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Using field topographic descriptors to estimate soil water retention

机译:使用野外地形描述符估算土壤保水量

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摘要

In field-, watershed-, and regional-scale projects, soil water retention is often estimated from soil textural classes shown in soil maps. The textural classes are relatively broad, often only the dominating textural class is shown, cartographers routinely use error-prone field judgments of soil texture, and soil texture is known to vary along slopes and to depend on the land surface shape. We, therefore, hypothesized that including topographic information in water retention estimation would increase accuracy. To test this hypothesis, we extracted data on 216 soil pedons for soils of moderate and large extent from the Natural Resources Conservation Service (NRCS) soil characterization database. Textural classes, genetic horizon numbers, slopes, position on the slope classes, and land surface shape classes were the field descriptors that we used to estimate water retention at -33 and -1500 kPa potentials for each horizon in each pedon. Because our input variables were both categorical and continuous, regression trees were used for subdividing the samples into the smallest number of the most homogeneous groups, which we tentatively called topotextural groups (TTG). The jackknife cross-validation was used to prune the regression trees to prevent overparameterization. Ten or fewer TTGs were defined for both the -33 and the -1500 kPa retention. The TTGs were different for the two matric potential levels. Using topographic variables and soil horizon seemed to be the most accurate way to make up for errors made in field determination of texture. For the A horizon, the topotextural grouping resulted in estimates that were more accurate than those using laboratory textures only. Although most of the topographic variables in this work are categorical, those variables seemed to be useful for improving estimates of water retention.
机译:在田间,流域和区域规模的项目中,土壤保水率通常是根据土壤图上显示的土壤质地类别进行估算的。质地类别相对较宽,通常仅显示主要的质地类别,制图师通常使用容易出错的土壤质地田间判断,并且已知土壤质地会沿坡度变化并取决于土地表面形状。因此,我们假设在保水量估算中包括地形信息将提高准确性。为了验证该假设,我们从自然资源保护局(NRCS)土壤特征数据库中提取了216个土壤中度和大范围土壤soil的数据。纹理类别,遗传视野数,坡度,坡度上的位置以及地表形状类别是我们用来估算每个脚踏子每个视野在-33和-1500 kPa电位下保水量的田间描述子。由于我们的输入变量既是分类变量又是连续变量,因此使用回归树将样本细分为数量最少的最均匀的组,我们将这些临时组称为拓扑结构组(TTG)。折刀交叉验证用于修剪回归树,以防止参数过大。为-33和-1500 kPa保留量定义了十个或更少的TTG。对于两个基质电位水平,TTG不同。使用地形变量和土壤层位似乎是弥补在现场确定质地时所犯错误的最准确方法。对于A层,拓扑构造分组的估计比仅使用实验室纹理的估计更准确。尽管这项工作中的大多数地形变量都是分类的,但是这些变量似乎对改善保水量很有用。

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