Charlotte E M Lloyd

Using hysteresis analysis of high-resolution water quality monitoring data, including uncertainty, to infer controls on nutrient and sediment transfer in catchments

A large proportion of nutrients and sediment is mobilised in catchments during storm events. Therefore understanding a catchments hydrological behaviour during storms and how this acts to mobilise and transport nutrients and sediment to nearby watercourses is extremely important for effective catchment management. The expansion of available in-situ sensors is allowing a wider range of water quality parameters to be monitored and at higher temporal resolution, meaning that the investigation of hydrochemical behaviours during storms is increasingly feasible. Studying the relationship between discharge and water quality parameters in storm events can provide a valuable research tool to infer the likely source areas and flow pathways contributing to nutrient and sediment transport. Therefore, this paper uses 2 years of high temporal resolution (15/30 min) discharge and water quality (nitrate-N, total phosphorus (TP) and turbidity) data to examine hysteretic behaviour during storm events in two contrasting catchments, in the Hampshire Avon catchment, UK. This paper provides one of the first examples of a study which comprehensively examines storm behaviours for up to 76 storm events and three water quality parameters. It also examines the observational uncertainties using a non-parametric approach. A range of metrics was used, such as loop direction, loop area and a hysteresis index (HI) to characterise and quantify the storm behaviour. With two years of high resolution information it was possible to see how transport mechanisms varied between parameters and through time. This study has also clearly shown the different transport regimes operating between a groundwater dominated chalk catchment versus a surface-water dominated clay catchment. This information, set within an uncertainty framework, means that confidence can be derived that the patterns and relationships thus identified are statistically robust. These insights can thus be used to provide information regarding transport processes and biogeochemical processing within river catchments.

Discharge and nutrient uncertainty: implications for nutrient flux estimation in small streams

The measurement of discharge is fundamental in nutrient load estimation. Because of our ability to monitor discharge routinely, it is generally assumed that the associated uncertainty is low. This paper challenges this preconception, arguing that discharge uncertainty should be explicitly taken into account to produce robust statistical analyses. In many studies, paired discharge and chemical datasets are used to calculate ‘true’ loads and used as the benchmark to compare with other load estimates. This paper uses two years of high frequency (daily and sub-hourly) discharge and nutrient concentration data (nitrate-N and total phosphorus (TP)) collected at four field sites as part of the Hampshire Avon Demonstration Test Catchment (DTC) programme. A framework for estimating observational nutrient load uncertainty was used which combined a flexible non-parametric approach to characterising discharge uncertainty, with error modelling that allowed the incorporation of errors which were heteroscedastic and temporally correlated. The results showed that the stage–discharge relationships were non-stationary, and observational uncertainties from ±2 to 25% were recorded when the velocity–area method was used. The variability in nutrient load estimates ranged from 1.1 to 9.9% for nitrate-N and from 3.3 to 10% for TP when daily laboratory data were used, rising to a maximum of 9% for nitrate-N and 83% for TP when the sensor data were used. However, the sensor data provided a better representation of the ‘true’ load as storm events are better represented temporally, posing the question: is it more beneficial to have high frequency, lower precision data or lower frequency but higher precision data streams to estimate nutrient flux responses in headwater catchments?

Discharge and nutrient uncertainty

The measurement of discharge is fundamental in nutrient load estimation. Because of our ability to monitor discharge routinely, it is generally assumed that the associated uncertainty is low. This paper challenges this preconception, arguing that discharge uncertainty should be explicitly taken into account to produce robust statistical analyses. In many studies, paired discharge and chemical datasets are used to calculate ‘true’ loads and used as the benchmark to compare with other load estimates. This paper uses two years of high frequency (daily and sub-hourly) discharge and nutrient concentration data (nitrate-N and total phosphorus (TP)) collected at four field sites as part of the Hampshire Avon Demonstration Test Catchment (DTC) programme. A framework for estimating observational nutrient load uncertainty was used which combined a flexible non-parametric approach to characterising discharge uncertainty, with error modelling that allowed the incorporation of errors which were heteroscedastic and temporally correlated. The results showed that the stage–discharge relationships were non-stationary, and observational uncertainties from ±2 to 25% were recorded when the velocity–area method was used. The variability in nutrient load estimates ranged from 1.1 to 9.9% for nitrate-N and from 3.3 to 10% for TP when daily laboratory data were used, rising to a maximum of 9% for nitrate-N and 83% for TP when the sensor data were used. However, the sensor data provided a better representation of the ‘true’ load as storm events are better represented temporally, posing the question: is it more beneficial to have high frequency, lower precision data or lower frequency but higher precision data streams to estimate nutrient flux responses in headwater catchments?

