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Simulating and Predicting Crop Yield and Soil Fertility under Climate Change with Fertilizer Management in Northeast China Based on the Decision Support System for Agrotechnology Transfer Model

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  • Wenting Yan

    (College of Land and Environment, Shenyang Agriculture University, Shenyang 110866, China)

  • Wenting Jiang

    (College of Land and Environment, Shenyang Agriculture University, Shenyang 110866, China)

  • Xiaori Han

    (College of Land and Environment, Shenyang Agriculture University, Shenyang 110866, China)

  • Wei Hua

    (College of Land and Environment, Shenyang Agriculture University, Shenyang 110866, China)

  • Jinfeng Yang

    (College of Land and Environment, Shenyang Agriculture University, Shenyang 110866, China)

  • Peiyu Luo

    (College of Land and Environment, Shenyang Agriculture University, Shenyang 110866, China)

Abstract

The risks of climate change and soil degradation for the agricultural environment and crop production are increasingly prominent. Based on the limitations of land resources, it is important to explore a sustainable and effective fertilization strategy to reduce risks and ensure there is a high yield of grain and sustainable development of agriculture. Soil fertility underpins cultivated land, which is the most important resource of agricultural production, and is also the key for maintaining agricultural sustainability. The central elements of soil fertility are soil organic carbon (SOC) and soil nitrogen (SN). This study applied the Decision Support System for Agrotechnology Transfer-Cropping System Model (DSSAT-CSM) and the CENTURY-based soil module to simulate the trends of crop yields, SN storages and SOC storages until the end of this century under different climate change circumstances, based on a 36-year long-term experiment established at Shenyang site, China. Four fertilizer practices were applied: control (CK), combined chemical fertilizer of nitrogen, phosphorus, and potassium (NPK), NPK with manure (MNPK), and NPK fertilizers plus a high application rate of manure (hMNPK). The outcomes indicated that the DSSAT model can fully simulate the yields of maize and soybean as well as the dynamic stocks of the SN and SOC. Three Representative Concentration Pathways (RCP 2.6, RCP 4.5, RCP 8.5) for future development were chosen from the fifth assessment report of the United Nations Intergovernmental Panel on Climate Change (IPCC). Moreover, a baseline was installed. Crop yields, SN, and SOC storages from 2016 to 2100 were estimated under four climate scenarios (RCP 2.6, RCP 4.5, RCP 8.5, and Baseline). The RCP scenarios in some treatments reduced SN and SOC stocks and maize yield, and had no effect on soybean yield. However, the application of NPK with manure could improve crop yields, while it increased SN and SOC storages substantially. To some extent, the negative effects of climate scenarios could be mitigated by applying manure. In the RCP 4.5, maize yields of NPK, MNPK, and hMNPK treatments declined by 14.8%, 7.7%, and 6.2%, respectively, compared with that of NPK under Baseline. The NPK fertilizers plus manure treatments could cut the reduction of maize yield caused by climate change in half. Additionally, the SOC storage and SN of chemical fertilizers plus manure treatments under RCP scenarios increased by 20.2%–33.5% and 13.7%–21.7% compared with that of NPK under baseline, respectively. It was concluded that a rational combination of organic and inorganic fertilizer applications is a sustainable and effective agricultural measure to maintain food security and relieve environmental stresses.

Suggested Citation

  • Wenting Yan & Wenting Jiang & Xiaori Han & Wei Hua & Jinfeng Yang & Peiyu Luo, 2020. "Simulating and Predicting Crop Yield and Soil Fertility under Climate Change with Fertilizer Management in Northeast China Based on the Decision Support System for Agrotechnology Transfer Model," Sustainability, MDPI, vol. 12(6), pages 1-20, March.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:6:p:2194-:d:331570
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    References listed on IDEAS

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    1. Timsina, J. & Humphreys, E., 2006. "Performance of CERES-Rice and CERES-Wheat models in rice-wheat systems: A review," Agricultural Systems, Elsevier, vol. 90(1-3), pages 5-31, October.
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    Cited by:

    1. Wu Xiao & Wenqi Chen & Tingting He & Linlin Ruan & Jiwang Guo, 2020. "Multi-Temporal Mapping of Soil Total Nitrogen Using Google Earth Engine across the Shandong Province of China," Sustainability, MDPI, vol. 12(24), pages 1-20, December.
    2. Yue Wang & Xingbin Liu & Luxin Wang & Haotian Li & Shiyu Zhang & Jinfeng Yang & Ning Liu & Xiaori Han, 2023. "Effects of Long-Term Application of Cl-Containing Fertilizers on Chloride Content and Acidification in Brown Soil," Sustainability, MDPI, vol. 15(11), pages 1-10, May.
    3. Zoia Arshad Awan & Tasneem Khaliq & Muhammad Masood Akhtar & Asad Imran & Muhammad Irfan & Muhammad Jarrar Ahmed & Ashfaq Ahmad, 2021. "Building Climate-Resilient Cotton Production System for Changing Climate Scenarios Using the DSSAT Model," Sustainability, MDPI, vol. 13(19), pages 1-26, September.
    4. Anshuman Gunawat & Devesh Sharma & Aditya Sharma & Swatantra Kumar Dubey, 2022. "Assessment of climate change impact and potential adaptation measures on wheat yield using the DSSAT model in the semi-arid environment," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(2), pages 2077-2096, March.
    5. Mohamadzade, Fahime & Gheysari, Mahdi & Eshghizadeh, Hamidreza & Tabatabaei, Mahsa Sadat & Hoogenboom, Gerrit, 2022. "The effect of water and nitrogen on drip tape irrigated silage maize grown under arid conditions: Experimental and simulations," Agricultural Water Management, Elsevier, vol. 271(C).

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