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首页> 外文期刊>Journal of Hydrology >Characterizing surface soil water with field portable diffuse reflectance spectroscopy
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Characterizing surface soil water with field portable diffuse reflectance spectroscopy

机译:野外便携式漫反射光谱法表征地表土壤水

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摘要

Surface soil moisture plays a key role in regulating a variety of processes associated with water and energy, especially evaporation. Most prevailing methods measure soil water content only for soil blocks or layers of a certain depth, rather than directly on the soil surface. Diffuse reflectance spectroscopy (DRS) provides a way to approximate surface soil water content by utilizing surface reflectance to quantify soil water. The direct measurement of surface water content could potentially improve the understanding and modeling accuracy of the processes associated with surface water dynamics. The present study investigated the reflectance variations in one artificially constructed sample set, one set of natural soil cores, and one set of natural surface soils, with various moisture levels. Results showed that the reflectance decreased non-linearly with an increase in soil moisture at single wavelengths for all three sample sets. The models derived from partial least square (PLS) regression with segmented cross-validation using natural logarithm transformed wave bands or full spectra provided accurate and stable prediction for all moisture ranges studied. Although it is still problematic to construct a single, universal model for surface soil moisture, segmented models based on soil property classes (i.e. texture, color) are able to accurately predict surface soil water content from measured reflectance. Specific calibrations for soils with similar soil texture or color are expected to provide promising prediction of surface soil moisture.
机译:表层土壤水分在调节与水和能量有关的各种过程(尤其是蒸发)中起着关键作用。大多数流行的方法仅在一定深度的土壤块或土壤层中测量土壤含水量,而不是直接在土壤表面上测量。漫反射光谱法(DRS)提供了一种通过利用表面反射率定量土壤水来估算表面土壤含水量的方法。直接测量地表水含量可能会改善与地表水动力学相关的过程的理解和建模精度。本研究调查了一组人工构建的样本集,一组天然土壤核和一组天然表层土壤在不同湿度下的反射率变化。结果表明,所有三个样品组的反射率都随着土壤水分在单波长下的增加而非线性下降。通过使用自然对数转换的波段或全光谱进行分段交叉验证的偏最小二乘(PLS)回归模型得出的模型,为研究的所有湿度范围提供了准确而稳定的预测。尽管构建用于表层土壤水分的单一通用模型仍然存在问题,但是基于土壤属性类(即质地,颜色)的分段模型能够根据测得的反射率准确预测表层土壤水分。预期对具有相似土壤质地或颜色的土壤进行专门的标定可以为土壤表层水分提供有希望的预测。

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