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首页> 外文期刊>Catena: An Interdisciplinary Journal of Soil Science Hydrology-Geomorphology Focusing on Geoecology and Landscape Evolution >Use of a state-space approach to predict soil water storage at the hillslope scale on the Loess Plateau, China
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Use of a state-space approach to predict soil water storage at the hillslope scale on the Loess Plateau, China

机译:利用状态空间方法预测中国黄土高原丘陵坡地的土壤蓄水量

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Soil water storage is a critical variable controlling hydrological and biological processes. The precise estimation of soil water storage in diverse soil layers is fundamental to understanding hydro-biological processes and efficiently managing water resources. The objectives of this study were to evaluate the effects of topography (elevation) and soil properties (clay, silt, sand content, median grain size, and fractal dimension) on soil water storage and then to estimate soil water storage using a state-space approach. The soil water storage values of three soil layers (0-1, 1-2, and 2-3 m) were measured from May to December 2014 at 70 locations along two 187 m long transects on a hillslope of the Loess Plateau, China. Samples from various depths were also collected to determine soil properties. The best state-space approach explained 98.8% of the total variation in soil water storage, while the best classical linear regression equation only explained 64.2%. The state-space approach using any combination of variables described the spatial pattern of soil water storage much better than equivalent linear regression equations. Elevation and clay content were identified as the most effective combination for soil water storage estimation in the state-space approach, and were used to effectively predict the soil water storage spatial pattern along the second transect The state-space approach is thus a useful tool that is recommended for predicting soil water storage spatial patterns at the hillslope scale using topography and soil properties. (C) 2015 Elsevier B.V. All rights reserved.
机译:土壤水储量是控制水文和生物过程的关键变量。准确估算不同土壤层中的土壤蓄水量是了解水生生物过程和有效管理水资源的基础。这项研究的目的是评估地形(高程)和土壤特性(粘土,淤泥,砂含量,中值粒径和分形维数)对土壤贮水量的影响,然后使用状态空间估算土壤贮水量。方法。 2014年5月至2014年12月,在中国黄土高原山坡的两个187 m长样带的70个位置上,测量了三个土壤层(0-1、1-2和2-3 m)的土壤储水量。还收集了来自各个深度的样品以确定土壤性质。最好的状态空间方法解释了土壤储水总量的98.8%,而最好的经典线性回归方程只解释了64.2%。使用变量的任意组合的状态空间方法比等效线性回归方程更好地描述了土壤蓄水的空间格局。在状态空间方法中,标高和黏土含量被认为是最有效的土壤蓄水量估算组合,可用于有效预测第二个样带的土壤蓄水空间格局。因此,状态空间法是一种有用的工具,建议使用地形和土壤特性预测山坡尺度的土壤蓄水空间格局。 (C)2015 Elsevier B.V.保留所有权利。

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