Dynamic modelling of spatially variable catchment hydrochemistry for critical loads assessment

摘要

Concern about acidification in upland areas has brought about the need to model the stream hydrochemical response to deposition and land-use changes and calculate critical loads. Application of dynamic models such as MAGIC are preferable to steady-state methods, since they are able to produce an estimate of the time scale required to meet some water chemistry target given a reduction in acid deposition. These models typically consider annual changes in stream chemistry at one point. However, in order to protect biota from 'acid episodes', quantification of temporal variability needs to encompass event responses; in addition spatial variability across the catchment also needs to be considered. In this paper, modelling of both spatial and temporal variability is combined in a new framework which enables quantification of catchment hydrochemical variability in time and space. Both low and high flow hydro-chemical variability are quantified in terms of statistical distributions of ANC (Acid Neutralisation Capacity). These are then input as stochastic variables to an EMMA (End-Member Mixing Analysis) model which accounts for temporal variability and ANC is hence predicted as a function of time and space across the whole catchment using Monte-Carlo simulation. The method is linked to MAGIC to predict future scenarios and may be used by iteration to calculate critical loads. The model is applied to the headwaters of the River Severn at Plynlimon, Wales, to demonstrate its capabilities.