基于RothC模型的东北旱地和稻田土壤有机碳动态变化模拟研究  

Simulating Soil Organic Carbon Dynamic Changes in Dryland and Paddy Field of Northeast China Using Roth C Model

作　　者：张昊鑫 于晟玥 雷秋良[1] 杜新忠 张继宗[1] 安妙颖 樊秉乾 罗加法 刘宏斌[1] ZHANG HaoXin;YU ShengYue;LEI QiuLiang;DU XinZhong;ZHANG Jizong;AN MiaoYing;FAN BingQian;LUO JiaFa;LIU HongBin(Key Laboratory of Non-Point Source Pollution Control,Ministry of Agriculture and Rural Affairs/Changping Soil Quality National Observation and Research Station/State Key Laboratory of Efficient Utilization of Arid and Semi-Arid Arable Land in Northern China/Institute of Agricultural Resources and Regional Planning,Chinese Academy of Agricultural Sciences,Beijing 100081,China;AgResearch Ruakura Research Centre,10 Bisley Road,Hamilton 3214,New Zealand)

机构地区：[1]农业农村部面源污染控制重点实验室/北京昌平土壤质量国家野外科学观测研究站/北方干旱半干旱耕地高效利用全国重点实验室/中国农业科学院农业资源与农业区划研究所,中国北京100081 [2]AgResearch Ruakura研究中心,新西兰汉密尔顿3214

出　　处：《中国农业科学》2025年第8期1564-1578,共15页Scientia Agricultura Sinica

基　　金：鄂尔多斯市“揭榜挂帅”项目(JBGS-2021-001);国家自然科学基金(U20A20114);黑土地保护与利用科技创新工程专项(XDA28130200);中央级公益性科研院所基本科研业务费专项(1610132024010)。

摘　　要：【目的】探究Roth C在东北地区旱地和稻田土壤有机碳储量动态变化的适用性及不同模型校准方法对于模型模拟性能的影响。【方法】选取了一个典型的旱地和一个典型的稻田长期试验点,旱地试验来自中国科学院海伦农业生态试验站(2004—2015年),稻田试验来自八五〇农场的试验数据(2010—2017年)。每个试验点选取两个试验处理分别为仅施无机肥(NPK)和施无机肥+秸秆还田(NPKS),用于模型模拟验证与性能评价。针对稻田土壤除采用Roth C外,还选取了两个修正版本Roth C_p和Roth C_0.6用于适用性评价,选用3种不同模型校准方法分别为平衡法(M1)、参数优化法(M2)、传递函数法(M3),分析不同模型校准方法对于模型模拟性能的影响。选用归一化均方根误差(n RMSE)、平均差(MD)、一致性指数(d)作为模型评价指标。【结果】海伦站的有机碳输入量表现出明显的波动趋势,NPK、NPKS处理的年均碳投入量分别为1.71、3.52 t·hm^(-2),八五〇农场的有机碳投入较为稳定,NPK、NPKS处理年均有机碳输入量分别为1.89、5.90 t·hm^(-2)。海伦站的模拟验证结果显示,采用不同模型校准方法进行模拟时其n RMSE均小于5%,d在0.60—0.74,说明不同模型校准方法下的模型性能均表现为优秀,Roth C能够准确的模拟出旱地NPK、NPKS处理的SOC储量变化趋势。当采用M2方法时NPK、NPKS处理的n RMSE最小,分别为3.46%、3.09%。八五〇农场的模拟验证结果显示,Roth C和Roth C_p的MD范围为-1.47—-13.41,n RMSE范围为2.90%—26.48%,d值均小于0.1,说明这两个模型大幅度高估了SOC储量的增加,Roth C和Roth C_p不能够模拟出稻田SOC储量的变化趋势。Roth C_0.6在NPK处理下,其MD范围为-0.08—0.44,n RMSE的范围为0.24%—0.85%,d值范围为0.31—0.76;而在NPKS处理下,MD范围为-5.71—-6.22,n RMSE范围为11.21%—12.12%,d值范围为0.12—0.13,说明Roth C_0.6能够模拟出NPK处理下SOC储量的动�【Objective】This study explored the applicability of the Roth C model for simulating soil organic carbon (SOC)dynamics in dryland and paddy fields in Northeast China and evaluated the impact of various calibration methods on simulation performance.【Method】This study selected one typical dryland and one typical paddy field as long-term experimental sites.The dryland experiment was conducted at the Heilongjiang Agricultural Ecology Experimental Station of the Chinese Academy of Sciences (2004-2015),and the paddy field experiment utilized data from the 850 Farm (2010-2017).At each experimental site,two treatments were selected for model simulation validation and performance evaluation:one with fertilization only,without straw return (NPK),and the other with both fertilization and straw returning (NPKS).For the paddy field soil,in addition to the Roth C model,two modified versions,including Roth C_p and Roth C_0.6,were also selected for suitability evaluation.Three different model calibration methods were employed:the equilibrium method,parameter optimization method,and transfer function method,to analyze the impact of these calibration methods on model simulation performance.Normalized root mean square error (n RMSE),mean difference (MD),and the index of agreement (d) were selected as model evaluation metrics.【Result】At the Heilongjiang station,organic carbon input exhibited a significant fluctuating trend,with the average annual carbon input under NPK and NPKS treatments being 1.71 and 3.52 t·hm^(-2),respectively.In contrast,organic carbon input at the 850 Farm was relatively stable,with the average annual carbon input for NPK and NPKS treatments being 1.89 and 5.90 t·hm^(-2),respectively.The simulation validation results from the Heilongjiang station showed that,under different model calibration methods,the n RMSE was consistently below 5%,and the index of agreement (d) ranged from 0.60 to 0.74.This indicated that the model performance was excellent across all calibration methods,and Roth C was able t

关 键 词：RothC模型 土壤有机碳 秸秆还田 模型校准方法 旱地 稻田 东北 

分 类 号：S153.6[农业科学—土壤学]