摘要
Analyses of the soil moisture evolution trend and the influence of different types of radiation on soil moisture are of great significance to the simulation and prediction of soil moisture.In this paper,soil moisture(2–60 cm) and various radiation data from 2014–2015 at the A’rou superstation were selected.The radiation data include the net radiation(NR),shortwave and longwave radiation(SR and LR).Using adaptive fractal analysis(AFA),the long-range correlation(LRC) of soil moisture and long-range cross correlation(LRCC) between moisture and three types of radiation were analyzed at different timescales and soil depths.The results show that:(1) Persistence of soil moisture and consistency between soil moisture and radiation mutate at 18-d and 6-d timescales,respectively.The timescale variation of soil moisture persistence is mainly related to the influence process of radiation on soil moisture;(2) Both the soil moisture persistence and soil moisture-radiation consistency vary substantially with soil depth.The soil depth variation of soil moisture persistence is related to the influence intensity of radiation;(3) From 2–6 day timescales,LR displays the strongest influence on soil moisture at depths of 2–10 cm through negative feedback of radiation on the soil temperature.The influence intensity decreases with depth from 2–15 cm.Therefore,the soil moisture persistence is weak and increases with depth from 2–15 cm;and(4) At more than 6 day timescales,SR and NR display a stronger influence on the soil moisture persistence at depths of 2–40 cm through positive feedback of radiation on the soil temperature,especially at depths of 2–10 cm.This influence also weakens with depth.The soil moisture persistence at depths of 2–10 cm is the weakest and increases with depth from 2–40 cm.The research results are instructive for determining timescales and soil depths related to soil water in hydrological models.
Analyses of the soil moisture evolution trend and the influence of different types of radiation on soil moisture are of great significance to the simulation and prediction of soil moisture. In this paper, soil moisture(2–60 cm) and various radiation data from 2014–2015 at the A’rou superstation were selected. The radiation data include the net radiation(NR), shortwave and longwave radiation(SR and LR). Using adaptive fractal analysis(AFA), the long-range correlation(LRC) of soil moisture and long-range cross correlation(LRCC) between moisture and three types of radiation were analyzed at different timescales and soil depths. The results show that:(1) Persistence of soil moisture and consistency between soil moisture and radiation mutate at 18-d and 6-d timescales, respectively. The timescale variation of soil moisture persistence is mainly related to the influence process of radiation on soil moisture;(2) Both the soil moisture persistence and soil moisture-radiation consistency vary substantially with soil depth. The soil depth variation of soil moisture persistence is related to the influence intensity of radiation;(3) From 2–6 day timescales, LR displays the strongest influence on soil moisture at depths of 2–10 cm through negative feedback of radiation on the soil temperature. The influence intensity decreases with depth from 2–15 cm. Therefore, the soil moisture persistence is weak and increases with depth from 2–15 cm; and(4) At more than 6 day timescales, SR and NR display a stronger influence on the soil moisture persistence at depths of 2–40 cm through positive feedback of radiation on the soil temperature, especially at depths of 2–10 cm. This influence also weakens with depth. The soil moisture persistence at depths of 2–10 cm is the weakest and increases with depth from 2–40 cm. The research results are instructive for determining timescales and soil depths related to soil water in hydrological models.
作者
ZHANG Ting
SHEN Shi
CHENG Changxiu
张婷;沈石;程昌秀(State Key Laboratory of Earth Surface Processes and Resource Ecology,Beijing Normal University,Beijing 100875,China;Key Laboratory of Environ mental Change and Natural Disaster,Beiji ng Normal Un iversity,Beiji ng 100875,China;Center for Geodata and Analysis,Faculty of Geographical Science,Beijing Normal University,Beijing 100875,China)
基金
National Key R&D Program of China,No.2017YFB0504102
National Natural Science Foundation of China No.41771537
