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Journal of Resources and Ecology >

2019 , Vol. 10 >Issue 2: 184 - 195

DOI: https://doi.org/10.5814/j.issn.1674-764X.2019.02.009

Farmland Ecosystem

Spatial Analysis of the Soil Carbon Sequestration Potential of Crop-residue Return in China Based on Model Simulation

  • CHEN Jinghua 1, 2 ,
  • WANG Shaoqiang , 1, 2, 3, * ,
  • Florian KRAXNER 4 ,
  • Juraj BALKOVIC 4 ,
  • XU Xiyan 5 ,
  • SUN Leigang 6
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  • 1. Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Beijing 100101, China
  • 2. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
  • 3. School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
  • 4. Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, Laxenburg A-2361, Austria
  • 5. Key Laboratory of Regional Climate-Environment for East Asia, Institute of Atmospheric Physics, Beijing 100029, China
  • 6. Hebei Engineering Research Center for Geographic Information Application, Institute of Geographical Sciences, Hebei Academy of Sciences, Shijiazhuang 050011, China
*Corresponding author: WANG Shaoqiang, E-mail:

Received date: 2018-10-22

  Accepted date: 2018-12-10

  Online published: 2019-03-30

Supported by

Foundation: The National Key Research and Development Program of China (2017YFC0503803)

General Program of National Natural Science Foundation of China (41571192)

The National Key Research and Development Program of China (2016YFA0600202)

Science and Technology Planning Project of Hebei, China (17390313D).

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Abstract

Crop-residue return is a recommended practice for soil and nutrient management and is important in soil organic carbon (SOC) sequestration and CO2 mitigation. We applied a process-based Environmental Policy Integrated Climate (EPIC) model to simulate the spatial pattern of topsoil organic carbon changes from 2001 to 2010 under 4 crop-residue return scenarios in China. The carbon loss (28.89 Tg yr-1) with all crop-residue removal (CR0%) was partly reduced by 22.38 Tg C yr-1 under the status quo CR30% (30% of crop-residue return). The topsoil in cropland of China would become a net carbon sink if the crop-residue return rate was increased from 30% to 50%, or even 75%. The national SOC sequestration potential of cropland was estimated to be 25.53 Tg C yr-1 in CR50% and 52.85 Tg C yr-1 in CR75%, but with high spatial variability across regions. The highest rate of SOC sequestration potential in density occurred in Northwest and North China while the lowest was in East China. Croplands in North China tended to have stronger regional SOC sequestration potential in storage. During the decade, the reduced CO2 emissions from enhanced topsoil carbon in CR50% and CR75% were equivalent to 1.4% and 2.9% of the total CO2 emissions from fossil fuels and cement production in China, respectively. In conclusion, we recommend encouraging farmers to return crop-residue instead of burning in order to improve soil properties and alleviate atmospheric CO2 rises, especially in North China.

Key words： cropland; crop-residue return; soil carbon sequestration; spatial pattern; EPIC model

Cite this article

CHEN Jinghua , WANG Shaoqiang , Florian KRAXNER , Juraj BALKOVIC , XU Xiyan , SUN Leigang . Spatial Analysis of the Soil Carbon Sequestration Potential of Crop-residue Return in China Based on Model Simulation[J]. Journal of Resources and Ecology, 2019 , 10(2) : 184 -195 . DOI: 10.5814/j.issn.1674-764X.2019.02.009

