions, owing to tight observational data constraints. The implications of this lack of change with respect to predictive capability and possible over-constraint by observed data are discussed.

[1]  Keith Beven,et al.  The use of generalised likelihood measures for uncertainty estimation in high order models of environmental systems , 2000 .

[2]  J. D. Whyatt,et al.  Spatial variability in emissions reduction strategies for sulphur and nitrogen in the UK , 1995 .

[3]  M. D. McKay,et al.  A comparison of three methods for selecting values of input variables in the analysis of output from a computer code , 2000 .

[4]  G. Hornberger,et al.  Modeling the Effects of Acid Deposition: Assessment of a Lumped Parameter Model of Soil Water and Streamwater Chemistry , 1985 .

[5]  R. G. Derwent,et al.  Treating uncertainty in models of the atmospheric chemistry of nitrogen compounds , 1967 .

[6]  George M. Hornberger,et al.  Estimating Uncertainty in Long-Term Reconstructions , 1989 .

[7]  T. Iversen,et al.  The influence of north American anthropogenic sulphur emissions over western Europe , 1992 .

[8]  H. Seip,et al.  Assessing effects of acid deposition in Southwestern China using the magic model , 1991 .

[9]  B. Cosby,et al.  Changes in acidification of lochs in Galloway, southwestern Scotland, 1979–1988: The MAGIC model used to evaluate the role of afforestation, calculate critical loads, and predict fish status , 1994 .

[10]  Keith Beven,et al.  The future of distributed models: model calibration and uncertainty prediction. , 1992 .

[11]  D. Fowler,et al.  An improved wet deposition map of the United Kingdom incorporating the seeder—feeder effect over mountainous terrain , 1992 .

[12]  David S. Lee,et al.  Acid deposition in the United Kingdom 1992-1994 , 1997 .

[13]  Harald Sverdrup,et al.  Calculating critical loads of acid deposition with PROFILE — A steady-state soil chemistry model , 1992 .

[14]  G. Hornberger,et al.  Approach to the preliminary analysis of environmental systems , 1981 .

[15]  Keith Beven,et al.  Multi-objective conditioning of a simple SVAT model. , 1999 .

[16]  S. Mylona,et al.  Sulphur dioxide emissions in Europe 1880–1991 and their effect on sulphur concentrations and depositions , 1996 .

[17]  Keith Beven,et al.  Prophecy, reality and uncertainty in distributed hydrological modelling , 1993 .

[18]  George M. Hornberger,et al.  Modeling the Effects of Acid Deposition: Estimation of Long‐Term Water Quality Responses in a Small Forested Catchment , 1985 .

[19]  C. Neal,et al.  Modelling long term stream acidification trends in upland wales at plynlimon , 1988 .

[20]  D. Fowler,et al.  Acid deposition in Wales: the results of the 1995 Welsh Acid Waters Survey , 1999 .

[21]  J. D. Whyatt,et al.  Developing the Hull Acid Rain Model: its validation and implications for policy makers , 2001 .

[22]  K. Beven,et al.  On constraining the predictions of a distributed model: The incorporation of fuzzy estimates of saturated areas into the calibration process , 1998 .

[23]  Keith Beven,et al.  Investigating the Uncertainty in Predicting Responses to Atmospheric Deposition using the Model of Acidification of Groundwater in Catchments (MAGIC) within a Generalised Likelihood Uncertainty Estimation (GLUE) Framework , 2003 .

[24]  T. Sparks,et al.  Trends and seasonality in stream water chemistry in two moorland catchments of the Upper River Wye, Plynlimon , 1997 .

[25]  R. Spear Eutrophication in peel inlet—II. Identification of critical uncertainties via generalized sensitivity analysis , 1980 .

[26]  K. Beven,et al.  Bayesian Estimation of Uncertainty in Runoff Prediction and the Value of Data: An Application of the GLUE Approach , 1996 .

[27]  A. Robson,et al.  Prediction of future short-term stream chemistry — a modelling approach , 1992 .

[28]  Jane Hall,et al.  Atmospheric inputs and catchment solute fluxes for major ions in five Welsh upland catchments , 1997 .