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Thermal conductivity of unfrozen and partially frozen managed peat soils

机译:联接和部分冷冻管理泥炭土壤的导热系数

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Detailed, accurate information on soil temperature is crucial for understanding processes leading to solute leaching and greenhouse gas (GHG) emissions from managed peat soils, but few studies have attempted to study these processes in detail. Drained peat soils have different characteristics from pristine peat. Cultivated peat soils, in particular, have high mineral matter content in the plough layer, due to mineralisation of peat and, sometimes, addition of mineral material. This study examined the effect of mineral matter content on thermal conductivity (lambda) in partially frozen and unfrozen peat samples. Effect of change in temperature from -3 degrees C to - 10 degrees C on thermal conductivity was also estimated. Three existing models for estimating the thermal conductivity of organic soils were assessed for their suitability for cultivated drained peat soils. The thermal conductivity of peat samples with three different levels of mineral matter content was determined, using the single probe method, in the saturated state and when subjected to at least two different matric potentials at five different temperatures ( + 10 degrees C, + 1 degrees C, - 3 degrees C, - 5 degrees C and -10 degrees C). The results showed that X values differed between peat soils depending on mineral matter content, ice content and moisture content. The samples with the highest mineral matter content and bulk density had higher thermal conductivity at positive temperatures and to a lesser extent, at freezing temperatures, when volumetric water content and volume of water-free pores was similar. Most soil samples, especially those with no added mineral soil, were not fully frozen at - 3 degrees C and - 5 degrees C, but this had minor effect on thermal conductivity compared with values measured at -10 degrees C. The Brovka-Rovdan model proved reasonably good at predicting frozen thermal conductivity in sand-enriched peat soils, while the de Vries model proved best at estimating thermal conductivity for unfrozen peat samples. We provide a first estimate of the thermal conductivity of (partially) frozen cultivated peat measured using undisturbed samples. These results can be used to parameterise numerical heat transport models for simulating soil processes and GHG emissions.
机译:详细的有关土壤温度的准确信息对于了解管理泥炭土壤的溶质浸出和温室气体(GHG)排放的过程至关重要,但很少有研究试图详细研究这些过程。排水泥炭土壤具有来自原始泥炭的不同特征。植物泥炭土壤,特别是在犁层中具有高矿物质含量,由于泥炭的矿化,有时,添加矿物质材料。该研究检测了矿物质含量对部分冷冻和未分的泥炭样品的热导率(Lambda)的影响。还估计了温度变化在-3℃至10摄氏度下的热导率的影响。评估了用于估计有机土的导热率的现有模型,适用于栽培排水泥炭土壤的适用性。使用单一探针方法在饱和状态下和在五个不同温度(+ 10℃,+ 1度的+ 10度C, - 3摄氏度, - 5摄氏度和-10度C)。结果表明,X值差异不同,取决于矿物质物质含量,冰含量和水分含量。具有最高矿物质含量和堆积密度的样品在阳性温度下具有较高的导热性,并且在较轻的程度上,在冷冻温度下,当体积水含量和无水孔的体积相似时。大多数土壤样品,特别是那些没有添加矿物土壤的样品,在3摄氏度和-5摄氏度中没有完全冷冻,但对于在-10摄氏度下测量的值相比,这对导热率有微小的影响经证明,合理良好地预测了富含泥煤土壤中的冷冻热导率,而DE VRIES模型估算了解冻泥炭样品的导热系数。我们提供使用未受干扰的样品测量的(部分)冷冻培养泥炭的导热率的第一估计。这些结果可用于参数化数字热传输模型,用于模拟土壤过程和温室气体排放。

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