Australian net (1950s–1990) soil organic carbon erosion: implications for CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; emission and land–atmosphere modelling

Chappell, Adrian; Webb, Nicholas P.; Rossel, Raphael A. Viscarra; Bui, Elisabeth N.

doi:10.5194/bg-11-5235-2014

Cited by 31 publications

(16 citation statements)

References 46 publications

(62 reference statements)

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“…A global N deposition model product from 1860 to 2100 offers dynamic forcing variables for coupled C-N models [Lamarque et al, 2010]. Simulating horizontal and vertical movements caused by soil erosion at regional and global scales will require a global net soil redistribution map [Chappell et al, 2014] to provide boundary conditions for global land models.…”

Section: Representation Of External Variables In Esmsmentioning

confidence: 99%

Toward more realistic projections of soil carbon dynamics by Earth system models

Luo

Ahlström

Allison

et al. 2016

Global Biogeochemical Cycles

385

360

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Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool-and flux-based data sets through data assimilation is LUO ET AL.SOIL CARBON MODELING 40 PUBLICATIONS

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Section: Representation Of External Variables In Esmsmentioning

confidence: 99%

Toward more realistic projections of soil carbon dynamics by Earth system models

Luo

Ahlström

Allison

et al. 2016

Global Biogeochemical Cycles

385

360

View full text Add to dashboard Cite

show abstract

“…There are a few studies involving techniques of quantitative measurement of SOC/TC transported by erosion from a watershed or a well-demarcated area. In Australia, Chappell et al [25] estimated the magnitude of 137 Cs -derived redistribution of SOC by all processes (water, wind, and tillage) at 4 Tg SOC/yr for 1950-1990s. This represents an average loss of 2% of TC stock, assuming that total C is mineralized as CO 2 , and would represent a net national flux of 15 Tg CO 2 eq/yr from all C pools in Australia.…”

Section: Country/region Study Duration (Yr) Soc Erosion Erosion Typesmentioning

confidence: 99%

“…By credibly accounting for the effects of erosion on net C exchange between the soil and the atmosphere, it may be possible to identify global hot spots of undertaking targeted interventions to mitigate the erosion-induced positive feedback to global warming. In Australia, Chappell et al [25] found SOC erosion by all processes at 4 Tg/yr. (or 2% of total C stock in 10-cm depth).…”

Section: Implications Of Ignoring Erosion Induced Transport Of Carbonmentioning

confidence: 99%

Soil Erosion and Gaseous Emissions

Lal

2020

Applied Sciences

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Accelerated soil erosion by water and wind involves preferential removal of the light soil organic carbon (SOC) fraction along with the finer clay and silt particles. Thus, the SOC enrichment ratio in sediments, compared with that of the soil surface, may range from 1 to 12 for water and 1 to 41 for wind-blown dust. The latter may contain a high SOC concentration of 15% to 20% by weight. The global magnitude of SOC erosion may be 1.3 Pg C/yr. by water and 1.0 Pg C/yr. by wind erosion. However, risks of SOC erosion have been exacerbated by the expansion and intensification of agroecosystems. Such a large magnitude of annual SOC erosion by water and wind has severe adverse impacts on soil quality and functionality, and emission of multiple greenhouse gases (GHGs) such as CO2, CH4, and N2O into the atmosphere. SOC erosion by water and wind also has a strong impact on the global C budget (GCB). Despite the large and growing magnitude of global SOC erosion, its fate is neither adequately known nor properly understood. Only a few studies conducted have quantified the partitioning of SOC erosion by water into three components: (1) redistribution over land, (2) deposition in channels, and (3) transportation/burial under the ocean. Of the total SOC erosion by water, 40%–50% may be redistributed over the land, 20%–30% deposited in channels, and 5%–15% carried into the oceans. Even fewer studies have monitored or modeled emissions of multiple GHGs from these three locations. The cumulative gaseous emissions may decrease at the eroding site because of the depletion of its SOC stock but increase at the depositional site because of enrichment of SOC amount and the labile fraction. The SOC erosion by water and wind exacerbates climate change, decreases net primary productivity (NPP) and use efficiency of inputs, and reduces soils C sink capacity to mitigate global warming. Yet research information on global emissions of CH4 and N2O at different landscape positions is not available. Further, the GCB is incomplete and uncertain because SOC erosion is not accounted for. Multi-disciplinary and watershed-scale research is needed globally to measure and model the magnitude of SOC erosion by water and wind, multiple gaseous emissions at different landscape positions, and the attendant changes in NPP.

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“…Using remote-sensing observations, Ginoux et al (2012) estimated that anthropogenic windblown dust sources account for 75 % of emissions in Australia and 25 % globally. Windblown dust emissions from cropland is of global importance (Mendez and Buschiazzo, 2010;Singh et al, 2012;Wang et al, 2013;Chappell et al, 2014;Xi and Sokolik, 2016).…”

Section: Introductionmentioning

confidence: 99%

Multimodel simulations of a springtime dust storm over northeastern China: implications of an evaluation of four commonly used air quality models (CMAQ v5.2.1, CAMx v6.50, CHIMERE v2017r4, and WRF-Chem v3.9.1)

Zhang

Gao

et al. 2019

Geosci. Model Dev.

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Abstract. Mineral dust particles play an important role in the Earth system, imposing a variety of effects on air quality, climate, human health, and economy. Accurate forecasts of dust events are highly desirable to provide an early warning and inform the decision-making process. East Asia is one of the largest dust sources in the world. This study applies and evaluates four widely used regional air quality models to simulate dust storms in northeastern China. Three dust schemes in the Weather Research and Forecasting model with Chemistry (WRF-Chem) (version 3.9.1), two schemes in both CHIMERE (version 2017r4) and CMAQ (version 5.2.1), and one scheme in CAMx (version 6.50) were applied to a dust event during 4–6 May 2015 in northeastern China. Most of these models were able to capture this dust event with the exception of CAMx, which has no dust source map covering the study area; hence, another dust source mask map was introduced to replace the default one for the subsequent simulation. Although these models reproduced the spatial pattern of the dust plume, there were large discrepancies between predicted and observed PM10 concentrations in each model. In general, CHIMERE had relatively better performance among all simulations with default configurations. After parameter tuning, WRF-Chem with the Air Force Weather Agency (AFWA) scheme using a seasonal dust source map from Ginoux et al. (2012) showed the best performance, followed by WRF-Chem with the UOC_Shao2004 scheme, CHIMERE, and CMAQ. The performance of CAMx had significantly improved by substituting the default dust map and removing the friction velocity limitation. This study suggested that the dust source maps should be carefully selected on a regional scale or replaced with a new one constructed with local data. Moreover, further study and measurement of sandblasting efficiency of different soil types and locations should be conducted to improve the accuracy of estimated vertical dust fluxes in air quality models.

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Australian net (1950s–1990) soil organic carbon erosion: implications for CO<sub>2</sub> emission and land–atmosphere modelling

Cited by 31 publications

References 46 publications

Toward more realistic projections of soil carbon dynamics by Earth system models

Toward more realistic projections of soil carbon dynamics by Earth system models

Soil Erosion and Gaseous Emissions

Multimodel simulations of a springtime dust storm over northeastern China: implications of an evaluation of four commonly used air quality models (CMAQ v5.2.1, CAMx v6.50, CHIMERE v2017r4, and WRF-Chem v3.9.1)

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