干旱区生态环境知识资源中心(Arid): Quantifying Shallow Overland Flow Patterns Under Laboratory Simulations Using Thermal and LiDAR Imagery

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DOI	10.1029/2020WR028857
	Quantifying Shallow Overland Flow Patterns Under Laboratory Simulations Using Thermal and LiDAR Imagery
	Danino, Din; Svoray, Tal; Thompson, Sally; Cohen, Ariel; Crompton, Octavia; Volk, Elazar; Argaman, Eli; Levi, Asher; Cohen, Yafit; Narkis, Kfir; Assouline, Shmuel
通讯作者	Svoray, T (corresponding author), Ben Gurion Univ Negev, Dept Geog & Environm Dev, Beer Sheva, Israel. ; Svoray, T (corresponding author), Ben Gurion Univ Negev, Dept Psychol, Beer Sheva, Israel.
来源期刊	WATER RESOURCES RESEARCH
ISSN	0043-1397
EISSN	1944-7973
出版年	2021
卷号	57 期号:3
英文摘要	Desertification processes pose a global environmental threat, impacting 61 x 10(6) km(2) of the terrestrial land area. Changes in overland flow patterns and consequent rainwater redistribution in drylands present a potential pathway to desertification, because vegetation often relies on water inputs from runoff to sustain growth under insufficient rainfall conditions. Of particular importance are the very shallow overland flows that redistribute water, nutrients, and biological matter within arid landscapes. However, characterizing overland flow patterns remains challenging, due to their very shallow depths, their distributed nature, and the poor understanding of how these flows interact with the underlying rough soil surface. This paper describes how coupling thermal images of shallow overland flows with light detection and ranging (LiDAR) scanning of the underlying soil surface in 1 m(2) experimental trays allows spatial patterns of shallow overland flow to be quantified. Laboratory experiments were used to explore the behaviors of shallow overland flow as mean slope gradients and soil roughness were varied. The results show that these imaging techniques are able to capture differences in flow patterns arising across soil surfaces with varying slope, roughness, and spatial variation in infiltration properties. Several spatial indices characterizing overland flow patterns were found to correlate with runoff volume. The presence of high permeability soil patches substantially regulated overland flow. A next logical step would be to apply the thermal and LiDAR measurement techniques to the hillslope scale.
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000635680800009
WOS类目	Environmental Sciences ; Limnology ; Water Resources
WOS研究方向	Environmental Sciences & Ecology ; Marine & Freshwater Biology ; Water Resources
来源机构	Ben-Gurion University of the Negev ; University of California, Berkeley ; University of Western Australia
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/351986
作者单位	[Danino, Din; Svoray, Tal; Cohen, Ariel] Ben Gurion Univ Negev, Dept Geog & Environm Dev, Beer Sheva, Israel; [Svoray, Tal] Ben Gurion Univ Negev, Dept Psychol, Beer Sheva, Israel; [Thompson, Sally; Crompton, Octavia] Univ Calif Berkeley, Dept Civil & Environm Engn, Berkeley, CA 94720 USA; [Thompson, Sally; Crompton, Octavia] Univ Western Australia, Dept Civil Environm & Min Engn, Perth, WA, Australia; [Volk, Elazar; Argaman, Eli] Minist Agr & Rural Dev, Soil Eros Res Stn, Bet Dagan, Israel; [Levi, Asher; Cohen, Yafit] Volcani Ctr, Inst Agr Engn ARO, Dept Sensing Informat & Mechanizat Engn, Rishon LeTsion, Israel; [Narkis, Kfir; Assouline, Shmuel] ARO Volcani Ctr, Inst Soil Water & Environm Sci, Dept Environm Phys & Irrigat, Rishon LeTsion, Israel
推荐引用方式 GB/T 7714	Danino, Din,Svoray, Tal,Thompson, Sally,et al. Quantifying Shallow Overland Flow Patterns Under Laboratory Simulations Using Thermal and LiDAR Imagery[J]. Ben-Gurion University of the Negev, University of California, Berkeley, University of Western Australia,2021,57(3).
APA	Danino, Din.,Svoray, Tal.,Thompson, Sally.,Cohen, Ariel.,Crompton, Octavia.,...&Assouline, Shmuel.(2021).Quantifying Shallow Overland Flow Patterns Under Laboratory Simulations Using Thermal and LiDAR Imagery.WATER RESOURCES RESEARCH,57(3).
MLA	Danino, Din,et al."Quantifying Shallow Overland Flow Patterns Under Laboratory Simulations Using Thermal and LiDAR Imagery".WATER RESOURCES RESEARCH 57.3(2021).