Elemental properties, hydrology, and biology interact to shape concentration‐discharge curves for carbon, nutrients, sediment, and major ions

Abstract

To investigate the prevalence and cause of concentration‐discharge (C‐Q) relationships for carbon, nutrients, major ions, and particulates, we analyzed 40 years of water quality data from 293 monitoring stations in France. Catchments drained diverse landscapes and ranged from 50 to 110,000 km2, together covering nearly half of France. To test for differences during low and high flows, we calculated independent C‐Q slopes above and below the median discharge. We found that 84% of all catchment‐element combinations were chemodynamic for at least half of the hydrograph and 60% of combinations showed nonlinear C‐Q curves. Only two or three of the nine possible C‐Q modalities were manifest for each parameter, and these modalities were stable through time, suggesting that intrinsic and extrinsic elemental properties (e.g., solubility, reactivity, and source dynamics) set basic C‐Q templates for each parameter, which are secondarily influenced by biological activity during low flows, and the interaction between hydrology and catchment characteristics at high flows. Several patterns challenged current C‐Q views, including low‐flow chemostasis for TSS in 66% of catchments, low‐flow biological mediation of NO3− in 71% of catchments, and positive C‐Q for dissolved organic carbon independent of catchment size in 80% of catchments. Efforts to reduce nutrient loading decreased phosphorus concentration and altered C‐Q curves, but NO3− continued to increase. While C‐Q segmentation requires more data than a single analysis, the prevalence of nonlinear C‐Q slopes demonstrates the potential information loss associated with linear or monotonic analysis of C‐Q relationships, and conversely, the value of long‐term monitoring.

Complex patterns of catchment solute–discharge relationships for coastal plain rivers

“…This behaviour was mostly confined to NO 3 and may result from dilution of nitrate sources that exhibit extremely stable flow (e.g., Florida's many artesian springs; Heffernan et al, ). This explanation differs from Moatar et al (), who found similar patterns, but suggests that they result from biogeochemical controls. Specifically, they contend that low flows favour biotic NO 3 uptake; but as discharge increases, the uptake velocity dramatically declines, precluding clear impacts on NO 3 flux.…”

“…These three properties suggest that regardless of low‐flow solute behaviour, high‐flow behaviour tends towards dilution, with high‐flow similarly defined for all catchments as >50% flow exceedance. The apparent generality of slope breaks at median flow emerges from our synthesis and important recent work (Moatar et al, ). This generality suggests common solute and flow generation processes across divergent watersheds.…”

“…Shifts to dilution behaviour above breakpoints indicate source limitation at higher flows. For Ca and Mg, breakpoints shifted from chemostasis to dilution, a common finding for catchments elsewhere (Moatar et al, ). The most notable downward shifts in β were for NO 3 , where positive low‐flow β values became negative above the breakpoint.…”

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

“…Compared to diurnal patterns, storm events induced considerably greater variability in streamflow dynamics and NO 3 -N and DOC concentrations, with no evidence for chemostatic behavior during any events [Moatar et al, 2017]. The rapid response of streamflow to precipitation inputs can be attributed in part to the numerous ditches and tile drains in the upper catchment.…”

Emergent archetype patterns of coupled hydrologic and biogeochemical responses in catchments

“…Catchments also integrate geochemical and microbial reactions occurring along a distribution of water flow paths that mobilize, transport, and transform dissolved solutes to stream networks van der Velde et al, 2010]. In-stream processes further alter C-Q-L relationships along the river network, from headwaters to catchment outlet at multiple nested spatiotemporal scales [Bieroza and Heathwaite, 2015;Moatar et al, 2017]. In-stream processes further alter C-Q-L relationships along the river network, from headwaters to catchment outlet at multiple nested spatiotemporal scales [Bieroza and Heathwaite, 2015;Moatar et al, 2017].…”