Field studies on the influence of rainfall intensity, vegetation cover and slope length on soil moisture infiltration on typical watersheds of the Loess Plateau, China

He, Zimiao; Jia, Guodong; Liu, Ziqiang; Zhang, Zhenyao; Yu, Xinxiao; Xiao, Peng

doi:10.1002/hyp.13892

Cited by 52 publications

(18 citation statements)

References 50 publications

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“…The storage changes and soil moisture difference indices at depths of 10 and cm in the upslope area for Cluster 4 were greater than those for Cluster 3 due to higher AMO, DUR, and INT. However, the storage change at a depth of 60 cm in the upslope for Cluster 4 was smaller than that of Cluster 3, which can be explained by the lower infiltration under drier ASM conditions (Zhu et al, 2014;Mei et al, 2018;He et al, 2020).…”

Section: Characterization Of Classified Hydrologic Eventmentioning

confidence: 96%

Characterization of Hillslope Hydrologic Events through a Self-Organizing Map

Lee

Kim

2021

Preprint

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Abstract. Hydrologic events can be characterized as particular combinations of hydrological processes on a hillslope scale. To configure hydrological mechanisms, we analyzed a dataset using an unsupervised machine learning algorithm to cluster the hydrologic events based on the dissimilarity distances between the weighting components of a self-organizing map (SOM). The time series of soil moisture was measured at 30 points (in 10 locations with 3 varying depths) for 356 rainfall events on a steep, forested hillslope between 2007 and 2016. Soil moisture features for hydrologic events can be effectively represented by the antecedent soil moisture, maximum variation, and standard deviation of peak-to-peak time between rainfall and soil moisture response. Five clusters were delineated for hydrologically meaningful event classification in the SOM representation. The two-dimensional spatial weighting patterns in the SOM provided greater insight on relationships between rainfall characteristics, antecedent wetness, and soil moisture response at different locations and depths. The distinction of the classified events can be explained by several rainfall features and antecedent soil moisture conditions that resulted in different patterns made by combinations of hillslope hydrological processes, vertical flow, and lateral flow along either surface or subsurface boundaries for the upslope and downslope areas.

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Section: Characterization Of Classified Hydrologic Eventmentioning

confidence: 96%

Characterization of Hillslope Hydrologic Events through a Self-Organizing Map

Lee

Kim

2021

Preprint

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“…From the beginning of rainstorm to the water migration reaching the basic stability, there is water seepage at the bottom drain of the model test device in each loess column with different dry densities, and the water migration reaches the maximum depth of the loess column (Z max > 70 cm). The change of water content in shallow loess is sensitive under different rainfall conditions [28]. In the range of 0-50cm depth of the loess column, with the continuous rainfall time, the volumetric water content of loess decreases gradually, while the resistivity shows a trend of gradual increase, which reveals that the water component has been infiltrating deeper into the loess column under the action of rainstorm.…”

Section: Water Migration Characteristics In Compacted Loess Under Rai...mentioning

confidence: 99%

Experimental study of water migration characteristics in compacted loess subjected to rainfall infiltration

Zhang

Han

et al. 2022

PLoS ONE

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In order to study the effect of the rainfall infiltration on water migration in compacted loess, a model device was developed for testing water migration in the soil under rainfall conditions. In this study, the volumetric water content and resistivity of soil were introduced into the model test device. This model test device was applied to the study of water migration characteristics in compacted loess under different rainfall conditions. The results show that the resistivity decreases with the increase of the volumetric water content at the same depth of the loess column. In this way, the characteristics of the water migration can also be reflected from the change of the resistivity. There is an intimate relationship between the resistivity and volumetric water content, dry density. The volumetric water content and dry density are normalized by saturation of loess, arriving the equation of saturation against the resistivity. The characteristics of rainfall infiltration in compacted loess show a particular pattern, which demonstrates that, with the increase of dry density of the loess column, the rainfall infiltration line present “Y”, “D” and “Λ” shape distribution respectively, under light rain, heavy rain and rainstorm.

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“…The storage changes and soil moisture difference indices at depths of 10 and 30 cm in the upslope area for Cluster 4 were greater than those for Cluster 3 due to higher AMO, DUR, and INT. However, the storage change at a depth of 60 cm in the upslope for Cluster 4 was smaller than that of Cluster 3, which could be explained by the lower infiltration under comparatively dry ASM conditions (Zhu et al, 2014;Mei et al, 2018;He et al, 2020). The machine learning algorithm (SOM) can be considered a useful analysis platform, not only for elucidating soil moisture response patterns in conjunction with rainfall and ASM (Fig.…”

Section: Characterization Of the Classified Hydrologic Eventsmentioning

confidence: 99%

Characterization of soil moisture response patterns and hillslope hydrological processes through a self-organizing map

Lee

Kim

2021

Hydrol. Earth Syst. Sci.

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Abstract. Hydrologic events can be characterized as particular combinations of hydrological processes on a hillslope scale. To configure hydrological mechanisms, we analyzed a dataset using an unsupervised machine learning algorithm to cluster the hydrologic events based on the dissimilarity distances between the weighting components of a self-organizing map (SOM). The time series of soil moisture was measured at 30 points (at 10 locations with three different depths) for 356 rainfall events on a steep, forested hillslope between 2007 and 2016. The soil moisture features for hydrologic events can be effectively represented by the antecedent soil moisture, soil moisture difference index, and standard deviation of the peak-to-peak time between rainfall and soil moisture response. Five clusters were delineated for hydrologically meaningful event classifications in the SOM representation. The two-dimensional spatial weighting patterns in the SOM provided more insights into the relationships between rainfall characteristics, antecedent wetness, and soil moisture response at different locations and depths. The distinction of the classified events could be explained by several rainfall features and antecedent soil moisture conditions that resulted in different patterns attributable to combinations of hillslope hydrological processes, vertical flow, and lateral flow along either surface or subsurface boundaries for the upslope and downslope areas.

show abstract

Field studies on the influence of rainfall intensity, vegetation cover and slope length on soil moisture infiltration on typical watersheds of the Loess Plateau, China

Cited by 52 publications

References 50 publications

Characterization of Hillslope Hydrologic Events through a Self-Organizing Map

Characterization of Hillslope Hydrologic Events through a Self-Organizing Map

Experimental study of water migration characteristics in compacted loess subjected to rainfall infiltration

Characterization of soil moisture response patterns and hillslope hydrological processes through a self-organizing map

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