title: Monitoring fluvial water chemistry for trend detection: hydrological variability masks trends in datasets covering fewer than 12 years.
abstract: This paper sub-samples four 35 year water quality time series to consider the potential influence of short-term hydrological variability on process inference derived from short-term monitoring data. The data comprise two time series for nitrate (NO(3)-N) and two for DOC (using water colour as a surrogate). The four catchments were selected not only because of their long records, but also because the four catchments are very different: upland and lowland, agricultural and non-agricultural. Multiple linear regression is used to identify the trend and effects of rainfall and hydrological 'memory effects' over the full 35 years, and then a moving-window technique is used to subsample the series, using window widths of between 6 and 20 years. The results suggest that analyses of periods between six and eleven years are more influenced by local hydrological variability and therefore provide misleading results about long-term trends, whereas periods of longer than twelve years tend to be more representative of underlying system behaviour. This is significant: if such methods for analysing monitoring data were used to validate changes in catchment management, a monitoring period of less than 12 years might be insufficient to demonstrate change in the underlying system.
authors.affiliation: Department of Civil Engineering, University of Bristol, Queen's Building, University Walk, Bristol, BS8 1TR, UK. nicholas.howden@bristol.ac.uk
authors.forename: Nicholas J K
authors.initials: NJ
authors.lastname: Howden
authors.forename: Tim P
authors.initials: TP
authors.lastname: Burt
authors.forename: Fred
authors.initials: F
authors.lastname: Worrall
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Whelan
mesh_terms: D003116:Color; D004739:England; D004784:Environmental Monitoring; D016014:Linear Models; D009566:Nitrates / Q000032:analysis*; D045483:Rivers / Q000737:chemistry*; D013997:Time Factors; D058438:Water Cycle
chemical_list: D009566:Nitrates