1 Introduction

Climate change is linked to rising carbon dioxide (CO2) and other greenhouse gases in the atmosphere caused by human activities. Mitigating the consequences of increasing atmospheric CO2 requires reducing anthropogenic CO2 emissions and removing CO2 from the atmosphere. Terrestrial carbon (C) sequestration is accomplished through land and soil management practices to enhance the storage of carbon or remove atmospheric CO2 into terrestrial ecosystems. During the 2000s, global terrestrial ecosystems absorbed carbon at a rate of 1.5±0.9 Pg C yr-1, offsetting around 20% of fossil fuel combustion and cement production (7.8±0.6 Pg C yr-1) (Ciais et al., 2013). Increasing agricultural soil carbon is a way to sequester CO2 and mitigate climate change. It is estimated that 0.4-0.9 Pg C yr-1 of atmospheric CO2 can be sequestered in global agricultural soils (Paustian et al., 1998; Lal, 2004a). The arable land in China is estimated to be around 106 Mha, accounting for about 7.5% of the world’s total cropland (FAO, 2014). Due to long intensive cultivation and the use of crop-residues as fuel or fodder, the C content level is relatively low in China’s agricultural soils (Qin et al., 2013). This land may have a large C sequestration potential if agricultural land management is improved.
The recommended management practices for cropland including no-tillage, conservation tillage, returning crop- residues and other biosolids to the soil, and even nitrogen fertilization may benefit SOC sequestration by increasing C input and/or decreasing C output, if practiced under appropriate management (Lal, 2002; Yan et al., 2007; Lu et al., 2009). The SOC sequestration potential was estimated at 23 Tg C yr-1 for conservation tillage in the European Union (Smith et al., 1998) and 17.8-35.7 Tg C yr-1 for conservation tillage and 11-67 Tg C yr-1 for residue management in the USA (Follett, 2001). The SOC sequestration potential of China’s cropland has been estimated to be 12.1-41.1 Tg C yr-1 for no-tillage (Lu et al., 2009; Tang et al., 2006) and 23.2 Tg C yr-1 for 50% crop-residue return (Yan et al., 2007). Crop-residue return significantly increased organic C in the topsoil of China’s cropland during the 1980s and 1990s (Huang and Sun, 2006). Soil C content increases with an increase in the quantity of residue returned to the soil (Larson et al., 1972; Rasmussen et al., 1980; Duiker and Lal, 1999). Returning residues to the soil converts soils from sources to sinks of atmospheric CO2 by enhancing soil productivity (Rasmussen et al., 1998). Soil C loss could be prevented when 2.1 Mg C ha-1 yr-1 were incorporated into China’s cropland (Wang et al., 2015). However, crop-residue removal for fuel and fodder is common worldwide, especially in developing countries in South Asia and Africa. These removals not only cause low organic matter inputs to soil but increase erosion losses of organic matter on the soil surface (Han et al., 2016).
Crop-residue production in China has been estimated at around 630 Tg yr-1 (Liu et al., 2008). Crop-residues are mainly returned to cropland, burned in the field, or removed for household fuel, fodder, power generation and papermaking. A large portion of crop-residue is directly burned in the field, especially in grain-producing regions with low population densities, industrially developed regions, and fossil fuel producing regions (Cao et al., 2006). Annual emissions of CO2 associated with biomass combustion (include burned in the field and as household fuel) in China ranged from 280 to 485 Tg (Streets et al., 2003; Palmer et al., 2003; Pétron et al., 2004; Yan et al., 2006; Zhang et al., 2008). In 2000, 201.20 Tg of CO2 emissions from field burning of around 23.0% of the total crop-residues contributed to 6.13% of the total national CO2 emissions (Cao et al., 2008). Actually, crop-residues are forbidden to be burned in the field by government regulations and laws, and encouraged to be returned to soils with subsidies since 1997 (Liu et al., 2012). The ban on crop-residue burning was restated in the National Modern Agriculture Development Plan (2011- 2015) (The State Council of the People’s Republic of China, 2012). The Ministry of Agriculture of the People’s Republic of China (MOA) encourages comprehensive utilization of crop-residues, including covering, burying, or returning as organic fertilizer, rather than burning.
The cropland of China would be capable of taking in additional C into the soil by returning crop-residues (Yan et al., 2007; Lu et al., 2009, 2015; Lou et al., 2011). Lu et al. (2009) extrapolated site-level SOC sequestration rates to obtain the SOC sequestration potential of crop-residue return in China at a national level. Based on over 150 field experiments across China, a meta-analysis indicated that 100% crop-residue return increased SOC storage by 81 Tg yr-1 for the first 5 years and 56.2 Tg yr-1 for a long period (20 years) (Lu, 2015). However, SOC sequestration is a complex process influenced by many factors, such as inputs from crop-residues, initial soil carbon levels and climatic and soil conditions, and thus shows high spatiotemporal heterogeneity. Although meta-analysis-based estimates quantified the SOC changes in a certain time period, spatial heterogeneity would still generate a large amount of uncertainty in estimates, particularly in regions where few measurements are available. Processes-based modeling, however, provides a more reliable theoretical foundation by integrating SOC dynamics with environmental factors and quantifying the effects of management practices (Smith et al., 1997; Yan et al., 2007). Although previous studies have simulated the spatial pattern of SOC changes from crop-residue return in China’s cropland (Tang et al., 2006; Yan et al., 2007), the return rates of crop-residues in these simulations were roughly set without the crop-residue utilization status taken into account. Particularly, SOC sequestration in topsoil strongly depends on the return rate of crop-residues, according to research based on an experimental site in Jianping County, Northeast China (Lou et al., 2011).
Here, a combination of a process-based Environmental Policy Integrated Climate (EPIC) model and spatially heterogeneous input datasets were applied to integrate the effects of various factors influencing soil C sequestration. A series of crop-residue return scenarios were set according to the actual utilization of crop-residues in China. We employed the EPIC model to simulate cropland SOC dynamics in a spatially explicit way based on climate data and crop production data from 2000 to 2010, so as to assess the potential of crop-residue return on SOC sequestration and explore effective C sequestration options at regional and national scales. Objectives of this paper are: 1) to assess the SOC dynamics of China’s cropland and its spatial pattern under different crop-residue return scenarios; and 2) to analyze and compare the potential of SOC sequestration for increasing crop-residue return across regions in China.

