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Pedotransfer functions for Irish soils – estimation of bulk density (ρb) per horizon type

机译:爱尔兰土壤的pedoransfer函数 - 估计每个地平线类型的堆积密度(ρb)

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摘要

Soil bulk density is a key property in defining soil characteristics. It describes the packing structure of the soil and is also essential for the measurement of soil carbon stock and nutrient assessment. In many older surveys this property was neglected and in many modern surveys this property is omitted due to cost both in laboratory and labour and in cases where the core method cannot be applied. To overcome these oversights pedotransfer functions are applied using other known soil properties to estimate bulk density. Pedotransfer functions have been derived from large international data sets across many studies, with their own inherent biases, many ignoring horizonation and depth variances. Initially pedotransfer functions from the literature were used to predict different horizon type bulk densities using local known bulk density data sets. Then the best performing of the pedotransfer functions were selected to recalibrate and then were validated again using the known data. The predicted co-efficient of determination was 0.5 or greater in 12 of the 17 horizon types studied. These new equations allowed gap filling where bulk density data were missing in part or whole soil profiles. This then allowed the development of an indicative soil bulk density map for Ireland at 0–30 and 30–50 cm horizon depths. In general the horizons with the largest known data sets had the best predictions, using the recalibrated and validated pedotransfer functions.
机译:土壤容重是定义土壤特性的关键属性。它描述了土壤的堆积结构,对于测量土壤碳储量和评估养分含量也至关重要。在许多较早的调查中,此属性被忽略,并且在许多现代调查中,由于实验室和人工的成本以及在无法应用核心方法的情况下,该属性被省略。为了克服这些疏忽,使用其他已知的土壤特性来应用pedotransfer函数来估计堆积密度。 Pedotransfer函数是从许多研究的大型国际数据集中得出的,它们具有固有的偏差,许多人忽略了地层和深度方差。最初,使用本地已知的堆密度数据集,将文献中的pedotransfer函数用于预测不同的层位型堆密度。然后,选择性能最佳的pedotransfer函数进行重新校准,然后使用已知数据再次进行验证。在研究的17种地平线类型中,有12种的预测确定系数为0.5或更高。这些新的方程式允许在部分或全部土壤剖面中缺少堆积密度数据的地方填充空隙。这样就可以在爱尔兰的0–30和30–50?cm地平线深度处建立指示性土壤容重图。通常,使用重新校准和验证的pedotransfer函数,具有最大已知数据集的地层具有最佳预测。

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