scholarly journals Modeling dissolved oxygen dynamics and coastal hypoxia: a review

2009 ◽  
Vol 6 (5) ◽  
pp. 9195-9256 ◽  
Author(s):  
M. A. Peña ◽  
S. Katsev ◽  
T. Oguz ◽  
D. Gilbert
Keyword(s):  
Organic Matter ◽  
Three Dimensional ◽  
Marine Ecosystems ◽  
Biogeochemical Cycles ◽  
Biogeochemical Processes ◽  
Dynamical Models ◽  
Validation Data ◽  
Dynamic Representation ◽  
Biogeochemical Models ◽  
Climate Change Responses

Abstract. Hypoxia occurs in marine ecosystems throughout the world, influences biogeochemical cycles of elements and may have severe impacts on marine life. Hypoxia results from complex interactions between physical and biogeochemical processes, which can not be addressed by observations alone. In this paper, we review oxygen dynamical models that have been applied in studies of factors controlling coastal hypoxia and in predictions of future states. We also identify scientific issues that need further development and point out some of the major challenges. Over recent decades, substantial progress has been made in the development of oxygen dynamical models. Considerable progress has been made towards the parameterization of biogeochemical processes in the water column and sediments, such as the dynamic representation of nitrification-denitrification. Recent advances in three-dimensional coupled physical-ecological-biogeochemical models allow better representation of physical-biological interactions. Several types of modelling approaches, from simple to complex, have significantly contributed to improve our understanding of hypoxia. We discuss the applications of these models to the study of the effects of oxygen depletion on biogeochemical cycles, links between nutrient enrichment and hypoxia development, impacts of hypoxia on marine ecosystems and predictions of climate change responses. However, for some processes models are still crude. For example, current representations of organic matter transformations and remineralization are incomplete, as they are mostly based on empirical parameterizations at few locations. For most of these processes, the availability of validation data has been a limiting factor in model development. Another gap is that, in virtually all nutrient load models, efforts have focused on nutrient utilization and organic matter degradation, whereas three-dimensional mixing and advection have been less well represented. Explicit inclusion of physical and biogeochemical processes in models will help us answer several important questions, such as those about the causes of the observed worldwide increase in hypoxic conditions, and future changes in the intensity and spread of coastal hypoxia. At the same time, recent quantitative model intercomparison studies suggest that the predictive ability of our models may be adversely affected by their increasing complexity, unless the models are properly constrained by observations.

scholarly journals Modeling dissolved oxygen dynamics and hypoxia

2010 ◽  
Vol 7 (3) ◽  
pp. 933-957 ◽  
Author(s):  
M. A. Peña ◽  
S. Katsev ◽  
T. Oguz ◽  
D. Gilbert
Keyword(s):  
Three Dimensional ◽  
Predictive Ability ◽  
Biogeochemical Cycles ◽  
Quantitative Model ◽  
Biogeochemical Processes ◽  
Biological Interactions ◽  
Discrete Observations ◽  
Management Scenarios ◽  
Biogeochemical Models ◽  
Oxygen Dynamics

Abstract. Hypoxia conditions are increasing throughout the world, influencing biogeochemical cycles of elements and marine life. Hypoxia results from complex interactions between physical and biogeochemical processes, which can not be understood by observations alone. Models are invaluable tools at studying system dynamics, generalizing discrete observations and predicting future states. They are also useful as management tools for evaluating site-specific responses to management scenarios. Here we review oxygen dynamics models that have significantly contributed to a better understanding of the effects of natural processes and human perturbations on the development of hypoxia, factors controlling the extent and temporal variability of coastal hypoxia, and the effects of oxygen depletion on biogeochemical cycles. Because hypoxia occurs in a variety of environments and can be persistent, periodic or episodic, models differ significantly in their complexity and temporal and spatial resolution. We discuss the progress in developing hypoxia models for benthic and pelagic systems that range from simple box models to three dimensional circulation models. Applications of these models in five major hypoxia regions are presented. In the last decades, substantial progress has been made towards the parameterization of biogeochemical processes in both hypoxic water columns and sediments. In coastal regions, semi-empirical models have been used more frequently than mechanistic models to study nutrient enrichment and hypoxia relationships. Recent advances in three-dimensional coupled physical-ecological-biogeochemical models have allowed a better representation of physical-biological interactions in these systems. We discuss the remaining gaps in process descriptions and suggest directions for improvement. Better process representations in models will help us answer several important questions, such as those about the causes of the observed worldwide increase in hypoxic conditions, and future changes in the intensity and spread of coastal hypoxia. At the same time, quantitative model intercomparison studies suggest that the predictive ability of our models may be adversely affected by their increasing complexity, unless the models are properly constrained by observations.