2 Methods and data

2.1 The EPIC model

We used the EPIC model to simulate the impact of crop- residue return on topsoil organic carbon in cropland of China. The EPIC model is a process-based model designed to predict the effects of management decisions on soil, water, nutrient and pesticide movements and their combined impact on soil loss, water quality and crop yields for regions with homogeneous soil and management. In EPIC, crop- residues added to the soil surface or belowground are split into two litter compartments: metabolic and structural, depending on N and lignin content. As the soil organic matter model in EPIC described, soil organic C and N are allocated into three compartments as functions of soil temperature and moisture: microbial biomass, slow humus and passive humus (Izaurralde et al., 2006). These three compartments of soil are different in size, function and turnover times. The soil C change is regulated by both inputs and decomposition rates of C. The density of organic carbon (t C ha-1) in the soil to a plow layer depth of 20 cm (OCPD), as one of the major soil carbon outputs in the EPIC model, and accounts for disturbance from tillage, irrigation and fertilization, carbon respiration from soil, leaching of carbon and carbon lost in runoff and eroded sediment (Elshout et al., 2015).
The EPIC model has been widely applied in the USA (Williams et al., 1984; Izaurralde et al., 2003), Europe (van der Velde et al., 2009), China (Lin et al, 2013; Zhao et al., 2013) and globally (Liu et al., 2007, 2013; Balkovic et al., 2013, 2014). It has been validated by measured data at different agricultural stations in China. Good agreement (R2≥0.87, P<0.01) was found between simulated and measured rice yields and SOC changes in paddy fields at Qianyanzhou (QYZ, 2006-2011) and Yingtang Ecological Experiment Station (YT, 1989-2002) (Lin et al., 2013). We also applied the model to estimate variations in SOC using optimized wheat and corn parameters and compared this to long-term experiment data (2004-2009) at Yucheng agricultural station (YC). The simulated results were consistent with measured ones (R2=0.85, P<0.01), and captured SOC dynamics with or without crop-residue return (Fig. 1).
Fig. 1 Model validation through long-term experiment at Yucheng agricultural station

2.2 Input data

We used EPIC version v.0509 to run on a daily time-step for long-term simulations (hundreds of years). Simulations were driven by weather statistics, soil texture data, crop types and crop management information at a spatial resolution of 10 km×10 km. Each grid was set as a simulation unit and supposed to be an internally homogeneous crop system, meteorological and soil situation. The daily meteorological data at ~660 meteorological stations across China from 2001 to 2010 were interpolated to individual 1-km pixels using ANUSPLIN (Hutchinson, 2004) and then spatially resampled to 10-km pixels. Based on the 1:1,000,000 scale Soil Map of China and databases from the 2nd National Soil Survey conducted from the late 1970s to the early 1990s (Shi et al., 2002; Liu et al., 2006), soil texture data was interpolated in a unified spatial resolution of 10×10 km2. The cropland distribution was obtained from the National Land Cover Project Dataset based on Landsat ETM+ images acquired in 1999 and 2000 for China (Liu et al., 2003, 2005). Thus, the cropping systems were simplified to dryland with a wheat-corn rotation system and paddy fields with double-cropping rice system. Drylands with a wheat-corn rotation system were mainly concentrated in northern China, while paddy fields with double-cropping rice were in southern China (Fig. 2). YC and QYZ are typical agricultural stations of wheat-corn rotation system and double-cropping rice system, respectively (Fig. 2). The optimized crop parameters and field management information implemented in this study (Table 1, 2) were obtained from model optimization and validation at these two stations.
Fig. 2 The distribution map of cropland in China (2000)
Table 1 Optimized crop parameters of wheat, corn and rice in the EPIC model
Parameter Wheat Corn Rice
Default value Optimized value Default value Optimized value Default value Optimized value
HI 0.45 0.47 0.5 0.55 0.2 0.5
DMLA 6 - 6 7 6 -
DLAI 0.6 0.5 0.8 0.6 0.8 0.9
HMX (m) 1 - 2 2.5 0.8 -
RDMX (m) 2 - 2 2.5 2 -
WYSF 0.21 0.2 0.4 - 0.25 -

Note: Abbreviations: HI, harvest index; DMLA, maximum potential leaf area index (LAI); DLAI, fraction of the growing season when LAI begins to decline; HMX, maximum crop height; RDMX, maximum root depth; WSYF, lower limit of harvest index.

Table 2 Field management calendar for wheat-corn rotation and double-cropping rice system
Item Date
Wheat-corn rotation Double-cropping rice
Build furrow dikes - 20-Apr
Cultivate - 25-Apr
Plant 24-Oct (wheat) 25-Apr
Irrigate 13-Mar 2-May
Apply pesticide 25-Mar 20-May
Harvest 15-Jun 10-Jul
Cultivate - 31-Jul
Plant 27-Jun (corn) 1-Aug
Apply pesticide 18-Jul 20-Aug
Harvest 2-Oct 5-Nov

