Supporting hierarchical soil biogeochemical modeling: Version 2 of the Biogeochemical Transport and Reaction model (BeTR-v2)

Reliable soil biogeochemical modeling is a prerequisite for credible projections of climate change and associated ecosystem feedbacks. This recognition has called for frameworks that can support flexible and efficient development and application of new or alternative soil biogeochemical modules in earth system models (ESMs). The BeTR-v1 code (i.e., CLM4-BeTR) is one such framework designed to accelerate the development and integration of new soil biogeochemistry formulations into ESMs, and to analyze structural uncertainty in ESM simulations. With a generic reactive transport capability, BeTR-v1 can represent multi-phase (e.g., gaseous, aqueous, and solid), multi-tracer (e.g., nitrate and organic carbon), and multi-organism (e.g., plants, bacteria and fungi) dynamics. Here, we describe the new version BeTR-v2, which adopts more robust numerical algorithms and improves on structural design over BeTR-v1. BeTR-v2 better supports different mathematical formulations in a hierarchical manner by allowing the resultant model be run either for a single topsoil layer, a vertically resolved soil column, or fully coupled with the land component of the Energy Exascale Earth System Model (E3SM). We demonstrate the BeTR-v2 capability with benchmark cases and example soil BGC implementations. By taking advantage of BeTR-v2’s generic structure integrated in E3SM, we then found that calibration could not resolve biases introduced by different numerical coupling strategies of plant-soil biogeochemistry. These results highlight the importance of numerically robust implementation of soil biogeochemistry and coupling with hydrology, thermal dynamics, and plants— capabilities that the open-source BeTR-v2 provides.

Regional oceanic and biogeochemical modeling strategy :forced or coupled model ?

<p><span> Regional high resolution biogeochemical modeling studies generaly use an oceanic model forced by prescribed atmospheric conditions. The computational cost of such approach is far lower than using an high resolution ocean-atmosphere coupled model. However, forced oceanic models cannot represent adequately the atmospheric reponse to the oceanic mesoscale (~10-100km) structures and the impact on the oceanic dynamics.</span></p><p><span>To assess the bias introduce by the use of a forced model, we compare here a regional high resolution (1/12º) ocean-atmosphere coupled model with oceanic simulations forced by the outputs of the coupled simulation. Several classical forcing strategies are compared : bulk formulae, prescribed stress, prescribed heat fluxes with or without Sea Surface Temperature (SST) restoring term, .... We study the Chile Eastern Boundary Upwelling System, and the oceanic model includes a biogeochemical component,</span></p><p><span>The coupled model oceanic mesoscale impacts the atmosphere through surface current and SST anomalies. Surface currents mainly affect the wind stress while SST impacts both the wind stress and the heat fluxes. In the forced simulations, mesoscale structures generated by the model internal variability does not correspond to those of the coupled simulation. According to the forcing strategy, the atmospheric conditions are not modified by the forced model mesoscale, or the modifications are not realistic. The regional dynamics (coastal upwelling, mesoscale activity, …) is affected, with impact on the biogeochemical activity.</span></p><p> </p><p> </p><p><em>This work was supported by the FONDECYT project 3180472 (Chile), with computational support of the NLHPC from the Universidad de Chile, the HPC from the Pontificia Universidad Catolica de Valparaiso and the Irene HPC from the GENCI at the CEA (France).</em></p>

Assessing life cycle impacts from changes in agricultural practices of crop production

Purpose This paper presents an improved methodological approach for studying life cycle impacts (especially global warming) from changes in crop production practices. The paper seeks to improve the quantitative assessment via better tools and it seeks to break down results in categories that are logically separate and thereby easy to explain to farmers and other relevant stakeholder groups. The methodological framework is illustrated by a concrete study of a phosphate inoculant introduced in US corn production. Methods The framework considers a shift from an initial agricultural practice (reference system) to an alternative practice (alternative system) on an area of cropland A. To ensure system equivalence (same functional output), the alternative system is expanded with displaced or induced crop production elsewhere to level out potential changes in crop output from the area A. Upstream effects are analyzed in terms of changes in agricultural inputs to the area A. The yield effect is quantified by assessing the impacts from changes in crop production elsewhere. The field effect from potential changes in direct emissions from the field is quantified via biogeochemical modeling. Downstream effects are assessed as impacts from potential changes in post-harvest treatment, e.g., changes in drying requirements (if crop moisture changes). Results and discussion An inoculant with the soil fungus Penicillium bilaiae has been shown to increase corn yields in Minnesota by 0.44 Mg ha−1 (~ 4%). For global warming, the upstream effect (inoculant production) was 0.4 kg CO2e per hectare treated. The field effect (estimated via the biogeochemical model DayCent) was − 250 kg CO2e ha−1 (increased soil carbon and reduced N2O emissions) and the yield effect (estimated by simple system expansion) was − 140 kg CO2e ha−1 (corn production displaced elsewhere). There were no downstream effects. The total change per Mg dried corn produced was − 36 kg CO2e corresponding to a 14% decrease in global warming impacts. Combining more advanced methods indicates that results may vary from − 27 to − 40 kg CO2e per Mg corn. Conclusion and recommendations The present paper illustrates how environmental impacts from changes in agricultural practices can be logically categorized according to where in the life cycle they occur. The paper also illustrates how changes in emissions directly from the field (the field effect) can be assessed by biogeochemical modeling, thereby improving life cycle inventory modeling and addressing concerns in the literature. It is recommended to use the presented approach in any LCA of changes in agricultural practices.