In terms of human health, the main concerns about water pollution relate to contamination in drinking water.  In Europe, where the vast majority of households are served by piped water, this puts the focus on public water supplies.  It is nevertheless important ro remember that exposures to contaminants do not only occur by drinking treated water; showering and bathing, swimming (in both treated pools and in lakes, rivers or the sea), and water handling (e.g. for irrigation) can all be responsible for significant exposures.  In addition, water supply to the tap is merely the last link in a long chain, which draws water from a range of natural sources, including surface and groundwaters.  Opportunities for contamination occur throughout this chain. 

Approaches to modelling

Models of water quality are therefore concerned with trying to estimate and simulate the processes involved from initial source (e.g. as rainfall) to ultimate exposure.  Three main elements of this chain are of particular importance, and because the processes involved in each case are somewhat different each tends to be associated with different types of model:

1. Surface runoff
2. Groundwaters
3. Treatment and public supply

In each case, different approaches to modelling may be used. 

Statistical models, derived from the analysis of measured data in a sample of locations, are often applied to give relatively simple predictions of variations in water quality either through time or over space.  These use empirically observed relationships between measured pollutant concentrations at sample locations (or times) and characteristics of the surrounding environment (e.g. land cover/use, soils, stream discharge, meteorology) as a basis for predicting variations in pollutant concentrations either through time or over space.   Where the focus is on predicting spatial patterns, models are often constructed in GIS, in order to facilitate data linkage, analysis and mapping. 

Process models have widely been developed for engineering purposes (i.e. to help manage water supplies).  These attempt to simulate the processes operating within the hydrological system, and often comprise a number of linked sub-models, representing the different compartments of the system - e.g. the soil, surface runoff and stream in the case of surface water.   They also tend to involve two different types of model: hydrological models which describe the processes by which precipitation passes into and through the water body (e.g. the stream or aquifer); and solute models which describe the processes by which contaminants are released into or picked up by the water, en route.   A large number of models serving part or all of these processes have been developed.

In general, statistical models have the advantage of simplicity and ease of application, but may be less reliable as a basis for prediction beyond the realm of the measured data on which they are based.  Process models are more robust in this respect, but they are relatively complex and have somewhat daunting data demands: lack of the relevant input data, or uncertainties in the data that do exist, may therefore be significant limitations.  Care is also needed, because most models have been developed to represent specific environmental conditions (e.g. climate, topography, land use, geology or soil types), and may not be applicable in other contexts.  In an attempt to exploit the differing advantages of both approaches, hybrid models, comprising both statistical and process-based elements, are also often used.