Saturated Hydraulic Conductivity in Northern Peats Inferred From Other Measurements
Saturated Hydraulic Conductivity in Northern Peats Inferred From Other Measurements
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DOI：
10.1029/2022wr033181
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发表时间：
2022-11-01
影响因子：
5.4
通讯作者：
Wilkinson, S. L.
中科院分区：
文献类型：
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作者：
Morris, P. J.;Davies, M. L.;Wilkinson, S. L.
在北方泥炭地，接近饱和的地表条件促进了宝贵的生态系统服务，如碳储存和饮用水供应。泥炭饱和导水率（K-sat）通过调节排水和蒸散，在维持湿润地表条件方面起着重要作用。泥炭K-sat可以在三维空间中表现出强烈的空间变异性，并且可以响应干扰而迅速变化。泥炭K-sat和其他水力特性的预测方程的发展，类似于矿物土壤pedotransfer函数，仍然是一个正在进行的研究课题。我们报告了对2，507个北方泥炭样本的荟萃分析，从中我们开发了线性模型，该模型可以从其他变量（包括深度，干容重，von Post评分（腐殖化程度））和分类信息（如表面微形态类型和泥炭地营养类型）预测泥炭K-sat（例如，沼泽和沼泽）。泥炭K-饱和度随深度、干容重和腐殖化作用的增加而强烈降低，并沿沿着沼泽泥炭到沼泽泥炭的营养梯度增加。干容重和腐殖化是特别重要的预测因子，大大提高了模型的技巧;我们最好的模型，其中包括这些变量，具有交叉验证的r（2）为0.75，偏差很小。第二个模型包括腐殖化作用，但省略了干容重，旨在快速现场估计K-sat，也表现良好（交叉验证r（2）= 0.64）。另外两个模型省略了几个预测因子，表现不太好（交叉验证的r（2）类似于0.5），并表现出更大的偏差，但允许从不太全面的数据中估计K-sat。我们的模型允许改进估计泥炭K-sat从更简单，更便宜的测量。
In northern peatlands, near-saturated surface conditions promote valuable ecosystem services such as carbon storage and drinking water provision. Peat saturated hydraulic conductivity (K-sat) plays an important role in maintaining wet surface conditions by moderating drainage and evapotranspiration. Peat K-sat can exhibit intense spatial variability in three dimensions and can change rapidly in response to disturbance. The development of skillful predictive equations for peat K-sat and other hydraulic properties, akin to mineral soil pedotransfer functions, remains a subject of ongoing research. We report a meta-analysis of 2,507 northern peat samples, from which we developed linear models that predict peat K-sat from other variables, including depth, dry bulk density, von Post score (degree of humification), and categorical information such as surface microform type and peatland trophic type (e.g., bog and fen). Peat K-sat decreases strongly with increasing depth, dry bulk density, and humification; and increases along the trophic gradient from bog to fen peat. Dry bulk density and humification are particularly important predictors and increase model skill greatly; our best model, which includes these variables, has a cross-validated r(2) of 0.75 and little bias. A second model that includes humification but omits dry bulk density, intended for rapid field estimations of K-sat, also performs well (cross-validated r(2) = 0.64). Two additional models that omit several predictors perform less well (cross-validated r(2) similar to 0.5), and exhibit greater bias, but allow K-sat to be estimated from less comprehensive data. Our models allow improved estimation of peat K-sat from simpler, cheaper measurements.