Occurrence and controls of preferential flow in the upper stream of the Heihe River Basin, Northwest China

Kang, Weiming; Tian, Jie; Lai, Yao; Xu, Shaoyuan; Gao, Chao; Hong, Weijie; Zhou, Yi; Pei, Lina; He, Chansheng

doi:10.1016/j.jhydrol.2022.127528

Cited by 10 publications

(4 citation statements)

References 90 publications

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“…The average sand content in our study was 48% (Figure 2), which exceeds the values reported in their study. Collectively, our results, in conjunction with other studies (Dekker & Ritsema, 1994; Hardie et al, 2011; Kang et al, 2022), suggest that sandier soils coupled with lower moisture can serve as potential conditions for triggering preferential flow.…”

Section: Discussionsupporting

confidence: 86%

“…Our results showed that the preferential flow was more evident under the dry antecedent soil moisture conditions than under the wet antecedent soil moisture conditions (Figure 5). Kang et al (2022) observed that soils with higher sand content exhibit a stronger hydrophobicity as the soil moisture decreases, which is favourable for the occurrence of preferential flow (especially finger flow). The average sand content in our study was 48% (Figure 2), which exceeds the values reported in their study.…”

Section: Discussionmentioning

confidence: 99%

“…In particular, numerous studies have reported a close relationship between initial soil moisture conditions and non‐equilibrium flow (Gao et al, 2018; Graham & Lin, 2011; Hardie et al, 2011; Merdun et al, 2008). Drier soils with high sand content often cause rainwater to penetrate into the soil as preferential flow paths (Dekker & Ritsema, 1994; Kang et al, 2022; King, 1981). Collectively, although these studies have elucidated individual factors influencing soil moisture response to rainfall, the relative influence of these factors on soil moisture dynamics at the hillslope scale remains inadequately described and understood.…”

Section: Introductionmentioning

confidence: 99%

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Responses of soil moisture at different topographic positions to rainfall events along a steep subtropical forested hillslope

Lu,

Liu,

et al. 2024

Hydrological Processes

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Understanding the dynamic response of soil moisture to rainfall is crucial for describing hydrological processes at the hillslope scale. However, because of sparse monitoring coupled with the complexity of water movement and steep topography, the findings of rainfall‐related soil moisture dynamics have not always been consistent, indicating a need for systematic investigations of soil moisture dynamics and infiltration patterns following rainfall inputs at multiple topographic positions along a hillslope. This study aimed to examine the nature of these responses by characterizing and quantifying the response amplitude, rate and time for 37 large rainfall events at 25 combinations of topographic positions and soil depths along a steep forested hillslope. Our results showed that soil moisture responses under different rainfall patterns could be attributed to one or the other rainfall characteristics, such as rainfall intensity and amount. However, soil moisture dynamics at different hillslope positions after rainfall varied widely due to the controls of soil properties, topography, and non‐equilibrium flow. Preferential flow was more evident under dry initial soil conditions than under wet initial soil conditions. Findings of this study reveal that the dynamic response patterns of soil moisture to rainfall do not always follow topographic controls, which can improve our understanding of water cycling related to the infiltration process at the hillslope scale, and support water resources management in subtropical mountain ecosystems.

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Section: Discussionsupporting

confidence: 86%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Responses of soil moisture at different topographic positions to rainfall events along a steep subtropical forested hillslope

Lu,

Liu,

et al. 2024

Hydrological Processes

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“…The annual average temperature at the AGS is from −3.1 to 3.6 • C, and the annual average precipitation, most of which occurs from June to September, is about 300-600 mm [2,19,47]. Both observation sites have been used by a number of studies as good representatives of the study area [61][62][63][64]. The measurement of the CRNS observation reliability at the two observation sites has also been adequately verified by previous studies [48,64].…”

Section: Study Areasmentioning

confidence: 55%

Comparison of Data Fusion Methods in Fusing Satellite Products and Model Simulations for Estimating Soil Moisture on Semi-Arid Grasslands

Zhu,

Zhang,

et al. 2023

Remote Sensing

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In arid and semi-arid areas, soil moisture (SM) plays a crucial role in land-atmosphere interactions, hydrological processes, and ecosystem sustainability. SM data at large scales are critical for related climatic, hydrological, and ecohydrological research. Data fusion based on satellite products and model simulations is an important way to obtain SM data at large scales; however, little has been reported on the comparison of the data fusion methods in different categories. Here, we compared the performance of two widely used data fusion methods, the Ensemble Kalman Filter (EnKF) and the Back-Propagation Artificial Neural Network (BPANN), in the degraded grassland site (DGS) and the alpine grassland site (AGS). The SM data from the Community Land Model 5.0 (CLM5.0) and the Soil Moisture Active and Passive (SMAP) were fused and validated against the observations of the Cosmic-Ray Neutron Sensor (CRNS) to avoid the impacts of scale-mismatch. Results show that compared with the original data sets at both sites, the RMSE of the fused data by BPANN (FD-BPANN) and EnKF (FD-EnKF) had improved by more than 50% and 31%, respectively. Overall, the FD-BPANN performs better than the FD-EnKF because the BPANN method assigned higher weights to input data with better performance and the EnKF method is affected by the strong variabilities of both the fused CLM5.0 and SMAP data and the CRNS data. However, in terms of the percentile range, the FD-BPANN showed the worst performance, with overestimations in the low SM range of 25th percentile (<Q25), because the BPANN method tends to be trapped in a local minimum. The BPANN method performed better in humid areas, then followed by semi-humid areas, and finally arid and semi-arid areas. Moreover, compared with the previous studies in arid and semi-arid areas, the BPANN method in this study performed better.

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Effect of Complex Parameters of Porous Media on Desalination Performance in Air-Gap Diffusion Distillation Based on Multiple Regression Analysis

Chen

Wang²,

Zhang³

et al. 2022

J. Therm. Sci.

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Occurrence and controls of preferential flow in the upper stream of the Heihe River Basin, Northwest China

Cited by 10 publications

References 90 publications

Responses of soil moisture at different topographic positions to rainfall events along a steep subtropical forested hillslope

Responses of soil moisture at different topographic positions to rainfall events along a steep subtropical forested hillslope

Comparison of Data Fusion Methods in Fusing Satellite Products and Model Simulations for Estimating Soil Moisture on Semi-Arid Grasslands

Effect of Complex Parameters of Porous Media on Desalination Performance in Air-Gap Diffusion Distillation Based on Multiple Regression Analysis

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