福建省漳州市水稻物候特征对稻田土壤有机碳制图的影响
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S159.2

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福建省自然科学基金项目(2020J05027)和国家自然科学基金项目(41971050)资助


Effects of Rice Phenological Characteristics on Soil Organic Carbon Mapping in Paddy Fields in Zhangzhou City,Fujian Province
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Supported by the Natural Science Foundation of Fujian Province (No.2020J05027)and the National Natural Science Foundation of China(No.41971050)

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    摘要:

    高精度土壤有机碳制图是研究耕地土壤有机碳时空格局及其影响机制的基础,相关研究结果可为农田“固碳减排”措施的制定提供决策支持。农业管理活动是农田土壤有机碳发生变化的重要影响因子,但基于农业管理活动的土壤有机碳制图却较为少见。基于遥感影像提取的物候参数是农业管理活动的直接反映,在研究农业管理活动对农田土壤有机碳的影响方面有较大应用潜力。基于此,本研究以福建省漳州市水稻田为研究对象,利用随机森林算法,基于5组不同的变量组合(A组:仅自然环境变量;B组:自然环境变量+早稻物候参数:C组:自然环境变量+晚稻物候参数;D组:自然环境变量+早稻物候参数+晚稻物候参数;E组:仅早稻物候参数+晚稻物候参数),分别构建土壤有机碳含量预测模型。通过对比5组模型的预测精度、预测值的空间分布特征和相关影响因子的重要性,分析物候参数对于土壤有机碳制图精度的影响作用,挖掘漳州市水田土壤有机碳制图的主要影响因子,解析对漳州市水田土壤有机碳有重要影响作用的农业管理活动。研究结果表明:物候参数的加入能够降低预测模型的误差和提升模型解释方差的能力;对漳州市水田土壤有机碳影响作用最大的物候参数依次为早稻季的NDVI增长速率(h1)、早稻生长季节开始的时间(a1)与早稻季NDVI下降速率(i1);三个最重要的物候参数与土壤有机碳含量分别呈正相关、负相关和负相关,因此,采取能够促使早稻苗早生快发、加快早稻分蘖速率和减缓早稻衰老速率的水肥管理措施可增加耕地土壤有机碳含量。基于物候参数构建预测模型能有效提高农田土壤有机碳制图精度,基于物候参数的农田土壤有机碳制图研究可为农田管理提供决策支持,此次研究结果可为相关研究提供理论依据。

    Abstract:

    【Objective】 High~precision soil organic carbon mapping is the basis for studying the spatiotemporal pattern of cultivated soil organic carbon and its influencing mechanism. Results of the relevant research can provide decision support for the designation of farmland management regarding "carbon sequestration and emission reduction". Agricultural management activities are an important influencing factor of soil organic carbon changes in farmland, but soil organic carbon mapping based on agricultural management activities is relatively rare. The phenological parameters extracted from remote sensing images are a direct reflection of agricultural management activities and have great application potential in studying the impact of agricultural management activities on farmland soil organic carbon. 【Method】 This study selected the paddy fields in Zhangzhou City, Fujian Province as the research object. We used the random forest algorithm, based on five different variable combinations (Group A:only natural environment variables; Group B:natural environment variables + early rice phenological parameters:Group C:natural environment variables + late rice phenological parameters; Group D:natural environment variables + early rice phenological parameters + late rice phenological parameters; Group E:early rice phenological parameters + late rice phenological parameters), to build soil organic carbon content prediction models. By comparing the prediction accuracy of the five groups of models, the spatial distribution characteristics of predicted values, the importance of related influencing factors, and the influence of phenological parameters on the accuracy of soil organic carbon mapping were analyzed. Also, the main influencing factors of soil organic carbon mapping in paddy fields in Zhangzhou City were excavated. Agricultural management activities that have an important impact on soil organic carbon in paddy fields in Zhangzhou City were also identified. 【Result】 The results showed that the differences in the spatial distribution of soil organic carbon in paddy fields in Zhangzhou resulted from the combined effect of natural environmental factors and agricultural management measures. Phenological parameters can effectively improve the mapping accuracy of soil organic carbon in paddy fields in Zhangzhou City. Compared with the prediction model based only on natural factors, the addition of phenological parameters can reduce the error of the prediction model and improve the ability of the model to explain variance. The phenological parameters that had the greatest impact on soil organic carbon in paddy fields in Zhangzhou City were the rate of increase at the beginning of the early rice growing season (h1), the time for the start of the early rice growing season (a1), and the rate of decrease at the end of the early rice growing season (i1). These three most important phenological parameters were positively, negatively, and negatively correlated with soil organic carbon content, respectively. 【Conclusion】 The adoption of water and fertilizer management measures that can promote early growth and rapid germination of the early rice, accelerate the tillering rate of the early rice, and slow down the senescence rate of the early rice will increase the soil organic carbon content in the cultivated land. Building a prediction model based on phenological parameters can effectively improve the accuracy of farmland soil organic carbon mapping. The research on farmland soil organic carbon mapping based on phenological parameters can provide decision support for farmland management. The results of this study can provide a theoretical basis for related research.

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吴启航,姚园,李一凡,曹文琦,蔡欣瑶,毋亭,张黎明,邢世和.福建省漳州市水稻物候特征对稻田土壤有机碳制图的影响[J].土壤学报,2024,61(2):385-397. DOI:10.11766/trxb202205150253 WU Qihang, YAO Yuan, LI Yifan, CAO Wenqi, Cai Xinyao, WU Ting, ZHANG Liming, XING Shihe. Effects of Rice Phenological Characteristics on Soil Organic Carbon Mapping in Paddy Fields in Zhangzhou City, Fujian Province[J]. Acta Pedologica Sinica,2024,61(2):385-397.

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  • 收稿日期:2022-05-15
  • 最后修改日期:2022-12-20
  • 录用日期:2023-04-10
  • 在线发布日期: 2023-04-11
  • 出版日期: 2024-03-15