Stable isotopes reduce parameter uncertainty of an estuarine carbon cycling model

Adiyanti, Sri; Eyre, Bradley D.; Maher, Damien T.; Santos, Isaac R.; Golsby-Smith, Lindsay; Mangion, Perrine; Hipsey, Matthew R.

doi:10.1016/j.envsoft.2016.02.011

Cited by 17 publications

(15 citation statements)

References 68 publications

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“…A precursor to confidently simulating nitrogen fluxes within the agricultural stream ecosystem is recognition of the potential for equifinality in numerical modeling results. Equifinality refers to the uncertainty of parameters in process‐based numerical models that can lead to a broad range of multiple parameter sets (i.e., realities) and in turn broad range of acceptable solutions [ Beven , ; Adiyanti et al ., ]. Over‐parameterization of numerical models for stream nitrogen suggest the high potential for equifinality.…”

Section: Introductionmentioning

confidence: 99%

“…Over‐parameterization of numerical models for stream nitrogen suggest the high potential for equifinality. Recent research suggests that these advanced model calibration and uncertainty subroutines might be coupled with ambient isotope tracers to reduce equifinality within water quality modeling [ Ford and Fox , ; Fox and Martin , ; Adiyanti et al ., ].…”

Section: Introductionmentioning

confidence: 99%

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Reducing equifinality using isotopes in a process‐based stream nitrogen model highlights the flux of algal nitrogen from agricultural streams

Ford

Fox

Pollock

2017

Water Resources Research

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The fate of bioavailable nitrogen species transported through agricultural landscapes remains highly uncertain given complexities of measuring fluxes impacting the fluvial N cycle. We present and test a new numerical model named Technology for Removable Annual Nitrogen in Streams For Ecosystem Restoration (TRANSFER), which aims to reduce model uncertainty due to erroneous parameterization, i.e., equifinality, in stream nitrogen cycle assessment and quantify the significance of transient and permanent removal pathways. TRANSFER couples nitrogen elemental and stable isotope mass‐balance equations with existing hydrologic, hydraulic, sediment transport, algal biomass, and sediment organic matter mass‐balance subroutines and a robust GLUE‐like uncertainty analysis. We test the model in an agriculturally impacted, third‐order stream reach located in the Bluegrass Region of Central Kentucky. Results of the multiobjective model evaluation for the model application highlight the ability of sediment nitrogen fingerprints including elemental concentrations and stable N isotope signatures to reduce equifinality of the stream N model. Advancements in the numerical simulations allow for illumination of the significance of algal sloughing fluxes for the first time in relation to denitrification. Broadly, model estimates suggest that denitrification is slightly greater than algal N sloughing (10.7% and 6.3% of dissolved N load on average), highlighting the potential for overestimation of denitrification by 37%. We highlight the significance of the transient N pool given the potential for the N store to be regenerated to the water column in downstream reaches, leading to harmful and nuisance algal bloom development.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reducing equifinality using isotopes in a process‐based stream nitrogen model highlights the flux of algal nitrogen from agricultural streams

Ford

Fox

Pollock

2017

Water Resources Research

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“…For such models, the broad range of parameters leads to large posterior solution spaces for fluxes and transformations. Parameter specification uncertainty is robustly reflected by the concept of equifinality, which refers to the potential for a posterior solution space of acceptable calibrations to be met by multiple parameterizations, or realizations (Beven, 2006;Adiyanti et al, 2016). The Generalized Likelihood Uncertainty Estimation (GLUE) framework provides a means to quantify equifinality and is applied using Monte Carlo-based realizations of a global parameter space and evaluation of the subsequent solutions against measured data to create a posterior solution space (Beven and Binley, 1992;Dean et al, 2009;Jin et al, 2010;Gong et al, 2011;Shen et al, 2012;.…”

Section: Constraining Model Parameterizationmentioning

confidence: 99%

“…The acceptance into such a solution space depends on evaluation of measured and modeled data using statistical metrics such as Nash-Sutcliffe efficiency, percent bias, and ratio of the root mean square error to the standard deviation of measured data, e.g., Moriasi et al (2007). While we commend the excellent work of researchers in quantifying this uncertainty, it has been shown that stable isotopes may also be coupled with water quality models to further reduce such uncertainty (Adiyanti et al, 2016;. In many ways, elucidation of parameterization via stable isotopes within watershed water quality modeling is another highly conceivable method, given the long history of stable isotopes to elucidate reactions (Sharp, 2007).…”