2.3 Crop-residue return scenarios

In China, around 30% of crop-residues are directly returned to cropland (Cui et al, 2008), while around 20% (ranged from 17% to 22.3%) of crop-residues are directly burned in the field (Streets et al., 2003; Yan et al., 2006; Liu et al., 2008; Zhang et al., 2008; Zhao et al., 2011) and 25% is used as household fuel (Cui et al., 2008). In order to describe the possibility of SOC sequestration by crop-residue return as comprehensively as possible, we applied the EPIC model to simulate the SOC dynamics of China’s cropland for a decade under 4 scenarios corresponding to different utilization of crop-residues in China: 1) CR0% estimated baseline SOC changes with crop-residue removal, 2) CR30% represented the status quo scenario with actual 30% crop-residue return, 3) CR50% corresponded to 50% crop-residue return, meaning more crop-residues that were otherwise burned directly in the field (around 20%) would be returned to cropland on the basis of CR30%, and 4) CR75% represented that crop-residues burned as household fuels (around 25%) would be additionally returned on the basis of CR50%. The first two scenarios were applied to assess the contribution of actual crop-residue return to SOC sequestration in China, while the other two were implemented to represent possible future scenarios to evaluate the significance of potential crop-residue management on CO2 mitigation.
Corn, wheat and rice are three major cereal crops in China. They comprise 80 million hectares and their annual residues account for more than 75% of total crop-residues (STEMOA, 2010). We calculated the quantities of aboveground crop-residues using crop production statistics (NBSPRC, 2011) and crop-to-residue ratios (CRR) (CAREI, 2000; Cao et al., 2006). The annual crop production and areas of these three major cereal crops for each province of China were taken from MOA statistics for 2000 to 2009 (Table 3). According to the two cropping systems, corn and wheat residues were accumulated for dryland, and rice residues for paddy fields. The 4 scenarios were implemented with the model input of crop-residues (RSD, t ha-1) that was calculated by the corresponding return rate and yield of crop-residue.
Table 3 Annual residue yields and cultivated areas of wheat, corn and rice
Year Total crop-residue (TCR, Mt) Cultivated area
(A, Mha)		 Yield of crop-residue
(CR, t ha-1)
Wheat Corn Rice Wheat Corn Rice Dryland Paddy field
2000 136.10 211.99 117.07 26.65 23.06 29.96 7.00 3.91
2001 128.23 228.18 110.63 24.66 24.28 28.81 7.28 3.84
2002 123.34 242.62 108.74 23.91 24.63 28.20 7.54 3.86
2003 118.14 231.66 100.09 22.00 24.07 26.51 7.59 3.78
2004 125.62 260.68 111.59 21.63 25.45 28.38 8.21 3.93
2005 133.13 278.76 112.87 22.79 26.36 28.85 8.38 3.91
2006 147.45 303.27 113.58 23.61 28.46 28.94 8.65 3.92
2007 149.31 304.60 115.90 23.72 29.48 28.92 8.53 4.01
2008 153.63 331.83 119.55 23.62 29.86 29.24 9.08 4.09
2009 156.88 327.71 121.79 24.29 31.18 29.63 8.74 4.11
$TC{{R}_{i}}=TC{{P}_{i}}\times CR{{R}_{i}}$ (1)
$C{{R}_{\text{dryland}}}={\sum\limits_{i=1}^{2}{TC{{R}_{i}}}}/{\sum\limits_{i=1}^{2}{{{A}_{i}}}}\;$ (2)
$C{{R}_{\text{paddyfield}}}=TC{{R}_{i=3}}/{{A}_{i=3}}$ (3)
$RS{{D}_{\text{dryland}\left( \text{paddyfield} \right)}}=C{{R}_{\text{dryland}\left( \text{paddyfield} \right)}}\times n%$ (4)
Where TCRi is the total crop-residues (Mt) for a particular crop type (i), i = 1, 2, 3 for corn, wheat and rice; TCPi represents total crop production (Mt); CRRi is crop-to- residue ratio, 2.0 for corn, 1.366 for wheat and 0.623 for rice; Ai is the area of cultivated croplands in China (Mha); and CRdryland and CRpaddy field represent the yield of crop-residues (t ha-1) in two cropping systems respectively. Thus, the model input RSD in the current year is calculated from CR in previous year and the return rates (n %).

2.4 Spatial analysis

In each simulation unit, ROCPD (t C ha-1 yr-1), conducted by equation (5), reflected the rate of SOC changes in China’s cropland.
${{R}_{OCPD}}=\frac{OCP{{D}_{2010}}-OCP{{D}_{2000}}}{10}$ (5)
According to $R_{OCPD_{CRn\%}}$ under different return scenarios (the subscript CRn% represented the selected crop-residue return scenario), the rate of SOC sequestration potential in C density (RSCSP, t C ha-1 yr-1) was calculated as following:
${{R}_{SCS{{P}_{CRn\%}}}}={{R}_{OCP{{D}_{CRn\%}}}}-{{R}_{OCP{{D}_{CR30\%}}}}$ (6)
For a regional comparison, China was divided into 8 agricultural regions by combining geographically close, agriculturally and economically similar provinces (Fig. 3). The 8 regions included Northeast China (Heilongjiang, Jilin and Liaoning provinces), North China (Beijing, Tianjin, Hebei, Inner Mongolia, Shandong and Shanxi provinces), Northwest China (Xinjiang, Ningxia, Gansu and Shaanxi provinces), Southwest China (Sichuan, Yunnan, Chongqing and Guizhou provinces), Central China (Henan, Hubei, Hunan and Jiangxi provinces), East China (Shanghai, Zhejiang, Jiangsu, Anhui, Fujian and Taiwan provinces), South China (Guangdong, Guangxi, Hainan, Hong Kong and Macao), and the Tibetan Plateau (Tibet and Qinghai provinces).
Fig. 3 Eight agricultural regions of China
For each crop-residue return scenario, the SOC sequestration potential in C storage (SCSP, Tg C yr-1) was calculated by multiplying the regional average RSCSP ($\overline{{{R}_{SCS{{P}_{j,k}}}}}$, j=1, for dryland, j=2, for paddy field; k=1,…,8) (t C ha-1 yr-1) and the area of corresponding region Ai,k (ha) , then the sum for the whole country was found.
$SCS{{P}_{k}}=\overline{{{R}_{SCS{{P}_{1,k}}}}}\times ({{A}_{1,k}}+{{A}_{2,k}})+\overline{{{R}_{SCS{{P}_{2,k}}}}}\times {{A}_{3,k}}$ (7)
$SCSP=\sum\limits_{k=1}^{8}{SCS{{P}_{k}}}$ (8)
China annually released more than 6 Pg CO2-eqv since 2005, surpassing the United States as the biggest CO2 emission country (Le Quéré et al., 2016). To assess the significance of raising the crop-residue return rate from 30% to 50%, and even 75%, we compared CO2 mitigation from crop-residue return with total CO2 emissions from fossil fuels and cement production in China (Boden et al., 2016). The CO2 mitigation from crop-residue return was calculated by the SCSP and the C-CO2 conversion coefficient (44/12).

