Improving a Biogeochemical Model to Simulate Surface Energy, Greenhouse Gas Fluxes, and Radiative Forcing for Different Land Use Types in Northeastern United States

Abstract

Land use changes exert important impacts on climate, primarily through altering greenhouse gas (GHG) and surface energy fluxes. Biogeochemical models have incorporated a relatively complete suite of biogeochemical processes to simulate GHG fluxes. However, these models often lack detailed processes of surface energy exchange, limiting their ability to assess the impacts of land use change on climate. In this study, we incorporated processes of surface energy exchange into a widely used biogeochemistry model, DeNitrification‐DeComposition (DNDC), so that it can quantify both GHG and energy fluxes between the biosphere and the atmosphere. When tested against field observations for the three dominant land use types (forest, hayfield, and cornfield) in the northeastern United States, the improved DNDC successfully captured the observed fluxes of outgoing shortwave radiation, latent heat, sensible heat, net ecosystem exchange of CO2, and their differences among the three land use types. To evaluate the differences in radiative forcing among these land use types, we conducted 100‐year simulations and converted the modeled GHG fluxes to radiative forcing using an atmospheric impulse response model. Our results show that the 100‐year cumulative differences in net radiative forcing are 3.35 nW m−2 between the hayfield and forest (slight warming) and 43.2 nW m−2 between the cornfield and forest (warming) per hectare land use difference. The cooling effects of increased albedo after the conversion of forest to hayfield or cornfield (observed and modeled in recent years) are gradually offset by the warming effects of the increasing release of GHG as the forest becomes older.

Simulating Soil-Plant-Climate Interactions and Greenhouse Gas Exchange in Boreal Grasslands using the DNDC Model.

“…According to Khan, [48], tillage, which is the standout feature of the 2019 (evaluation) period, can stimulate soil microbial activity and thus respiration. Nevertheless, simulated NEE was not significantly different from observed (-14%), in line with the findings of Deng et al ., [41] who also reported a good match for NEE, and of Abdalla et al, [26] who reported a corelation of R = 0.6 for NEE simulations compared to measured data on permanent grassland in the Republic of Ireland.…”

“…The nitrification, denitrification, and fermentation sub-models simulate C and N transformations that are mediated by soil microbes and controlled by soil environmental factors and concentrations of relevant substrates [39], [40]. The DNDC model adopted in this study was further improved to simulate surface energy exchange, soil frost and thaw dynamics, and C gas fluxes in cold regions [41]- [43].…”

“…This may be linked to the model simulating little or no respiration during the colder months, and to both increase more slowly and decrease more rapidly at the commencement and ending of the growing season compared to measured data. Using the improved DNDC model [41] improved model performance which was able to simulate GHG satisfactorily.…”

A Decreasing Trend of Nitrous Oxide Emissions From California Cropland From 2000 to 2015

“…The DNDC model (Li et al., 1992a , 1992b ) used in this study was originally developed for quantifying carbon (C) sequestration and GHG emissions from agroecosystems, and has been extensively applied to simulate N 2 O emissions from different types of ecosystems (Deng et al., 2020 ; Gilhespy et al., 2014 ; Giltrap et al., 2010 ). The model simulates soil C and N transformations through a series of biogeochemical reactions, such as decomposition, microbial assimilation, plant uptake, ammonium adsorption, ammonia volatilization, nitrification, denitrification, and nitrate leaching.…”

Improving a Biogeochemical Model to Simulate Microbial‐Mediated Carbon Dynamics in Agricultural Ecosystems

“…Furthermore, there are large uncertainties regarding their behaviors in modeling SOC changes and CO 2 fluxes due to very limited model testing against field-scale observations. The process-based biogeochemical model, DNDC, has incorporated a relatively complete suite of biophysical and biogeochemical processes and FMPs, which enables it to simulate vegetation growth, transport and transformations of C and nitrogen (N), SOC changes, and greenhouse gas (GHG) fluxes in terrestrial ecosystems (e.g., Deng et al, 2018Deng et al, , 2020Gilhespy et al, 2014;Giltrap et al, 2010;Li, 2000;Li et al, 1992aLi et al, , 2012. However, DNDC does not explicitly simulate microbial or enzymatic decomposition of SOM, and therefore is unable to reproduce microbial regulations on soil C cycle.…”