Regional carbon and CO2 budgets of North Sea tidal estuaries

Carbon Dynamics Along the Seine River Network: Insight From a Coupled Estuarine/River Modeling Approach

“…Over the first 32 km of the estuary, B0 = 10,000 m and CL = 10,700 m. From this point forward and until Poses, the width was calculated using B0 = 480 m and CL = 105,500 m. The depth profile was approximated by a regular increase from 4.8 m at the mouth to 6.8 m 152 km upstream (i.e., Caudebec) followed by a linear decrease to 2.3 m at the end of the tidal influence at kilometer 168 ( Figure 2B). The use of relatively simple representations of the depth profile was proven sufficient to reproduce the hydrodynamics and transport of several tidal estuaries with C-GEM in previous studies (Scheldt and Elbe Estuaries in Volta et al, 2016b and Delaware Bay in Laruelle et al, 2017a for instance).…”

“…Our study relies on the off-line coupling of two transient, spatially discrete models: C-GEM and pyNuts-Riverstrahler. C-GEM is a recently developed generic estuarine model (Volta et al, 2014(Volta et al, , 2016a which has already been applied to several estuaries distributed along the coast of the North Atlantic Ocean (Volta et al, 2016b;Laruelle et al, 2017a) while the pyNuts-Riverstrahler platform is a well-established model coupling watersheds and river network (Billen et al, 1994;Garnier and Billen, 1994;Thieu et al, 2015). Simulations similar to those described in Marescaux (2018) are first performed with pyNuts-Riverstrahler for year 2010 over the entire Seine watershed.…”

“…pyNuts-Riverstrahler have been extensively validated for the Seine river and the set-up used for the current study is identical to that described in extenso in Marescaux (2018). C-GEM relies on a generic parametrization derived from a large collection of modeling studies performed on temperate estuaries (Volta et al, 2016b). Several modifications to this generic estuarine parameterization were implemented during the calibration stage (namely, the rate of aerobic degradation of organic matter which was increased from 6.08 10 −4 to 1.2 10 −3 µMC•s −1 , the half-saturation constant for TOC degradation which was decreased from 183 to 100 µMC and the nitrification rate which was increased from 2.73 10 −5 to 5 10 −4 µMN•s −1 ) but these calibration values all fall with ranges reported by the literature survey of Volta et al (2016b).…”

Ecosystem Metabolism and Carbon Balance in Chesapeake Bay: A 30‐Year Analysis Using a Coupled Hydrodynamic‐Biogeochemical Model

“…Thus, in this study we quantified seasonal, interannual, and decadal variability in ecosystem metabolism and the associated sources, sinks, and exchange of organic and inorganic carbon in Chesapeake Bay with a coupled hydrodynamic and biogeochemical model (Regional Ocean Modelling System‐Row Column Aesop‐carbonate chemistry). Process‐based models provide a tool to overcome challenges in understanding ecosystem metabolism variability over multiple time and space scales because they quantify physical transport and ecosystem metabolism at high resolution and allow for simulations of future estuarine responses to human activities and climate change (Bianchi et al, ; Hofmann et al, ; Laruelle et al, ; Volta et al, ). The model was configured for a long‐term retrospective simulation (1986–2015) to investigate the interannual variations of carbon balance due to changes in nutrient inputs, hydrological conditions, and atmospheric p CO 2 .…”

Estuarine Dissolved Organic Carbon Flux From Space: With Application to Chesapeake and Delaware Bays

“…Linked hydrodynamic-biogeochemical mechanistic models used to estimate estuary-ocean exchange include explicit representation of the key processes that affect carbon in estuaries, such as advection, gas exchange, photosynthesis, and respiration. These models range in hydrodynamic complexity from 1-D, tidally averaged, advection-diffusion models (Hofmann et al, 2008;Laruelle et al, 2017;Soetaert & Herman, 1995;Volta et al, 2016) to 3-D tidally resolving models (Cerco & Cole, 1993;Feng et al, 2015;Kemp et al, 1997). Biogeochemical complexity can be measured by the number of state variables, which ranges from six (Vanderborght et al, 2007) to 20 (Cerco & Cole, 1993;Soetaert & Herman, 1995).…”