Soil moisture dynamics within soil profiles and associated environmental controls

被引:104
作者
Huang, X. [1 ]
Shi, Z. H. [1 ,2 ]
Zhu, H. D. [1 ]
Zhang, H. Y. [2 ]
Ai, L. [2 ]
Yin, W. [3 ]
机构
[1] Huazhong Agr Univ, Coll Resources & Environm, Wuhan 430070, Peoples R China
[2] Chinese Acad Sci, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shanxi, Peoples R China
[3] Yangtze River Water Resources Protect Sci Inst, Wuhan 430051, Peoples R China
基金
中国国家自然科学基金;
关键词
Soil moisture; Environmental factors; Soil profiles; Partial least squares regression; LEAST-SQUARES REGRESSION; SEMIARID LOESS PLATEAU; WATER STORAGE; TEMPORAL STABILITY; LAND-USE; SURFACE MOISTURE; EOF ANALYSIS; CATCHMENT; TIME; VARIABILITY;
D O I
10.1016/j.catena.2015.01.014
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Knowledge of soil moisture dynamics within soil profiles can improve hydrologic process modeling. The heterogeneity of environmental factors (e.g., topographic attributes, soil properties, land use types and antecedent precipitation) influences soil moisture dynamics. In this study, we measured the soil moisture content at 10-cm depth intervals between the soil surface and the soil-bedrock boundary at 39 sites within a small catchment in 2008 and 2009; we primarily analyzed the environmental controls on soil moisture dynamics over the entire soil profile (0-10, 10-20, 20-30, 30-40, 40-50, and >50 cm). Soil properties, terrain attributes, land use types and precipitation were evaluated as the potential controls. Given the high co-dependence of environmental factors, partial least squares regression (PLSR) was used to understand the links between soil moisture dynamics and the 14 selected environmental indices. The results show that PLSR considerably reduced the dimensionality of the soil moisture data. The first two components explained 73.5%, 69.9%, 65.7%, 60.1%, 51.5% and 47.6% of the soil moisture variability at the measurement depths of 0-10 cm, 10-20 cm, 20-30 cm, 30-40 cm, 40-50 cm and >50 cm, respectively. Antecedent precipitation dominates the first and second positive components of the PLSR models at all of the measurement depths. The first-order controls were determined by calculating the Variable Influence on Projection (VIP). The VIP values revealed that the soil moisture in the top layer (0-10 cm) is controlled by antecedent precipitation. In the intermediate layer (10-30 cm), the first-order controls of soil moisture are antecedent precipitation, soil thickness, topographic wetness index, and soil texture; while in the deeper layer (>30 cm), antecedent precipitation, soil thickness, topographic wetness index, relative elevation and slope gradient control soil moisture dynamics. The results indicate that soil moisture is closely associated with environmental factors in measurement catchments at various soil layers and provide a deeper understanding of hydrological processes. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:189 / 196
页数:8
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