Floods are dominant controls on export of solutes from catchments. In contrast, low‐flow periods such as droughts are potentially dominant control points for biogeochemical processing, enhancing spatiotemporal variation in solute concentrations, stream metabolism, and nutrient uptake. Using complementary time series (i.e., an Eulerian reference frame) and longitudinal profiling (i.e., a Lagrangian reference frame), we investigated hydrologic controls on temporal and spatial variation in solute flux and metabolism in the Lower Santa Fe River (FL, USA), where highly colored surface water mixes with exceptionally clear groundwater from springs. Gage measurements suggest groundwater inputs ranged from <1% (during extreme floods) to 86% (during extreme drought) of total discharge (Q). Mass transport of most solutes was dominated by high‐Q periods. Most solute C‐Q relationships exhibited statistically significant slope breakpoints near the transition between surface and groundwater dominance. In particular, parameters controlling water column light attenuation were chemostatic above median Q but markedly reduced at low Q. As a result, river metabolism and assimilatory nitrate (NO3−) uptake were consistently suppressed at high Q and enhanced at low Q, with greater variability in response to drivers other than water column light transmittance. Spatial variation in solute concentrations was also enhanced at low Q, induced by discrete groundwater inflow and biogeochemical processing along the reach. Contrasting reference frames yielded corroborative evidence for transport dominance at high Q, which damps spatiotemporal heterogeneity. In contrast, low‐Q periods enable localized mixing controls on solute concentrations and high rates of metabolism and nutrient processing that increase spatiotemporal variability.

Stream water chemistry is traditionally measured as variation over time at fixed sites, with sparse sites providing a crude understanding of spatial heterogeneity. An alternative Lagrangian reference frame measures changes with respect to both space and time as water travels through a network. Here, we collected sensor-based measurements of water chemistry at high spatial resolution along nearly 500 km of the Upper Colorado River. Our objective was to understand sources of spatiotemporal heterogeneity across different solutes and determine whether longitudinal change manifests as smooth gradients as suggested by the River Continuum Concept (RCC) or as abrupt changes as suggested by the Serial Discontinuity Concept (SDC). Our results demonstrate that Lagrangian sampling integrates spatiotemporal variation, and profiles reflect processes that vary in both space and time and over different scales.Over each day of sampling, water temperature (T) and dissolved oxygen (DO) varied strongly in response to diel solar cycles, with most of the variation driven by sampling time rather than sampling location. Equilibration of T and DO with the atmosphere limited small scale spatial heterogeneity, with variation at the entire profile scale driven by regional climate gradients. As such, T and DO profiles more closely approximated the smooth gradients of the RCC (though including temporal sampling artefacts). Conversely, variation in specific conductance and nitrate (NO 3 -N) was largely driven by spatial patterns of lateral inflows such as tributaries and groundwater. This resulted in discrete shifts in the profiles at or downstream of discontinuities, appearing as the profiles expected with the SDC. The concatenation of spatiotemporal variation that produces observed Lagrangian profiles presents interpretive challenges but also augments our understanding of where, how, and critically why water chemistry changes in time and space as it moves through river networks.

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