Challenges and Limitations of Using Monitoring Data in Catchment-Based Models—A Case Study of Rivers Taw and Torridge, UK

Water quality monitoring is a key requirement for fulfilling various national environmental policies, but with many competing needs and limited resources, data collected can suffer from both spatial and temporal deficiencies. Modelling offers the potential to substitute estimated values into observational gaps, but model validation often requires the very data that are lacking. In this paper we present the results of a pilot study to investigate spatial and temporal issues around the monitoring of faecal indicator bacteria (Escherichia coli) in rivers of the Taw and Torridge catchments in the UK. Statistical analysis of in situ measurements versus simulated data from the catchment models reveals similar seasonal associations between riverine bacterial counts and rainfall patterns. Furthermore, spatial apportionment of livestock to better reflect land use was found to be important in the models, especially in upstream reaches of the catchments. In conclusion, successful monitoring of faecal bacteria levels in UK rivers requires risk-based monitoring (sufficient to identify possible seasonal trends) and informed spatial consideration of sampling sites. Catchment models can be useful aids for directing and augmenting such monitoring programmes, but these models should undergo rigorous validation, particularly in upper catchment areas, to ensure correct model response to changes in land use and/or climate.