scholarly journals Challenges associated with modeling low-oxygen waters in Chesapeake Bay: a multiple model comparison

2016 ◽  
Vol 13 (7) ◽  
pp. 2011-2028 ◽  
Author(s):  
Isaac D. Irby ◽  
Marjorie A. M. Friedrichs ◽  
Carl T. Friedrichs ◽  
Aaron J. Bever ◽  
Raleigh R. Hood ◽  
...  
Keyword(s):  
Dissolved Oxygen ◽  
Chesapeake Bay ◽  
Mixed Layer ◽  
Model Comparison ◽  
Three Dimensional ◽  
Surface Mixed Layer ◽  
Multiple Model ◽  
Low Oxygen ◽  
Mixing Depth ◽  
Biogeochemical Models

Abstract. As three-dimensional (3-D) aquatic ecosystem models are used more frequently for operational water quality forecasts and ecological management decisions, it is important to understand the relative strengths and limitations of existing 3-D models of varying spatial resolution and biogeochemical complexity. To this end, 2-year simulations of the Chesapeake Bay from eight hydrodynamic-oxygen models have been statistically compared to each other and to historical monitoring data. Results show that although models have difficulty resolving the variables typically thought to be the main drivers of dissolved oxygen variability (stratification, nutrients, and chlorophyll), all eight models have significant skill in reproducing the mean and seasonal variability of dissolved oxygen. In addition, models with constant net respiration rates independent of nutrient supply and temperature reproduced observed dissolved oxygen concentrations about as well as much more complex, nutrient-dependent biogeochemical models. This finding has significant ramifications for short-term hypoxia forecasts in the Chesapeake Bay, which may be possible with very simple oxygen parameterizations, in contrast to the more complex full biogeochemical models required for scenario-based forecasting. However, models have difficulty simulating correct density and oxygen mixed layer depths, which are important ecologically in terms of habitat compression. Observations indicate a much stronger correlation between the depths of the top of the pycnocline and oxycline than between their maximum vertical gradients, highlighting the importance of the mixing depth in defining the region of aerobic habitat in the Chesapeake Bay when low-oxygen bottom waters are present. Improvement in hypoxia simulations will thus depend more on the ability of models to reproduce the correct mean and variability of the depth of the physically driven surface mixed layer than the precise magnitude of the vertical density gradient.

scholarly journals Surfactant control of gas transfer velocity along an offshore coastal transect: results from a laboratory gas exchange tank

2016 ◽  
Vol 13 (13) ◽  
pp. 3981-3989 ◽  
Author(s):  
R. Pereira ◽  
K. Schneider-Zapp ◽  
R. C. Upstill-Goddard
Keyword(s):  
Organic Matter ◽  
Gas Exchange ◽  
Trace Gas ◽  
Gas Transfer ◽  
Transfer Velocity ◽  
Chl A ◽  
Gas Transfer Velocity ◽  
Biogeochemical Models ◽  
Sea Surface Microlayer ◽  
Laboratory Water

Abstract. Understanding the physical and biogeochemical controls of air–sea gas exchange is necessary for establishing biogeochemical models for predicting regional- and global-scale trace gas fluxes and feedbacks. To this end we report the results of experiments designed to constrain the effect of surfactants in the sea surface microlayer (SML) on the gas transfer velocity (kw; cm h−1), seasonally (2012–2013) along a 20 km coastal transect (North East UK). We measured total surfactant activity (SA), chromophoric dissolved organic matter (CDOM) and chlorophyll a (Chl a) in the SML and in sub-surface water (SSW) and we evaluated corresponding kw values using a custom-designed air–sea gas exchange tank. Temporal SA variability exceeded its spatial variability. Overall, SA varied 5-fold between all samples (0.08 to 0.38 mg L−1 T-X-100), being highest in the SML during summer. SML SA enrichment factors (EFs) relative to SSW were  ∼  1.0 to 1.9, except for two values (0.75; 0.89: February 2013). The range in corresponding k660 (kw for CO2 in seawater at 20 °C) was 6.8 to 22.0 cm h−1. The film factor R660 (the ratio of k660 for seawater to k660 for “clean”, i.e. surfactant-free, laboratory water) was strongly correlated with SML SA (r ≥ 0.70, p ≤ 0.002, each n = 16). High SML SA typically corresponded to k660 suppressions  ∼  14 to 51 % relative to clean laboratory water, highlighting strong spatiotemporal gradients in gas exchange due to varying surfactant in these coastal waters. Such variability should be taken account of when evaluating marine trace gas sources and sinks. Total CDOM absorbance (250 to 450 nm), the CDOM spectral slope ratio (SR = S275 − 295∕S350 − 400), the 250 : 365 nm CDOM absorption ratio (E2 : E3), and Chl a all indicated spatial and temporal signals in the quantity and composition of organic matter in the SML and SSW. This prompts us to hypothesise that spatiotemporal variation in R660 and its relationship with SA is a consequence of compositional differences in the surfactant fraction of the SML DOM pool that warrants further investigation.