3 Results

3.1 Spatial pattern of SOC dynamics under different crop-residue return scenarios

As illustrated in Fig. 4 and Table 4, CR50% and CR75% led to net C uptake instead of C loss in CR0% and CR30%, and ROCPD (annual average variation rate of the organic carbon in the topsoil) showed spatial variability. When all crop-residues were removed, soil carbon was lost at an average rate of 0.37 t ha-1 yr-1 in China’s cropland (Table 4), leading to a total carbon loss of 28.89 Tg C yr-1. The highest C loss occurred in the Northeast China Plain (Fig. 4a). Under the CR30% scenario, the close-to-zero ROCPD (Fig. 4b) reflected that crop-residue return had already mitigated the soil carbon loss. Compared with CR0%, the total carbon loss has been mitigated at 22.38 Tg C yr-1. The rate of carbon loss in Northeast China decreased from 0.60 t ha-1 yr-1 to 0.05 t ha-1 yr-1. Although mild carbon loss still occurred in a majority of regions, SOC storage increased in North and Northwest China (Table 4). CR30% changed the topsoil in North and Northwest China from net C loss to C uptake. If 50% of crop-residues were returned, the whole cropland in China would turn to a net carbon uptake (Fig. 4c). The national average ROCPD was 0.29 t C ha-1 yr-1, with the greatest increase of OCPD in Northwest China (0.61 t C ha-1 yr-1). Additionally, the more crop-residue returned to cropland (CR75%), the more carbon was sequestrated (Fig. 4d), even in South China with the lowest ROCPD of 0.18 t C ha-1 yr-1. Under 2 potential crop-residue return scenarios (CR50% and CR75%), ROCPD in North and Northwest China increased most notably among all 8 agricultural regions (Fig. 4c, d).
Table 4 The average and standard deviation (SD) of ROCPD in 8 agricultural regions under 4 crop-residue return scenarios
Region CR0% CR30% CR50% CR75%
ROCPD
(t C ha-1 yr-1)		 SD ROCPD
(t C ha-1 yr-1)		 SD ROCPD
(t C ha-1 yr-1)		 SD ROCPD
(t C ha-1 yr-1)		 SD
Northeast China -0.60 0.41 -0.05 0.20 0.17 0.31 0.66 0.33
North China -0.19 0.30 0.03 0.14 0.56 0.30 0.94 0.19
Northwest China -0.15 0.23 0.05 0.14 0.61 0.32 0.95 0.21
Southwest China -0.51 0.57 -0.20 0.52 0.14 0.62 0.46 0.63
Central China -0.34 0.41 -0.09 0.27 0.19 0.37 0.51 0.49
South China -0.48 0.70 -0.30 0.58 -0.07 0.60 0.18 0.67
East China -0.42 0.40 -0.13 0.25 0.07 0.28 0.36 0.44
Tibetan Plateau -0.39 0.41 0.00 0.30 0.48 0.43 0.84 0.37
Total China -0.37 0.45 -0.07 0.31 0.29 0.45 0.65 0.48
Fig. 4 The spatial pattern of ROCPD under (a) CR0%, the baseline scenario, (b) CR30%, the status quo scenario, (c) CR50% and (d) CR75%, the potential scenarios.

