干旱区生态环境知识资源中心(Arid): Predicting Annual Mean Profile Soil Moisture from Soil Particle-Size Distributions on a Small-Scale Hillslope on the Chinese Loess Plateau

Arid

DOI	10.2136/sssaj2019.05.0145
	Predicting Annual Mean Profile Soil Moisture from Soil Particle-Size Distributions on a Small-Scale Hillslope on the Chinese Loess Plateau
	Yang, Xianlong 1; Yang, Qian 1; Lu, Yongli 2
通讯作者	Lu, Yongli
来源期刊	SOIL SCIENCE SOCIETY OF AMERICA JOURNAL
ISSN	0361-5995
EISSN	1435-0661
出版年	2019
卷号	83 期号:6 页码:1648-1654
英文摘要	Soil water content (SWC) varies notably over time and space due to soil heterogeneity, climatic conditions, vegetation, and topography. To restore vegetation rationally in arid and semiarid regions, it is important to have an accurate and rapid estimation of annual mean soil water content (AMSWC). Research on predicting of profile AMSWC from routinely available soil parameters, however, is still underrepresented in the literature. Our objective was to explore the ability of pedotransfer functions to accurately predict profile AMSWC from routinely available soil particle-size distributions (PSDs) for a small-scale hillslope on the Chinese Loess Plateau. The SWCs in soil profiles from 0- to 400-cm depths were measured regularly at 30 monitoring sites on a typical hillslope during the growing seasons in 2014 and 2015. A total of 750 soil samples were taken from the same soil layers (0-400 cm) of these sites and their PSDs were determined using a laser diffraction technique. The results indicated that AMSWC increased exponentially (P < 0.001) with the clay (R-2 = 0.632), silt (R-2 = 0.480), and fractal dimensions (R-2 = 0.616), however, they decreased exponentially (P < 0.001) with the sand content (R-2 = 0.572). Using clay content as a predictor variable, the model established separately for each 100 cm depth soil sample resulted in a higher R-2 (0.915), lower mean error (ME, 0.120%), and lower root mean squared error (RMSE, 0.999%), than the model of the whole 0- to 400-cm soil depth (R-2 = 0.830, ME = 0.199%, RMSE = 1.262%). These results showed that profile AMSWC at hillslope was able to be well-estimated from routinely available soil clay content data. The model established separately for each 100-cm depth soil sample performed well at predicting AMSWC on a small-scale hillslope on the Chinese Loess Plateau. Our study proposed a precise and rapid method for estimating profile AMSWC at hillslope, serving for the optimization of soil water management and vegetation construction in dry regions.
类型	Article
语种	英语
国家	Peoples R China
收录类别	SCI-E
WOS记录号	WOS:000502983600005
WOS关键词	WATER-RETENTION ; PEDOTRANSFER FUNCTIONS ; TEMPORAL STABILITY ; BULK-DENSITY ; CAPACITY ; STORAGE ; LAYERS ; MODEL ; AREA
WOS类目	Soil Science
WOS研究方向	Agriculture
EI主题词	2019-11-01
来源机构	兰州大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/310427
作者单位	1.Lanzhou Univ, Coll Pastoral Agr Sci & Technol,State Key Lab Gra, Minist Educ,Key Lab Grassland Livestock Ind Innov, Engn Res Ctr Grassland Ind,Minist Agr & Rural Aff, Lanzhou 730020, Gansu, Peoples R China; 2.Gansu Agr Univ, Coll Resources & Environm Sci, Lanzhou 730070, Gansu, Peoples R China
推荐引用方式 GB/T 7714	Yang, Xianlong,Yang, Qian,Lu, Yongli. Predicting Annual Mean Profile Soil Moisture from Soil Particle-Size Distributions on a Small-Scale Hillslope on the Chinese Loess Plateau[J]. 兰州大学,2019,83(6):1648-1654.
APA	Yang, Xianlong,Yang, Qian,&Lu, Yongli.(2019).Predicting Annual Mean Profile Soil Moisture from Soil Particle-Size Distributions on a Small-Scale Hillslope on the Chinese Loess Plateau.SOIL SCIENCE SOCIETY OF AMERICA JOURNAL,83(6),1648-1654.
MLA	Yang, Xianlong,et al."Predicting Annual Mean Profile Soil Moisture from Soil Particle-Size Distributions on a Small-Scale Hillslope on the Chinese Loess Plateau".SOIL SCIENCE SOCIETY OF AMERICA JOURNAL 83.6(2019):1648-1654.