Dynamic modelling of spatially variable catchment hydrochemistry for critical loads assessment

Concern about acidification in upland areas has brought about the need to m odel the stream hydrochemical response to deposition and land-use changes a nd calculate critical loads. Application of dynamic models such as MAGIC ar e preferable to steady-state methods, since they are able to produce an est imate of the time scale required to meet some water chemistry target given a reduction in acid deposition. These models typically consider annual chan ges in stream chemistry at one point. However, in order to protect biota fr om 'acid episodes', quantification of temporal variability needs to encompa ss event responses; in addition spatial variability across the catchment al so needs to be considered. In this paper, modelling of both spatial and tem poral variability is combined in a new framework which enables quantificati on of catchment hydrochemical variability in time and space. Both low and h igh flow hydro-chemical variability are quantified in terms of statistical distributions of ANC (Acid Neutralisation Capacity). These are then input a s 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 b y iteration to calculate critical loads. The model is applied to the headwa ters of the River Severn at Plynlimon, Wales, to demonstrate its capabiliti es.