3.2 SOC sequestration potential in C density across China

We mapped RSCSP (the rate of SOC sequestration potential in C density) by increasing the crop-residue return rate from 30% to 50% and 75% (Fig. 5). Under the CR50% scenario, the national RSCSP average was 0.36 t ha-1 yr-1, and the regional average RSCSP ranged from 0.56 t ha-1 yr-1 in Northwest China to 0.20 t C ha-1 yr-1 in East China. Under the CR75% scenario, the national RSCSP doubled (0.72 t C ha-1 yr-1) and RSCSP was more than 0.9 t C ha-1 yr-1 in Northwest and North China and 0.5 t C ha-1 yr-1 in East China. RSCSP under CR50% and CR75% showed similar spatial patterns: higher in northern regions and lower in southern regions. For each region, the SOC sequestration potential was analyzed for dryland and paddy field (Table 5). For dryland, the highest regional RSCSP occurred in Northwest and North China in both potential scenarios. For paddy field, North China maintained a high RSCSP, and the Tibetan Plateau also showed great potential.
Table 5 The SOC sequestration potentials in 8 agricultural regions under CR50% and CR75%
Region Cropland type Area (Mha) RSCSP (t C ha-1 yr-1) SCSP (Tg C yr-1)
CR50% CR75% CR50% CR75%
Northeast China Paddy field 3.20 0.04 0.41 0.14 1.30
Dryland 7.90 0.24 0.76 1.93 5.98
North China Paddy field 0.32 0.14 0.72 0.04 0.23
Dryland 15.98 0.54 0.91 8.64 14.56
Northwest China Paddy field 0.28 0.12 0.57 0.03 0.16
Dryland 5.61 0.59 0.92 3.28 5.17
Southwest China Paddy field 4.52 0.11 0.43 0.49 1.92
Dryland 6.12 0.44 0.76 2.67 4.66
Central China Paddy field 9.40 0.10 0.26 0.93 2.44
Dryland 9.28 0.43 0.87 3.97 8.08
South China Paddy field 4.65 0.12 0.29 0.54 1.37
Dryland 0.71 0.33 0.68 0.24 0.48
East China Paddy field 6.36 0.12 0.31 0.78 1.99
Dryland 5.32 0.33 0.82 1.76 4.36
Tibetan Plateau Paddy field 0.00 0.18 0.45 0.00 0.00
Dryland 0.17 0.49 0.85 0.08 0.14
Total China Paddy field 28.73 0.11 0.34 2.95 9.41
Dryland 51.08 0.44 0.85 22.58 43.44
Total
cropland		 79.81 0.36 0.72 25.53 52.85
Fig. 5 The spatial pattern of RSCSP under (a) CR50% for converting burning crop-residues in the field to return and (b) CR75% for converting burning crop-residues both in the field and as household fuel to return

3.3 SOC sequestration potential in C storage across 8 agricultural regions

Under CR50% and CR75% scenarios, SCSP (the SOC sequestration potential in C storage) in cropland of China was estimated to be 25.53 Tg C yr-1 and 52.85 Tg C yr-1, respectively (Table 5). As for regional SCSP, the highest was in North China, followed by Central China. By increasing CR30% to CR50%, cropland in North China sequestrated 8.68 Tg C yr-1 more, which was about 34.0% of national SCSP. However, the regional SCSP in South China (0.78 Tg C yr-1) was less than one tenth of the highest in North China. The Tibetan Plateau, with the least cropland area, only had a regional SCSP of 0.08 Tg C yr-1. When more crop-residues were returned (CR75%), the maximum and minimum regional SCSP remained in North China and the Tibetan Plateau. Central China has the largest area of cropland but a regional SCSP of 10.52 Tg C yr-1, equal to 71% of that in North China (14.79 Tg C yr-1) under the CR75% scenario. With the half dryland-half paddy field mix in Central China, around 80% of C uptake was in dryland. The strong SOC sequestration capability in dryland led to high regional SCSP in North China due to a dominant dryland distribution, despite the smaller area of total cropland. Thus, North China is the region of first priority for enhancing SOC sequestration by increasing crop-residue return.

3.4 Contribution to mitigate CO2 emissions in China

CO2 mitigation via increasing crop-residue return partly offset total CO2 emissions from fossil fuels and cement production in China (Fig. 6). If the return rate of crop- residues was increased to 50%, the SOC sequestration would equal 936 Tg of CO2 mitigation, meaning 1.4% of total CO2 emissions in China would be offset by converting burning crop-residues in the field to return during the simulated decade. If the rate was increased to 75%, the CO2 mitigation would reach 1938 Tg, offsetting 2.9% of total CO2 emissions. Although the offset grew smaller from 2001 to 2010 because total CO2 emissions in China increased continuously, it could be considerably neutralized by crop- residue return. Therefore, reversal of crop-residue burning to return in cropland will help mitigate CO2 emissions and slow climate change. It is definitely a valuable practice for crop-residue and plays an important role in national sustainable development and global climate change.
Fig. 6 The contribution of CO2 mitigation by the increasing crop-residue return rate from 30% to 50% (a) and 75% (b)

