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Improvement and Comparison of the Accumulated Temperature Model of Northeast Spring Maize
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摘要: 积温是农业气象科研和业务工作中最常使用的指标之一，但由于受其他环境条件的影响，农作物生育期间的积温在年际间和地区间均表现出不稳定性。因此，如何对已有积温模型进行修正，使农作物生育期间积温计算值趋于稳定并反映实际情况，对农业生产和气象服务均有重要意义。该文以东北春玉米四单19为例，应用沈国权提出的非线性积温模型（简称NLM）进行拟合，分析了参数选择对积温稳定性的影响，提出使用平均温度的二次函数对线性积温模型（简称LM）进行修正（修正后模型称TRM）并进行效果分析，与NLM进行比较。结果表明：NLM拟合时参数P越小，模拟有效积温越稳定；NLM积温在年际间、地区间均存在差异，造成积温不稳定的主要因子是温度强度，与其他因子相关性较差；有效积温与生育期平均温度呈二次曲线关系，对LM的温度二次方修正结果与NLM结果比较发现，二次方修正方法具有可行性。Abstract: Spring maize in Northeast China plays a more and more important role in the national maize production. The gradually increase in acreage, the per unit area yield and total yield of spring maize have markedly improved since 1980s. Accumulated temperature is one of indexes which are commonly used in agricultural meteorological research and operation service. It's also used in crop model and regional thermal resource analysis which can reflect differences in demand of heat resources between different crops and varieties. And it can also be used to evaluate the suitability of heat conditions in a certain area for crop growth and development to avoid blindness of crops introduction. But in fact, the stability of accumulated temperature is relative, and it fluctuates with differences of crop varieties, locations, years and growth periods. It results in the limited application of the accumulated temperature index. Besides environmental conditions, the instability of accumulated temperature is also affected by different calculation methods. In general, accumulated temperature models are divided into two categories, including linear model and nonlinear model. Therefore, how to choose and revise the existing model for stabilizing the calculation value of accumulated temperature and making it fit well with the actual situation is of great significance for agricultural production and meteorological service.Based on observations of spring maize and meteorological data in Northeast China, the spring maize Sidan19 is taken as an example. The nonlinear accumulated temperature model proposed by Shen Guoquan with good stability is adopted to fit, and the influence of parameter selection on the stability of accumulated temperature is analyzed. The quadratic function of mean temperature to the liner model is revised and analyzed, and the nonlinear model is compared. Results show that the stability of accumulated temperature is related to the parameter P, more stable with smaller P. However, accumulated temperature calculated by the nonlinear model shows inter-annual and inter-regional differences. The main cause for the instability is different temperature strength and its less correlated with other meteorological factors. For each growth period, fitted curves between accumulated temperature and mean temperature are quadratic. The fitting effect of the accumulated temperature calculated by the revised linear model is better than that of Shen Guoquan nonlinear model. Moreover, the stability doesn't appear to be much different between two methods. Thus, the revision of linear model considering the mean temperature for spring maize in Northeast China is feasible, which can help revising agro-meteorological indexes and improving agriculture service capacity.
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Key words:
- spring maize;
- accumulated temperature model;
- stability;
- revision model
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图 1 不同站点NLM积温与生育期平均温度的相关性
Fig. 1 Correlations between accumulated temperature by nonlinear model and mean temperature at different stations
图 2 NLM与LM积温对比
Fig. 2 Comparison between accumulated temperature obtained by nonlinear model and linear model
图 3 出苗-成熟期NLM积温与气象因子关系
Fig. 3 Relationship between accumulated temperature by nonlinear model and meteorological factors during emergence to maturity
图 4 NLM积温与生育期平均温度的二次相关分析(混合站点)
Fig. 4 Quadratic correlation between accumulated temperature by nonlinear model and mean temperature(mixed stations)
表 1 东北春玉米不同生育期的三基点温度(单位：℃)
Table 1 Temperatures of three fundamental points of spring maize in growing seasons(unit:℃)
