Science is often driven forward by the emergence of new measurements. Whenever one makes observations at a scale, precision, or frequency that was previously unattainable, one is almost guaranteed to learn something new and interesting. Our purpose in this commentary is to argue that catchment hydrochemistry is on the verge of just such a major new advance, driven by automated, online continuous analysis for many chemical constituents in natural waters.To date, most catchment hydrochemical studies have been based on hourly or sub-hourly measurements of water fluxes, and weekly or monthly samples of rainfall and streamflow chemistry. This stark mismatch in measurement time scales springs from the measurement technologies involved. Water flux measurements are easily automated, and can be logged at any interval that is desired. Conventional laboratory measurements of water chemistry, by contrast, are time consuming and expensive, and at high sampling frequencies the sample bottles pile up fast. For this reason, high-frequency chemical monitoring has typically been restricted to intensive studies of individual storm events.That is now changing. Field-deployable autoanalysers are now a reality, and ion-specific electrodes continue to improve. These technological developments promise to provide measurements of rainfall and streamflow chemistry at hourly or sub-hourly intervals (similar to the time scales at which hydrometric data have long been available) and to provide these measurements for long spans of time, not just for intensive field campaigns associated with individual storms.These technologies are likely to transform our view of catchment processes, by allowing us to observe their hydrochemical evolution at temporal resolutions that are orders of magnitude finer than before. Continuous online measurements of pH and electrical conductivity have been available for years, and they provide a preview of the high-frequency hydrochemical behaviour that will become observable through automated online chemical analysis

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Abstract:Catchment travel time distributions reflect how precipitation from different storms is stored and mixed as it is transported to the stream. Catchment travel time distributions can be described by the mean travel time and the shape of the distribution around the mean. Whereas mean travel times have been quantified in a range of catchment studies, only rarely has the shape of the distribution been estimated. The shape of the distribution affects both the short-term and long-term catchment response to a pulse input of a soluble contaminant. Travel time distributions are usually estimated from conservative tracer concentrations in precipitation and streamflow, which are analyzed using time-domain convolution or spectral methods. Of these two approaches, spectral methods are better suited to determining the shape of the distribution. Previous spectral analyses of both rainfall and streamflow tracer time series from several catchments in Wales showed that rainfall chemistry spectra resemble white noise, whereas the stream tracer spectra in these same catchments exhibit fractal 1/f scaling over three orders of magnitude. Here we test the generality of the observed fractal scaling of streamflow chemistry, using spectral analysis of long-term tracer time series from 22 catchments in North America and Europe. We demonstrate that 1/f fractal scaling of stream chemistry is a common feature of these catchments. These observations imply that catchments typically exhibit an approximate power-law distribution of travel times, and thus retain a long memory of past inputs. The observed fractal scaling places strong constraints on possible models of catchment behavior, because it is inconsistent with the exponential travel time distributions that are predicted by simple mixing models.

Several studies have highlighted an increase in DOC concentration in streams and lakes of UK upland catchments though the causal mechanisms controlling the increase have yet to be fully explained. This study, compiles a comprehensive data set of DOC concentration records for UK catchments to evaluate trends and test whether observed increases are ubiquitous over time and space. The study analysed monthly DOC time series from 198 sites, including 29 lakes, 8 water supply reservoirs and 161 rivers. The records vary in length from 8 to 42 years going back as far as 1961. Of the 198 sites, 153 (77%) show an upward trend in DOC concentration significant at the 95% level, the remaining 45 (23%) show no significant trend and no sites show a significant decrease in DOC concentration. The average annual increase in DOC concentration was 0.17 mg C/l/year. The dataset shows: (i) a spatial consistent upward trend in the DOC concentration independent of regional effects of rainfall, acid and nitrogen deposition, and local effects of land-use change; (ii) a temporally consistent increase in DOC concentration for period back as far as the 1960s; (iii) the increase in DOC concentration means an estimated DOC flux from the UK as 0.86 Mt C for the year 2002 and is increasing at 0.02 Mt C/year. Possible reasons for the increasing DOC concentration are discussed.

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This paper reviews current knowledge on sampling, storage and analysis of phosphorus (P) in river waters. Potential sensitivity of rivers with different physical, chemical and biological characteristics (trophic status, turbidity, flow regime, matrix chemistry) is examined in terms of errors associated with sampling, sample preparation, storage, contamination, interference and analytical errors. Key issues identified include:The need to tailor analytical reagents and concentrations to take into account the characteristics of the sample matrix. The effects of matrix interference on the colorimetric analysis. The influence of variable rates of phospho-molybdenum blue colour formation. The differing responses of river waters to physical and chemical conditions of storage. The higher sensitivities of samples with low P concentrations to storage and analytical errors.Given high variability of river water characteristics in space and time, no single standardised methodology for sampling, storage and analysis of P in rivers can be offered. 'Good Practice' guidelines are suggested, which recommend that protocols for sampling, storage and analysis of river water for P is based on thorough site-specific method testing and assessment of P stability on storage. For wider sampling programmes at the regional/national scale where intensive site-specific method and stability testing are not feasible, 'Precautionary Practice' guidelines are suggested. The study highlights key areas requiring further investigation for improving methodological rigour.

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