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

Abstract

A large proportion of nutrients and sediment is mobilised in catchments during storm events. Therefore understanding a catchment's 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.

Suspended sediment transport dynamics in rivers: Multi-scale drivers of temporal variation

“…Duvert et al, 2010;Lloyd et al, 2016;Sun et al, 2015;Tananaev, 2015). The most common patterns are anti-clockwise and clock-wise loops ( Figure 3) (Horowitz et al, 2014;Williams, 1989).…”

“…This variability is often related to seasonal patterns in rainfall, snowmelt and storm events, but precipitation events of similar magnitudes during different times of the year can also result in different sediment-discharge relationships, suggesting a more complex set of drivers and interactions (Lloyd et al, 2016). Therefore, understanding the behavior of the catchment in terms of sediment generation and storage is crucial to assess the annual cycling of SS transport, which is especially important for the development of targeted soil and water conservation strategies.…”

“…High-flow events generate a large proportion of the total annual SS load in rivers Horowitz, 2009;Lloyd et al, 2016;Pulley et al, 2015). Consequently, disentangling the factors that drive event-based SS dynamics is essential to improve our understanding of longer term SS trends, the importance of episodic events on those trends, and the impact of SS on ecology, geomorphology and infrastructure.…”

“…During a single rainfall event, there is considerable variation in SS concentration in the river, and these variations have been associated with numerous drivers (Lloyd et al, 2016;Smith and Blake, 2014). Compared to long-term patterns in SS transport, more specific hydro-meteorological factors need to be taken into account to explain the variations in SS transport during events.…”

Sustaining reservoir use through sediment trapping in NW Ethiopia

“…Identifying the STPs within a catchment helps to implement ST measures where they can disconnect the STPs to enhance ST (Lloyd et al, 2016). Implementing ST measures at the most appropriate locations where they can disconnect landscape units, is believed to be the most efficient way to reduce reservoir sedimentation .…”