生物与土壤

黄土丘陵沟壑区不同深度土壤水分对降雨的响应及其稳定性

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  • 1.中国林业科学研究院荒漠化所,北京 100091
    2.中国科学院西北生态环境资源研究院内陆河流域生态水文重点实验室,甘肃 兰州 730000
    3.北京师范大学地理科学学部,北京 100875
    4.华北油田技术监督检验处计量中心站,河北 任丘 062552
姚雪玲(1981-),女,博士,研究方向为半干旱区草地生态恢复. E-mail:yaoxueling@126.com

收稿日期: 2019-06-11

  修回日期: 2019-11-26

  网络出版日期: 2021-04-14

基金资助

国家重点研发计划项目(2016YFC0500806);国家自然科学基金项目资助(41671187)

Soil moisture response and stability to rainfall in different depths in Loess Plateau

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  • 1. Research Institute of Desertification, Chinese Academy of Forestry, Beijing 100091, China
    2. Key Laboratory of Ecohydrology of Inland River Basin, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, Gansu, China
    3. Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
    4. Technical Supervision Department of Huabei Oilfield, Metrology Center Station, Renqiu 062552, Hebei, China

Received date: 2019-06-11

  Revised date: 2019-11-26

  Online published: 2021-04-14

摘要

通过采用点面结合的方法,分析黄土高原地区降雨影响下不同深度土壤水分的时空变化,从土壤水分复杂的“变异性”中提取相对的“不变性”。结果表明:20 cm以上土壤水分无明显规律,难以表征不同植被类型或空间位置上的土壤水分差异;小于30 mm的降雨基本不会引起40 cm以下土壤水分明显波动;100 cm深处,各采样点的土壤水分能在一个稳定值上保持数月时间,在大于46 mm的强降雨之后出现阶梯式抬升,之后又保持稳定状态;越往土层深处,土壤水分时空稳定性越明显,能较好的表征各植被类型或空间位置上的土壤水分差异。该研究从土壤水分的稳定性角度进行分析,对黄土高原土壤水分的地面采样设计和时空预测具有实际应用价值。

本文引用格式

姚雪玲,杨国靖,王帅,郭秀江 . 黄土丘陵沟壑区不同深度土壤水分对降雨的响应及其稳定性[J]. 干旱区地理, 2021 , 44(2) : 507 -513 . DOI: 10.12118/j.issn.1000–6060.2021.02.21

Abstract

The soil in the Loess Plateau, China is deep and contains abundant soil water resources. However, the terrain is complex, and small land patches are used in this area. Therefore, the temporal and spatial changes of soil moisture are extremely complicated. Previous studies have concentrated more on the soil moisture’s variation characteristics. This study extracts invariance from its variability and explores soil moisture stability characteristics to provide a scientific basis for ground-sampling design and soil moisture prediction in the Loess Plateau. A typical hill in the Loess Plateau was selected as our experimental site, and continuous soil moisture data were obtained using five monitoring instruments on the hillside. The rainfall was monitored simultaneously to investigate the soil moisture changes at varying depths under the influence of varying rainfall events. The soil moisture of five sample strips (including 31 sampling points) was measured using the ground-drilling sampling method, and the sampling was conducted before and after the rainy season to investigate the spatial variation of soil moisture at varying depths. The results show that soil moisture above a 20 cm depth fluctuated frequently under the influence of rainfall-evaporation and had no obvious regularity, making it challenging to characterize soil moisture differences for various land-use types or spatial locations. Therefore, the surface soil moisture should be used cautiously when studying soil moisture change characteristics. At a depth of 40-80 cm, rainfall less than 30 mm will not cause significant soil moisture changes. For different land-use types, the order of soil water content in farmland>grassland>shrubland could remain unchanged for long without heavy rainfall. At a depth of 100 cm, the soil moisture at each sampling point could be maintained at a stable value for several months. Rainfall less than 46 mm will not cause significant soil moisture changes in this layer. After heavy rainfall (>46 mm), the soil moisture will rise stepwise, and maintain long-term stability at the new level. In space, where the soil water content is higher, it remains high after the rainy season, whereas where the soil water content is lower before the rainy season, it remains low after the rainy season. The deeper into the soil, the more stable the spatial stability of soil moisture. Therefore, when comparing soil moisture of different land-use types or spatial locations using the ground-sampling method, deep sampling is critical to obtain stable and reliable results. This study’s results have practical value in simplifying soil moisture ground monitoring and rationally arranging sampling time nodes and have a reference value for soil moisture temporal and spatial prediction in the Loess Plateau.

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