Fingerprinting hydrological and biogeochemical drivers of freshwater quality

Abstract

Understanding the interplay between hydrological flushing and biogeochemical cycling in streams is now possible owing to advances in high‐frequency water quality measurements with in situ sensors. It is often assumed that storm events are periods when biogeochemical processes become suppressed and longitudinal transport of solutes and particulates dominates. However, high‐frequency data show that diel cycles are a common feature of water quality time series and can be preserved during storm events, especially those of low‐magnitude. In this study, we mine a high‐frequency dataset and use two key hydrochemical indices, hysteresis and flushing index to evaluate the diversity of concentration‐discharge relationships in third order agricultural stream. We show that mobilization patterns, inferred from the hysteresis index, change on a seasonal basis, with a predominance of rapid mobilization from surface and near stream sources during winter high‐magnitude storm events and of delayed mobilization from subsurface sources during summer low‐magnitude storm events. Using dynamic harmonic regression, we were able to separate concentration signals during storm events into hydrological flushing (using trend as a proxy) and biogeochemical cycling (using amplitude of a diel cycle as a proxy). We identified three groups of water quality parameters depending on their typical c‐q response: flushing dominated parameters (phosphorus and sediments), mixed flushing and cycling parameters (nitrate nitrogen, specific conductivity and pH) and cycling dominated parameters (dissolved oxygen, redox potential and water temperature). Our results show that despite large storm to storm diversity in hydrochemical responses, storm event magnitude and timing have a critical role in controlling the type of mobilization, flushing and cycling behaviour of each water quality constituent. Hydrochemical indices can be used to fingerprint the effect of hydrological disturbance on freshwater quality and can be useful in determining the impacts of global change on stream ecology.

Turbidity‐discharge hysteresis in a meso‐scale catchment: The importance of intermediate scale events

“…Short time turbidity variation was observed for all low Q events, with a period ranging between 8 h and 3 days (example in Figure S4). Hysteresis index analysis are sensitive to diel cycles (Heathwaite & Bieroza, 2020), and the assumption of a connection between turbidity and Q is not fulfilled for these events. The events showed a general low turbidity (average 10 FNU) and amplitude of turbidity variation (10 FNU), as well as a low mean Q (<1 m 3 /s).…”

“…Evaluating differences in the temporal patterns of C and Q during events (hysteresis patterns) is a widely used approach to understanding more about catchment processes and hydrological pathways (Bieroza & Heathwaite, 2015; Bowes et al, 2005; Butturini et al, 2008; Evans & Davies, 1998; Fovet et al, 2018; Glover & Johnson, 1974; Hashemi et al, 2020; Heathwaite & Bieroza, 2020; Rose et al, 2018; Walling & Foster, 1975). So‐called “hysteresis loops” are often used to graphically represent such differences.…”

Stormflow concentration–discharge dynamics of suspended sediment and dissolved phosphorus in an agricultural watershed

“…Individual rainfall events were defined and quantified as periods of measured precipitation preceded and followed by at least 6 h of no measurable precipitation (Palecki et al, 2005), and we defined the “recovery period” between individual rainfall events as the length of time (in days) since the preceding storm (Walling & Webb, 1982). Antecedent precipitation in the week prior to each event was quantified with an antecedent precipitation index (API 7 ) as in other studies of intra‐event stormflow dynamics (Brocca et al, 2008; Heathwaite & Bieroza, 2020) using USGS measurements of total daily rainfall at Greenleaf, WI (Station #441546088082001; located approximately 5 km from the study site).…”

Spatial and temporal dynamics of nitrogen exchange in an upwelling reach of a groundwater‐fed river and potential response to perturbations changing rainfall patterns under UK climate change scenarios

“…Under a changing climate, an increased incidence of high intensity summer storms superimposed on a general trend towards low flows may disproportionately impact river biogeochemistry (see e.g., Bieroza & Heathwaite, 2017; Heathwaite & Bieroza, 2020). Raymond et al (2016) suggest that low‐frequency large events, which are predicted to increase with climate change, are responsible for a significant percentage of annual terrestrial DOM input to drainage networks by “pulse‐shunt” of biochemically reactive DOM via surface and subsurface pathways such as Permanent Control Points.…”

“…also examined riparian wetlands as permanent control points using a combination of geochemical, geophysical and isotope ratio methods. The authors distinguished wetter areas supporting denitrification from zones where plant demand for nitrate was greater than demand by denitrifiers, leading to the assimilation, breakdown and re-release of inorganic nutrient fractions in the form of dissolved organic matter (DOM), which was subsequently flushed into adjacent waters during high flow events: the flushing of macropores and micropores during storm events was observed to be the primary mechanism for the export of nutrients.Under a changing climate, an increased incidence of high intensity summer storms superimposed on a general trend towards low flows may disproportionately impact river biogeochemistry (see e.g.,Bieroza & Heathwaite, 2017;Heathwaite & Bieroza, 2020) Raymond et al (2016). suggest that low-frequency large events, which are predicted to increase with climate change, are responsible for a significant percentage of annual terrestrial DOM input to drainage networks by "pulse-shunt" of biochemically reactive DOM via surface and subsurface pathways such as Permanent Control Points.…”