首页> 外文期刊>Acta Agriculturae Scandinavica. Section B, Soil and Plant Science >Predicting daily soil temperature profiles in arable soils in cold temperate regions from air temperature and leaf area index
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Predicting daily soil temperature profiles in arable soils in cold temperate regions from air temperature and leaf area index

机译:根据气温和叶面积指数预测寒冷温带地区耕地的每日土壤温度分布

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Modelling of ecosystem processes often requires soil temperature as a driving variable. Since soil temperature measurements are seldom available for regional applications, they have to be estimated from standard meteorological data. The objective of this paper is to present a general, simple empirical approach for estimating daily depth profiles of soil temperature from air temperature and a surface cover index (LAI; leaf area index) mainly focusing on agricultural soils in cold temperate regions. Air and soil temperature data measured daily or every fifth day at one to six different depths were acquired from all meteorological stations in Sweden where such records are available. The stations cover latitudes from 55.65 degrees to 68.42 degrees N and mean annual air temperatures from +8.6 to -0.6 degrees C. The time series spanned between two and ten years. The soils at the stations cover a wide range of soil textures, including two organic soils. We calibrated the model first for each station and then for all stations together and the general parameterization only slightly decreased the goodness of fit. This general model then was applied to two treatments in a field experiment: bare soil and a winter rape crop. The parameters governing the influence of LAI on heat fluxes were optimized using this experiment. Finally, the model was validated using soil temperature data from two barley treatments differing in LAI taken from another field experiment. In general, the model predicted daily soil temperature profiles well. For all soils and depths at the meteorological stations, 95% of the simulated daily soil temperatures differed by less than 2.8 degrees C from measurements. The corresponding differences were somewhat higher for the validation data set (3.9 degrees C), but bias was still low. The model explained 95% of the variation in the validation data. Since no site-specific adjustments were made in the validation simulations, we conclude that the application of the general model presented here will result in good estimates of soil temperatures under cold temperate conditions. The very limited input requirements (only air temperature and LAI) that are easily obtainable from weather stations and from satellites make this model suitable for spatial applications at catchment or regional scales.
机译:对生态系统过程进行建模通常需要将土壤温度作为驱动变量。由于土壤温度测量很少可用于区域应用,因此必须根据标准气象数据进行估算。本文的目的是提出一种通用,简单的经验方法,用于根据气温和主要针对寒冷温带地区的农业土壤的表面覆盖指数(LAI;叶面积指数)估算土壤温度的每日深度剖面。每天或每五天从一到六个不同深度测量的空气和土壤温度数据是从瑞典所有有此记录的气象站获取的。这些气象站的纬度范围为北纬55.65度至68.42度,年平均气温为+8.6至-0.6摄氏度。时间序列跨度为两年至十年。车站的土壤覆盖了广泛的土壤质地,包括两种有机土壤。我们首先为每个测站然后对所有测站一起对模型进行了校准,而一般参数化仅稍微降低了拟合优度。然后将此通用模型应用于田间试验的两种处理方式:裸土和冬季油菜作物。使用此实验优化了控制LAI对热通量的影响的参数。最后,该模型使用来自另一个大田试验的两种不同大麦处理的大麦处理的土壤温度数据进行了验证。通常,该模型可以很好地预测每日土壤温度分布。对于气象站的所有土壤和深度,模拟的每日土壤温度的95%与测量值相差不到2.8摄氏度。对于验证数据集(3.9摄氏度),相应的差异有些高,但偏差仍然很低。该模型解释了验证数据中95%的变化。由于在验证模拟中未进行针对特定地点的调整,因此我们得出结论,此处介绍的一般模型的应用将对冷温带条件下的土壤温度产生良好的估计。可从气象站和卫星轻松获得非常有限的输入要求(仅气温和LAI),因此该模型适用于集水区或区域尺度的空间应用。

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