scholarly journals Modulation of the vertical particles transfer efficiency in the Oxygen Minimum Zone off Peru

2018 ◽  
Author(s):  
Marine Bretagnon ◽  
Aurélien Paulmier ◽  
Véronique Garçon ◽  
Boris Dewitte ◽  
Sérena Illig ◽  
...  
Keyword(s):  
Organic Matter ◽  
Water Column ◽  
Sediment Traps ◽  
Biogeochemical Cycles ◽  
High Temporal Resolution ◽  
Oxygen Minimum Zones ◽  
Marine Life ◽  
Minimum Zone ◽  
Earth’S System ◽  
Oxygen Minimum

Abstract. The fate of the Organic Matter (OM) produced by marine life controls the major biogeochemical cycles of the Earth’s system. The OM produced through photosynthesis is either preserved, exported towards sediments or degraded through remineralisation in the water column. The productive Eastern Boundary Upwelling Systems (EBUSs) associated with Oxygen Minimum Zones (OMZs) should foster OM preservation due to low O2 conditions, but their intense and diverse microbial activity should enhance OM degradation. To investigate this contradiction, sediment traps were deployed near the oxycline and in the OMZ core on an instrumented moored line off Peru, providing high temporal resolution O2 series characterizing two seasonal steady states at the upper trap: suboxic ([O2] 

scholarly journals Simulating measurable ecosystem carbon and nitrogen dynamics with the mechanistically-defined MEMS 2.0 model

2021 ◽  
Author(s):  
Yao Zhang ◽  
Jocelyn M. Lavallee ◽  
Andy D. Robertson ◽  
Rebecca Even ◽  
Stephen M. Ogle ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Water ◽  
Root Zone ◽  
Ecosystem Respiration ◽  
Gross Primary Production ◽  
Total N ◽  
Calibration And Validation ◽  
Biogeochemical Models ◽  
Lower Accuracy ◽  
C Stocks

Abstract. For decades, predominant soil biogeochemical models have used conceptual soil organic matter (SOM) pools and only simulated them to a shallow depth in soil. Efforts to overcome these limitations have prompted the development of new generation SOM models, including MEMS 1.0, which represents measurable biophysical SOM fractions, over the entire root zone, and embodies recent understanding of the processes that govern SOM dynamics. Here we present the result of continued development of the MEMS model, version 2.0. MEMS 2.0 is a full ecosystem model with modules simulating plant growth with above and below-ground inputs, soil water, and temperature by layer, decomposition of plant inputs and SOM, and mineralization and immobilization of nitrogen (N). The model simulates two commonly measured SOM pools – particulate and mineral-associated organic matter (POM and MAOM), respectively. We present results of calibration and validation of the model with several grassland sites in the U.S. MEMS 2.0 generally captured the soil carbon (C) stocks (R2 of 0.89 and 0.6 for calibration and validation, respectively) and their distributions between POM and MAOM throughout the entire soil profile. The simulated soil N matches measurements but with lower accuracy (R2 of 0.73 and 0.31 for calibration and validation of total N in SOM, respectively) than for soil C. Simulated soil water and temperature were compared with measurements and the accuracy is comparable to the other commonly used models. The seasonal variation in gross primary production (GPP; R2 = 0.83), ecosystem respiration (ER; R2 = 0.89), net ecosystem exchange (NEE; R2 = 0.67), and evapotranspiration (ET; R2 = 0.71) were well captured by the model. We will further develop the model to represent forest and agricultural systems and improve it to incorporate new understanding of SOM decomposition.

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