4 Discussion

4.1 Comparison with previous SOC sequestration potential estimates in China

From 1980 to 2000, China’s terrestrial ecosystems were a net carbon sink of 0.19-0.26 Pg C yr-1, equal to absorbing 28%-37% of the nationwide cumulative fossil carbon emissions (Piao et al., 2009). Agricultural soils hold potential for enhanced C sequestration. The SOC storage in cropland, especially at 0-40 cm of depth, was substantially increased by conservational cultivation (Zhao et al., 2017). The topsoil carbon storage of cropland in China increased at a rate of 15.6-36.5 Tg C yr-1 by the combined effects of climate, atmospheric CO2 concentrations and land use change (Huang and Sun, 2006; Pan et al., 2010; Sun et al., 2010; Yu et al., 2012). The soil carbon dynamics of China’s cropland in the above estimates were comprehensively affected, inclusive of coarse crop-residue return. Our model simulation, however, could assess the effect of crop-residue return through comparison of return scenarios.
Our simulations were in good agreement with previously estimated SOC sequestration in China’s cropland by crop- residue return using various methods (Table 6). Compared to a meta-analysis, process-based model simulations overestimate the SOC sequestration of crop-residue return more or less including ours, because the processes and environments are idealized. Among model simulations, the SOC sequestration potential of 25.53 Tg yr-1 by increasing the return rate to 50% in our study (from 30%) is comparable to 54.69 Tg yr-1 in DNDC model simulation (from 15%), which included the triple-cropping system but just simulated a single year. Our estimate is higher than 23.2 Tg yr-1 in the CEVSA simulation (from 25%). The bias may be caused by crop- residues derived from remote sensing-based NPP (Net Primary Productivity) in that study. Besides, the regional RSCSP of CR50% and CR75% in our study was 0.20-0.56 t C ha-1 yr-1 and 0.48-0.91 t C ha-1 yr-1, respectively, relatively lower than the results of field experiments (Lou et al., 2011; Yang et al., 2015). It should be noted that we only considered crop-residue return in our study and that other practices such as N fertilizer also lead to SOC sequestration.
Table 6 Estimated SOC sequestration potential of China’s croplands from different investigators
Scenarios SOC sequestration potential Methods Reference
C storage
(Tg C yr-1)		 C density
(t C ha-1 yr-1)
CR40%-CR90% 36.8 0.28 Meta-analysis Sun et al., 2010
CR100% 48.2-56.2 - Meta-analysis Lu, 2015
CR15%-CR50% 54.69 - DNDC model Tang et al., 2006
CR25%- CR50% 23.2 - GLO-PEM model and CEVSA model Yan et al., 2007
CR25%- CR100% 57.1 - GLO-PEM model and CEVSA model Yan et al., 2007
CR50%(rice), CR95%(corn) 42.23 0.397 Statistical model Han et al., 2008
CR100% 34.4 0.087-0.730 Statistical model Lu et al., 2009
CR 4 t/ha - 0.275 Field experiments Lou et al., 2011
CR 12.4 t/ha - 1.425 Field experiments Lou et al., 2011
CR 3 t/ha + N fertilizer - 1.18 Field experiments Yang et al., 2015
CR 3 t/ha + pig manure compost +
N fertilizer		 - 1.27 Field experiments Yang et al., 2015
CR30%-CR50% 25.53 0.20-0.56 EPIC model This study
CR30%-CR75% 52.85 0.48-0.91 EPIC model This study

4.2 Explanation for the spatial pattern of SOC sequestration potential

There might be multiple explanations for the north-south pattern for RSCSP, such as the amount of crop-residue inputs, efficiency of carbon sequestration and initial soil carbon density. The RSCSP in Northwest and North China was higher than that in South and East China (Fig. 4). Northwest China was estimated to have the highest C sequestration per unit area both in this study and Lun et al. (2016). Dryland dominates cropland in northern agricultural regions of China, especially in Northwest and North China (Fig. 1). It has been reported that crop-residue return with upland cropping shows stronger increases in C storage compared with rice cropping (Lu, 2015). According to production data, a wheat- corn rotation system in dryland produced more crop-residue than double-rice cropping system in paddy field (Table 3). More crop-residues mean more C inputs under the same scenario. Thus, the unequal crop-residue inputs resulted in variation in RSCSP across China.
Additionally, the difference in carbon sequestration potential efficiency in dryland and paddy field partly explained the difference in dryland and paddy field. The efficiency of carbon sequestration potential (CSEp) was the carbon sequestration per crop-residue input compared to CR30% under the potential return scenarios (CR50% and CR75%). Normalized by crop-residue inputs, the CSEp in dryland (0.27 t C /t Crop-residue under CR50%, 0.25 t C /t Crop- residue under CR75%) was much higher than that in paddy field (0.13 t C /t Crop-residue under CR50%, 0.19 t C /t Crop-residue under CR75%) under the same scenarios (Fig. 7a). It illustrated that increasing the crop-residue return rate could be more efficient in dryland than paddy field. The CSEp had smaller standard deviation and higher convergence with the increase of crop-residue inputs; and the frequency distribution of CSEp in dryland was more concentrated than that in paddy field (Fig. 7b). In other words, SOC in dryland increased more efficiently and stably from increasing crop-residue return and might be less influenced by environmental factors than paddy field. Water may play a role whereby carbon sequestration efficiency was higher in arid and semi-arid regions of northwestern China and lower in the humid regions of southern and eastern China (Yan et al., 2007).
Fig. 7 The CSEp (a) and its frequency distribution (b) in dryland and paddy field under 2 potential return scenarios
Initial soil carbon level also influenced the spatial pattern of SOC sequestration potential. Barren soils linearly increase in SOC with increased C inputs through crop-residue return, while soils with high SOC levels close to the storage capacity often do not respond to increased C inputs (Lal, 2000). The average soil carbon density was 32.3 t C ha-1 in the plow layer of China’s cropland (Wang et al., 2004), much lower than the global average range of 50 to 150 t C ha-1 (Lal, 2000). Further, an increasing tendency of soil carbon density was indicated from north to south (Wang et al., 2001). Due to lower soil carbon density, topsoil in northern regions could enhance more carbon by crop-residue return than in southern regions. The spatial pattern of initial soil carbon levels might be a explanation, but further experiments are needed.

