Quantifying wetland methane emissions with process-based models of different complexities

Abstract

Abstract.Bubbling is an important pathway of methane emissions from wetland ecosystems.However the concentration-based threshold function approach in current biogeochemistry models of methane is not sufficient to represent the complex ebullition process. Here we revise an extant process-based biogeochemistry model, the Terrestrial Ecosystem Model into a multi-substance model (CH 4 , O 2 , CO 2 and N 2 ) to simulate methane production, oxidation, and transport (particularly ebullition) with different model complexities. When ebullition is modeled with a concentrationbased threshold function and if the inhibition effect of oxygen on methane production and the competition for oxygen between methanotrophy and heterotrophic respiration are retained, the model becomes a two-substance system. Ignoring the role of oxygen, while still modeling ebullition with a concentration-based threshold function, reduces the model to a one-substance system. These models were tested through a group of sensitivity analyses using data from two temperate peatland sites in Michigan. We demonstrate that only the four-substance model with a pressure-based ebullition algorithm is able to capture the episodic emissions induced by a sudden decrease in atmospheric pressure or by a sudden drop in water table. All models captured the retardation effect on methane efflux from an increase in surface standing water which results from the inhibition of diffusion and the increase in rhizospheric oxidation. We conclude that to Correspondence to: J. Tang (tang16@purdue.edu) more accurately account for the effects of atmospheric pressure dynamics and standing water on methane effluxes, the multi-substance model with a pressure-based ebullition algorithm should be used in the future to quantify global wetland CH 4 emissions. Further, to more accurately simulate the pore water gas concentrations and different pathways of methane transport, an exponential root distribution function should be used and the phase-related parameters should be treated as temperature dependent.

HIMMELI v1.0: HelsinkI Model of MEthane buiLd-up and emIssion for peatlands

“…HIMMELI also simulates CO 2 transport via all three transport pathways. This is not a common feature in CH 4 models: to our knowledge, only the multi-substance version of TEM (Tang et al, 2010), ecosys (Grant and Roulet, 2002), and the Segers model (Segers and Leffelaar, 2001a-c) included that.…”

“…HIMMELI does not bring any new processes as such into the CH 4 model world and it utilizes process descriptions largely adopted from earlier models (e.g., Arah and Stephen, 1998;Tang et al, 2010;Wania et al, 2010). However, it is among the most complete models considering the transport of compounds.…”

“…Of these, the Xu model (Xu et al, 2007), CLM-Microbe (Xu et al, 2014), and VISIT (Ito and Inatomi, 2012) do not explicitly simulate O 2 transport between the atmosphere and peat. On the other hand, LPJ-WhyMe (Wania et al, 2010), a revised multi-substance version of TEM (Tang et al, 2010), ecosys (version in Grant and Roulet, 2002), and a recent model by Kaiser et al (2017) -not included in the list by Xu et al (2016) -do simulate all these. HIMMELI also simulates CO 2 transport via all three transport pathways.…”

Technical Note: Simple formulations and solutions of the dual-phase diffusive transport for biogeochemical modeling

“…All symbols are defined in Appendix Table A1. where S (C, z) is the tracer source due to processes other than diffusion and C is the bulk tracer concentration including both gaseous and aqueous phases. From the assumption of equilibrium between aqueous and gaseous phases (e.g., Tang et al, 2010):…”

“…The interest in predicting fluxes of various biogenic greenhouse gases and their interactions with climate change has motivated the development of many terrestrial biogeochemical models; e.g., ecosystem methane models (Walter and Heiman, 2000;Zhuang et al, 2004;Tang et al, 2010;Riley et al, 2011), nitrification-denitrification models (Venterea and Rolston, 2000;Maggi et al, 2008), water-CO 2 isotope models (Riley et al, 2002), and generic reactive transport models that attempt to integrate as many biogeochemical processes and chemical species as possible (e.g., Simunek and Suarez, 1993;Grant, 2001;Tang et al, 2013). To resolve the depthdependent dynamics, these models in general represent multiphase (aqueous and gaseous phase) diffusion processes and often assume negligible advection.…”