Fluvial networks integrate, transform, and transport constituents from terrestrial and aquatic ecosystems. To date, most research on water quality dynamics has focused on process understanding at individual streams, and, as a result, there is a lack of studies analyzing how physical and biogeochemical drivers scale across fluvial networks. We performed tracer tests in five stream orders of the Jemez River continuum in New Mexico, USA, to quantify reach‐scale hyporheic exchange during two different seasonal periods to address the following: How do hyporheic zone contributions to overall riverine processing change with space and time? And does the spatiotemporal variability of hyporheic exchange scale across fluvial networks? Combining conservative (i.e., bromide) and reactive (i.e., resazurin) tracer analyses with solute transport modeling, we found a dominance of reaction‐limited transport conditions and a decrease of the contributions of hyporheic processing across stream orders and flow regimes. Our field‐based findings suggest that achieving knowledge transferability of hyporheic processing within fluvial networks may be possible, especially when process variability is sampled across multiple stream orders and flow regimes. Therefore, we propose a shift in our traditional approach to investigating scaling patterns in transport processes, which currently relies on the interpretation of studies conducted in multiple sites (mainly in headwater streams) that are located in different fluvial networks, to a more cohesive, network‐centered investigation of processes using the same or readily comparable methods.
Stream solute tracers are commonly injected to assess transport and transformation in study reaches, but results are biased toward the shortest and fastest storage locations. While this bias has been understood for decades, the impact of an experimental constraint on our understanding has yet to be considered. Here, we ask how different our understanding of reach‐ and segment‐scale transport would be if our empirical limits were extended. We demonstrate a novel approach to manipulate experimental conditions and observe mass that is stored at timescales beyond the traditional reach‐scale window of detection. We are able to explain the fate of an average of 26% of solute tracer mass that would have been considered as “lost” in a traditional study design across our 14 replicates, extending our detection limits to characterize flowpaths that would have been previously unmeasured. We demonstrate how this formerly lost mass leads to predicting lower magnitudes of gross gains and losses in individual reaches, and ultimately show that the network turnover we infer from solute tracers represents an upper limit on actual, expected behavior. Finally, we review the evolution of tracer studies and their interpretation including this approach and provide a proposed future direction to extend empirical studies to not‐before‐seen timescales.
more » « less- Award ID(s):
- 2334072
- NSF-PAR ID:
- 10399794
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Water Resources Research
- Volume:
- 59
- Issue:
- 3
- ISSN:
- 0043-1397
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
more » « less
Abstract -
more » « less
Abstract The distribution of oceanic biogeochemical tracers is fundamentally tied to physical dynamics at and below the mesoscale. Since global climate models rarely resolve those scales, turbulent transport is parameterized in terms of the large‐scale gradients in the mean tracer distribution and the physical fields. Here, we demonstrate that this form of the eddy flux is not necessarily appropriate for reactive tracers, such as nutrients and phytoplankton. In an idealized nutrient‐phytoplankton system, we show that the eddy flux of one tracer should depend on the gradients of itself and the other. For certain parameter regimes, incorporating cross‐diffusion can significantly improve the representation of both phytoplankton and nutrient eddy fluxes. We also show that the efficacy of eddy diffusion parameterizations requires timescale separation between the flow and reactions. This result has ramifications for parameterizing subgrid scale biogeochemistry in more complex ocean models since many biological processes have comparable timescales to submesoscale motions.
-
more » « less
Abstract Novel observation techniques (e.g., smart tracers) for characterizing coupled hydrological and biogeochemical processes are improving understanding of stream network transport and transformation dynamics. In turn, these observations are thought to enable increasingly sophisticated representations within transient storage models (TSMs). However, TSM parameter estimation is prone to issues with insensitivity and equifinality, which grow as parameters are added to model formulations. Currently, it is unclear whether (or not) observations from different tracers may lead to greater process inference and reduced parameter uncertainty in the context of TSM. Herein, we aim to unravel the role of in‐stream processes alongside metabolically active (MATS) and inactive storage zones (MITS) using variable TSM formulations. Models with one (1SZ) and two storage zones (2SZ) and with and without reactivity were applied to simulate conservative and smart tracer observations obtained experimentally for two reaches with differing morphologies. As we show, smart tracers are unsurprisingly superior to conservative tracers when it comes to partitioning MITS and MATS. However, when transient storage is lumped within a 1SZ formulation, little improvement in parameter uncertainty is gained by using a smart tracer, suggesting the addition of observations should scale with model complexity. Importantly, our work identifies several inconsistencies and open questions related to reconciling time scales of tracer observation with conceptual processes (parameters) estimated within TSM. Approaching TSM with multiple models and tracer observations may be key to gaining improved insight into transient storage simulation as well as advancing feedback loops between models and observations within hydrologic science.
-
more » « less
Abstract Accounting for the burial of tracer particles during bedload transport is an important component in the formulation of tracer dispersal in rivers. Herein we propose a modified active layer formulation, which accounts for the effect of burial and admits analytical solutions, enabling insightful exploration of the phenomenon of superdiffusion of bedload tracers at the intermediate timescale. This phenomenon has been observed in recent numerical results using the 2‐D Exner‐Based Master Equation. By assuming that tracers in the active layer can exchange with nontracer particles in the substrate layer to preserve mass, and that tracers entering the substrate layer get permanently trapped during the timescale of analysis, we are able to deduce governing equations for the tracer concentration in both layers. The active layer tracer concentration is shown to be governed by an advection‐diffusion equation with a sink term, and the increase of tracers in the substrate layer is driven by a corresponding source term. The solution for the variance of tracer population is analytically determined and can be approximated by the sum of a diffusion‐induced scaling (
∝ ) and an advection‐induced scaling (t 1∝ ) terms at the intermediate timescale, which explains the phenomenon of superdiffusion. The proposed formulation is shown to be able to capture the key characteristics of tracer transport as inferred by comparison with available results of numerical simulations.t 3 -
Abstract Lateral mesoscale eddy-induced tracer transport is traditionally represented in coarse-resolution models by the flux–gradient relation. In its most complete form, the relation assumes the eddy tracer flux as a product of the large-scale tracer concentration gradient and an eddy transport coefficient tensor. However, several recent studies reported that the tensor has significant spatiotemporal complexity and is not uniquely defined, that is, it is sensitive to the tracer distributions and to the presence of nondivergent (“rotational”) components of the eddy flux. These issues could lead to significant biases in the representation of the eddy-induced transport. Using a high-resolution tracer model of the Gulf Stream region, we examine the diffusive and advective properties of lateral eddy-induced transport of dynamically passive tracers, reevaluate the utility of the flux–gradient relation, and propose an alternative approach based on modeling the local eddy forcing by a combination of diffusion and generalized eddy-induced advection. Mesoscale eddies are defined by a scale-based spatial filtering, which leads to the importance of new eddy-induced terms, including eddy-mean covariances in the eddy fluxes. The results show that the biases in representing these terms are noticeably reduced by the new approach. A series of targeted simulations in the high-resolution model further demonstrates that the approach outperforms the flux–gradient model in reproducing the stirring and dispersing effect of eddies. Our study indicates potential to upgrade the traditional flux–gradient relation for representing the eddy-induced tracer transport.more » « less