4.3 Uncertainty analysis

There are several uncertainties in our estimates due to a lack of available data. Despite topsoil being the main part impacted by cultivation, uncertainties still resulted from not considering SOC dynamics in deep soil (below 20 cm) because of limited soil texture data along a vertically distribution. Additionally, each of our simulation units covered a square area of 100 km2. It is difficult to guarantee the internal homogeneity of all input data in such an area, which might bring about overestimation or underestimation of SOC sequestration. Due to the coarse spatial distribution of land use/cover, spatial heterogeneity was also weakened by simplifying crop systems into wheat-corn rotation system in dryland and double-cropping rice system in paddy field. In northern regions, especially Northeast China, the rice cultivation system in paddy field is mostly single-cropping rice rather than double-cropping rice (Mei et al., 1988). Due to the mismatch of rice cultivation systems, we could overestimate the SOC sequestration potential in paddy field. The return rate varied in different regions, but we set unified return rates for all 8 agricultural regions in our study because spatially explicit residue return rates were unavailable. To quantify and reduce uncertainties in soil carbon changes caused by model inputs, the combination with remote sensing data of high spatial resolution would be helpful, and spatially and temporally explicit climate and soil texture are also needed.
The short period of our simulation might cause overestimation of the SOC sequestration potential of crop-residue return. Through long-term field experiment observations, Stewart et al. (2007) proposed a nonlinear carbon saturation model instead of the linear model to test the SOC-C input relationship. Based on the nonlinear model, the soil carbon has a saturation point and therefore, higher efficiency of C fixation is in soils further from C saturation. A statistical saturation model based on long-term agricultural experiments found that the total SOC sequestration potential till C saturation was 2.7 Pg C or 19.4 t C ha-1 in China’s cropland (Qin et al. 2013). However, compared to the SOC sequestration duration of decades (West and Six, 2007; Lal, 2004b), our model simulation was for a short period of time (10 years), and therefore is unable to explore the soil carbon saturation level under long-term carbon inputs. Longer simulations to verify whether the limit exists are needed.
Some deviations arose from the neglect of CH4 and N2O emissions. Crop-residue return stimulates CH4 from rice paddies and direct N2O emissions (Lu et al., 2010; Li et al., 2005), which are both greenhouse gases and might offset the CO2 mitigation effect of crop-residue return. CH4 emissions from rice paddies in China increased by 4.734 Tg yr-1 from 366.8 Tg yr-1 crop-residue return, equivalent to 118.4 Tg CO2-eqv yr-1 (Lu et al., 2010). According to the DNDC simulation for a maize-wheat double-cropping rotation in Hebei, China, increasing crop-residue return from 15% to 90% led to increases in direct N2O emissions from 13 kg N ha-1 y-1 to 20 kg N ha-1 yr-1 (Li et al., 2005). Due to limitations in the EPIC model, it is difficult to take the emissions of CH4 and N2O from crop-residue return into consideration. For future work, CH4 and N2O emissions from crop-residue return should be collected by long-term field experiments to improve model processes.

5 Conclusions

We used a process-based EPIC model to simulate the spatial pattern of topsoil organic carbon changes under different crop-residue return scenarios in cropland in China based on climate data and crop production data from 2000 to 2010. Our analyses indicated that the actual 30% of return had already mitigated carbon loss at 22.38 Tg C yr-1 but did not offset all loss under the crop-residue removal scenario. If the return rate was increased from 30% to 50%, cropland in China would become a net carbon sink. The reversal of crop-residue burning in the field to return would enhance topsoil carbon density at a national average rate of 0.36 t C ha-1 yr-1. When the return rate reached 75%, the increase in carbon density doubled (0.72 t C ha-1 yr-1). Under CR50% and CR75%, the spatial RSCSP pattern was similarly higher in northern regions and lower in southern regions. Among 8 agricultural regions, the highest RSCSP occurred in Northwest and North China. North China had the most significant SCSP due to its high RSCSP and large cropland area. The national SOC sequestration potential could reach 25.53 Tg C yr-1 under CR50% and 52.85 Tg C yr-1 under CR75%. During the decade, the enhanced topsoil carbon storages under CR50% and CR75% were equivalent to 936 Tg and 1938 Tg CO2 mitigation respectively, offsetting 1.4% and 2.9% of total CO2 emissions from fossil fuels and cement production in China. Returning crop-residues burned in the field or as household fuel to cropland are more conducive to growth of cropland soil carbon and mitigation of CO2 emissions in China, especially North China.
For future work, it is valuable to add CH4 and N2O emissions from crop-residue return to the EPIC model, and combine a more detailed spatial distribution of return rates and land use/cover from high-resolution remote sensing data to reduce model uncertainty and improve accuracy. Future long-term simulation will provide improve agricultural management for GHG mitigation.

The authors have declared that no competing interests exist.

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