High-frequency monitoring of catchment nutrient exports reveals highly variable storm-event responses and dynamic source zone activation

Storm events can drive highly variable behaviour in catchment nutrient and water fluxes, yet short-term event dynamics are frequently missed by low resolution sampling regimes. In addition, nutrient source zone contributions can vary significantly within and between storm events. Our inability to identify and characterise time-dynamic source zone contributions severely hampers the adequate design of land-use management practices in order to control nutrient exports from agricultural landscapes. Here, we utilise an 8-month high-frequency (hourly) time series of streamflow, nitrate (NO3-N), dissolved organic carbon (DOC), and hydroclimatic variables for a headwater agricultural catchment. We identified 29 distinct storm events across the monitoring period. These events represented 31% of the time series and contributed disproportionately to nutrient loads (42% of NO3-N and 43% of DOC) relative to their duration. Regression analysis identified a small subset of hydroclimatological variables (notably precipitation intensity and antecedent conditions) as key drivers of nutrient dynamics during storm events. Hysteresis analysis of nutrient concentration-discharge relationships highlighted the dynamic activation of discrete NO3-N and DOC source zones, which varied on an event-specific basis. Our results highlight the benefits of high-frequency in situ monitoring for characterising short-term nutrient fluxes and unravelling connections between hydroclimatological variability and river nutrient export and source zone activation under extreme flow conditions. These new process-based insights, which we summarise in a conceptual model, are fundamental to underpinning targeted management measures to reduce nutrient loading of surface waters.

Determining the sources of nutrient flux to water in headwater catchments: Examining the speciation balance to inform the targeting of mitigation measures

Diffuse water pollution from agriculture (DWPA) is a major environmental concern, with significant adverse impacts on both human and ecosystem health. However, without an appropriate understanding of the multiple factors impacting on water, mitigation measures cannot be targeted. Therefore, this paper addresses this gap in understanding, reporting the hydrochemical monitoring evidence collected from the UK Governments Demonstration Test Catchments (DTC) programme including contrasting chalk and clay/mudstone catchments. We use data collected at daily and sub-daily frequency over multiple sites to address: (1) How does the behaviour of the full range of nitrogen (N) species and phosphorus (P) fractions vary? (2) How do N species and P fractions vary inter- and intra-annually? (3) What do these data indicate about the primary pollution sources? And (4) which diffuse pollution mitigation measures are appropriate in our study landscapes? Key differences in the rates of flux of nutrients were identified, dependent on catchment characteristics. Full N speciation and P fractionation, together with dissolved organic carbon (DOC) enabled identification of the most likely contributing sources in each catchment. Nitrate (NO3-N) was the dominant N fraction in the chalk whereas organic and particulate N comprised the majority of the load in the clay/mudstone catchments. Despite current legislation, orthophosphate (PO4-P) was not found to be the dominant form of P in any of the catchments monitored. The chalk sub-catchments had the largest proportion of inorganic/dissolved organic P (DOP), accompanied by episodic delivery of particulate P (PP). Contrastingly, the clay/mudstone sub-catchments loads were dominated by PP and DOP. Thus, our results show that by monitoring both the inorganic and organic fractions a more complete picture of catchment nutrient fluxes can be determined, and sources of pollution pin-pointed. Ultimately, policy and management to bring nutrient impacts under control will only be successful if a multi-stressor approach is adopted.