Journal of Resources and Ecology ›› 2019, Vol. 10 ›› Issue (2): 184-195.DOI: 10.5814/j.issn.1674-764X.2019.02.009
• Farmland Ecosystem • Previous Articles Next Articles
CHEN Jinghua1,2, WANG Shaoqiang1,2,3,*(), Florian KRAXNER4, Juraj BALKOVIC4, XU Xiyan5, SUN Leigang6
Received:
2018-10-22
Accepted:
2018-12-10
Online:
2019-03-30
Published:
2019-03-30
Contact:
WANG Shaoqiang
Supported by:
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.
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URL: http://www.jorae.cn/EN/10.5814/j.issn.1674-764X.2019.02.009
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 | - |
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 | - |
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 |
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 |
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 |
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 |
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 |
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.
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 |
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
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 |
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 |
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