Section: Constraining Model Parameterizationmentioning

confidence: 99%

“…These added equations are often accompanied with few new unknowns or insensitive unknowns; therefore, a stable isotope data stream may assist with model parameterization. For these reasons, several studies have used stable isotopes to help with parameterizing water quality models (Tobias and Böhlke, 2011;Van Engeland et al, 2012;Hong et al, 2014;Fox and Martin, 2014;Ford and Fox, 2015;Adiyanti et al, 2016;.…”

Section: Constraining Model Parameterizationmentioning

confidence: 99%

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Improving In-Stream Nutrient Routines in Water Quality Models Using Stable Isotope Tracers: A Review and Synthesis

Jensen¹,

Ford²,

Fox³

et al. 2018

Transactions of the ASABE

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Abstract. Water quality models serve as an economically feasible alternative to quantify fluxes of nutrient pollution and to simulate effective mitigation strategies; however, their applicability is often questioned due to broad uncertainties in model structure and parameterization, leading to uncertain outputs. We argue that reduction of uncertainty is partially achieved by integrating stable isotope data streams within the water quality model architecture. This article outlines the use of stable isotopes as a response variable within water quality models to improve the model boundary conditions associated with nutrient source provenance, constrain model parameterization, and elucidate shortcomings in the model structure. To assist researchers in future modeling efforts, we provide an overview of stable isotope theory; review isotopic signatures and applications for relevant carbon, nitrogen, and phosphorus pools; identify biotic and abiotic processes that impact isotope transfer between pools; review existing models that have incorporated stable isotope signatures; and highlight recommendations based on synthesis of existing knowledge. Broadly, we find existing applications that use isotopes have high efficacy for reducing water quality model uncertainty. We make recommendations toward the future use of sediment stable isotope signatures, given their integrative capacity and practical analytical process. We also detail a method to incorporate stable isotopes into multi-objective modeling frameworks. Finally, we encourage watershed modelers to work closely with isotope geochemists to ensure proper integration of stable isotopes into in-stream nutrient fate and transport routines in water quality models. Keywords: Isotopes, Nutrients, Uncertainty analysis, Water quality modeling, Watershed.

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Integration of submerged aquatic vegetation motion within hydrodynamic models

Nakayama

Shintani

Komai

et al. 2020

Preprint

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Aquatic models used for both freshwater and marine systems frequently need to account for submerged aquatic vegetation (SAV) due to its influence on flow and water quality. Despite its importance, parameterizations are generally adopted that simplify feedbacks from SAV, such as canopy properties (e.g., considering the deflected vegetation height) and the bulk friction coefficient. This study reports the development of a fine-scale non-hydrostatic model that demonstrates the two-way effects of SAV motion interaction with the flow. An object-oriented approach is applied to capture the multiphase phenomena, whereby a leaf-scale SAV model based on a discrete element method is combined with a flow dynamics model to resolve stresses from currents and waves. The model is verified through application to a laboratory-scale seagrass bed. A force balance analysis revealed that leaf elasticity and buoyancy are the most significant components influencing the horizontal and vertical momentum equations, respectively. The sensitivity of canopy-scale bulk friction coefficients to water depth, current speeds, and vegetation density of seagrass was explored. Deeper water was also shown to lead to a smaller decrease in vegetation height. The model approach can contribute to improving assessment of processes influencing water quality, sediment stabilization, carbon sequestration, and SAV restoration, thereby supporting an understanding of how waterways and coasts will respond to changes brought about by development and a changing climate. Plain Language Summary Aquatic system models that capture aquatic vegetation are increasingly important to help us understand processes controlling carbon budgets (e.g., "blue carbon") and for planning restoration efforts (e.g., Adams et al., 2016, https://doi.org/10.1002/lno.10319). Current models all rely on "static" approaches to account for vegetation via bulk parameterizations, though we know vegetation motion is important (e.g., Abdolahpour et al., 2018, https://doi.org/10.1002/lno.11008). Our study is the first to model the feedback between blade-scale vegetation motion and hydrodynamics to show it is crucial in shaping bottom mixing processes with implications for carbon and nutrient deposition.

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Stable isotopes reduce parameter uncertainty of an estuarine carbon cycling model

Cited by 17 publications

References 68 publications

Reducing equifinality using isotopes in a process‐based stream nitrogen model highlights the flux of algal nitrogen from agricultural streams

Reducing equifinality using isotopes in a process‐based stream nitrogen model highlights the flux of algal nitrogen from agricultural streams

Improving In-Stream Nutrient Routines in Water Quality Models Using Stable Isotope Tracers: A Review and Synthesis

Integration of submerged aquatic vegetation motion within hydrodynamic models

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