Modeling the processes of soil moisture in regulating microbial and carbon-nitrogen cycling

Wang, Gangsheng; Huang, Wenjuan; Zhou, Guoyi; Mayes, Melanie A.; Zhou, Jizhong

doi:10.1016/j.jhydrol.2020.124777

Modeling the processes of soil moisture in regulating microbial and carbon-nitrogen cycling

Journal Article · Sun Mar 01 23:00:00 EST 2020 · Journal of Hydrology

DOI:https://doi.org/10.1016/j.jhydrol.2020.124777· OSTI ID:1615210

^[1]; Huang, Wenjuan ^[2]; Zhou, Guoyi ^[3]; ^[4]; Zhou, Jizhong ^[5]

Univ. of Oklahoma, Norman, OK (United States)
Chinese Academy of Sciences (CAS), Guangzhou (China). South China Botanical Garden; Iowa State Univ., Ames, IA (United States)
Nanjing Univ. of Information Science & Technology (China)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Univ. of Oklahoma, Norman, OK (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Tsinghua Univ., Beijing (China)

Soil carbon (C) and nitrogen (N) cycles and their complex responses to hydro-climatic forcing have gained increasing attention. While the temperature effects have been intensively studied, soil moisture response functions (SMRFs) are not well documented for various microbial and enzymatic processes due to the difficulties in directly measuring and differentiating the moisture effects on various processes. In this work we extended our C-only Microbial-ENzyme Decomposition (MEND) model to the C-N coupled MEND model with flexible element stoichiometry. Our model calibration showed good agreement between simulated and observed C:N ratios in soil organic matter and microbial biomass, as well as the ammonium and nitrate concentrations. We show that the selection of SMRFs for specific biogeochemical processes could result in significant differences in model simulated microbial and C-N processes. In particular, it is essential to account for the soil moisture effects on microbial dormancy and resuscitation, as the changes in microbial physiology under favorable or stressful conditions will exert strong controls on soil C and N dynamics. We also advocate the utilization of dynamic (time-variant) data (e.g., litter input, N deposition, soil temperature and moisture), instead of time-invariant data, to drive model simulations and analyses. Dynamic forcing data (particularly dynamic soil moisture) better represent the real-world climate and environmental conditions, which could facilitate more realistic modeling and understanding of soil C and nutrient cycling in a changing world.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); National Natural Science Foundation of China (NSFC)

Grant/Contract Number:: AC05-00OR22725; SC0004730; SC0004601; SC0014079; SC0016247; SC0010715

OSTI ID:: 1615210

Alternate ID(s):: OSTI ID: 1691633

Journal Information:: Journal of Hydrology, Journal Name: Journal of Hydrology Journal Issue: C Vol. 585; ISSN 0022-1694

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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54 ENVIRONMENTAL SCIENCES
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