生育期 最适温度 下限温度 上限温度 出苗-拔节期 24.0 12.0 35.0 拔节-抽雄期 28.0 16.0 35.0 抽雄-成熟期 24.0 15.0 35.0 出苗-成熟期 25.0 12.0 35.0 
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表 2 NLM拟合参数及模型积温变异情况(泰来站)
Table 2 Fitting parameters of nonlinear model and variation coefficient(Tailai Station)
生育期 P Q K 线性转换决定系数 积温变异系数/% 出苗-拔节期 0.5 1.0123 e12.6868 0.70 9.38 0.6 1.1621 e13.3011 0.73 9.40 0.7 1.3120 e13.9153 0.75 9.42 0.8 1.4619 e14.5296 0.77 9.44 0.9 1.6117 e15.1439 0.79 9.46 1.0 1.7616 e15.7581 0.81 9.48 拔节-抽雄期 0.5 0.8693 e10.2277 0.87 20.97 0.6 1.0041 e10.7549 0.88 21.21 0.7 1.1390 e11.2821 0.89 21.46 0.8 1.2738 e11.8093 0.90 21.73 0.9 1.4086 e12.3365 0.90 22.01 1.0 1.5434 e12.8637 0.91 22.30 抽雄-成熟期 0.5 4.2089 e20.7425 0.91 14.47 0.6 4.5281 e21.7664 0.92 14.54 0.7 4.8472 e22.7903 0.92 14.60 0.8 5.1663 e23.8143 0.93 14.67 0.9 5.4855 e24.8382 0.93 14.74 1.0 5.8046 e25.8621 0.94 14.81 出苗-成熟期 0.5 1.1779 e13.9831 0.97 6.62 0.6 1.3366 e14.6211 0.98 6.63 0.7 1.4953 e15.2591 0.98 6.63 0.8 1.6539 e15.8971 0.98 6.64 0.9 1.8126 e16.5351 0.98 6.64 1.0 1.9713 e17.1731 0.98 6.65 注：方程均达到0.001显著性水平。
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表 3 分站及混合站点NLM
Table 3 Nonlinear model fitted for each station and mixed ones
生育期 站点 拟合方程 出苗-拔节期 泰来 A(T)=e12.6868(T-B)-0.5(M-T)-1-1.0123 哈尔滨 A(T)=e14.6129(T-B)-0.5M-T-1-1.8809* 青冈 A(T)=e14.4623(T-B)-0.5M-T-1-1.7370** 混合站点 A(T)=e16.8326(T-B)-0.5M-T-1-2.6384 拔节-抽雄期 泰来 A(T)=e10.2277(T-B)-0.5M-T-1-0.8693 哈尔滨 A(T)=e11.5074(T-B)-0.5M-T-1-1.2226 青冈 A(T)=e16.3605(T-B)-0.5M-T-1-3.2350 混合站点 A(T)=e11.0222(T-B)-0.5M-T-1-1.0965 抽雄-成熟期 泰来 A(T)=e20.7425(T-B)-0.5M-T-1-4.2089 哈尔滨 A(T)=e14.1598(T-B)-0.5M-T-1-1.7701 青冈 A(T)=e26.7917(T-B)-0.5M-T-1-6.3742 混合站点 A(T)=e17.7128(T-B)-0.5M-T-1-3.1065 出苗-成熟期 泰来 A(T)=e13.9831(T-B)-0.5M-T-1-1.1779 哈尔滨 A(T)=e12.3094(T-B)-0.5M-T-1-0.5786 青冈 A(T)=e12.7876(T-B)-0.5M-T-1-0.7696*** 混合站点 A(T)=e13.7376(T-B)-0.5M-T-1-1.1076 注：*表示达到0.004显著性水平，**表示达到0.01显著性水平，***表示达到0.029显著性水平，其余均达到0.001显著性水平。
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表 4 不同站点NLM积温(单位：℃·d)
Table 4 Accumulated temperature of NLM at different stations(unit:℃·d)
生育期 泰来 哈尔滨 青冈 出苗-拔节期 540.2±53.1 314.2±30.5 400.9±37.6 拔节-抽雄期 116.1±25.50 169.6±34.8 138.1±42.6 抽雄-成熟期 355.9±54.0 382.3±39.9 255.5±41.8 出苗-成熟期 1253.0±87.0 1147.7±42.54 1036.1±26.33 注：表中数值为积温平均值±标准差，各生育期NLM积温地区间差异均达到0.01显著性水平。
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表 5 NLM与LM积温变异系数比较(单位：%)
Table 5 Comparison between variation coefficient of accumulated temperature obtained by nonlinear and linear models(unit:%)
站点 出苗-拔节期 拔节-抽雄期 抽雄-成熟期 出苗-成熟期 NLM LM NLM LM NLM LM NLM LM 泰来 9.38 13.03 20.97 21.82 14.47 14.64 6.62 6.79 哈尔滨 9.35 17.51 19.75 24.29 9.91 15.61 3.57 6.26 青冈 8.76 12.47 28.88 29.19 15.30 18.58 2.38 5.12 混合站点 21.91 27.70 20.82 30.37 20.67 21.76 7.14 9.42
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表 6 NLM与TRM积温决定系数与归一化均方根误差
Table 6 R2 and normalized root mean square error of accumulated temperature obtained by nonlinear model and temperature revision model
站点 生育期 决定系数 归一化均方根误差 NLM TRM NLM TRM 泰来 出苗-拔节期 0.4149* 0.5713** 10.0224 8.5341 拔节-抽雄期 0.7513** 0.7746** 11.0674 10.3617 抽雄-成熟期 0.8014** 0.8553** 6.6636 5.5704 出苗-成熟期 0.9366** 0.9406** 1.7100 1.6534 哈尔滨 出苗-拔节期 0.2549 0.3139* 15.1518 14.5037 拔节-抽雄期 0.5065** 0.5265** 17.2740 16.7126 抽雄-成熟期 0.4084* 0.4139* 12.0380 11.9491 出苗-成熟期 0.3735* 0.4050* 4.9659 4.8311 青冈 出苗-拔节期 0.4540 0.4963 9.2304 8.8518 拔节-抽雄期 0.9574** 0.9621** 6.0310 5.6866 抽雄-成熟期 0.7024** 0.7065** 10.1577 10.0677 出苗-成熟期 0.1740 0.7359** 4.6613 2.6322 混合站点 出苗-拔节期 0.5096** 0.5427** 19.5490 18.7301 拔节-抽雄期 0.2628** 0.3897** 26.6452 23.7275 抽雄-成熟期 0.6340** 0.7285** 13.5658 11.3389 出苗-成熟期 0.5786** 0.5782** 6.1211 6.1213 注：*表示达到0.05的显著性水平；**表示达到0.01的显著性水平。
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表 7 NLM与TRM积温变异系数比较(单位：%)
Table 7 Comparison between variation coefficient of accumulated temperature obtained by nonlinear model and temperature revision model(unit: %)
站点 出苗-拔节期 拔节-抽雄期 抽雄-成熟期 出苗-成熟期 NLM TRM NLM TRM NLM TRM NLM TRM 泰来 9.38 9.85 20.97 19.20 14.47 13.54 6.62 6.58 哈尔滨 9.35 9.81 19.75 17.63 9.91 10.04 3.57 3.99 青冈 8.76 8.79 28.88 28.62 15.30 15.62 2.38 4.39 混合站点 21.91 20.40 20.82 18.96 20.67 18.57 7.14 7.17
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