Prediction of soil moisture scarcity using sequential Gaussian simulation in an arid region of China

doi:10.1016/j.geoderma.2017.02.003

ISWC OpenIR > 水保所科研产出--SCI > 2017--SCI

	Prediction of soil moisture scarcity using sequential Gaussian simulation in an arid region of China
	Zhang, Shuaipu 1; Shao, Mingan 1,2; Li, Danfeng 3; Shao, MG (reprint author), Northwest A&F Univ, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shaanxi, Peoples R China.; Shao, MG (reprint author), Chinese Acad Sci, Key Lab Ecosyst Network Observat & Modeling, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.
文章类型	Article
	2017
发表期刊	GEODERMA
ISSN	0016-7061
通讯作者邮箱	mashao@ms.iswc.ac.cn
卷号	295 页码:119-128
摘要	Soil moisture plays a vital role in maintaining the sustainability of dryland ecosystems. Accurately predicting soil moisture scarcity (SMS) has an important interest of guidance to soil and water conservation. In this study, we gathered a time series of soil moisture measurements throughout the growing season (from April to October) in an area of approximately 100 km(2) in a desert oasis of northwestern China. Sequential Gaussian simulation was applied to investigate the spatial variability and scarcity of soil moisture across multiple land use types. Soil moisture exhibited considerable spatial heterogeneity with different magnitudes of spatial dependence at different times. Two hundred simulated realizations depicted the possible spatial variations of soil moisture in the geographic space. SMS was characterized as the natural event that occurred when the spatial probability of soil moisture not exceeding 0.15 cm(3) cm(-3) was greater than a critical threshold. With the increasing of probability thresholds, the proportion of SMS locations in each land use decreased at different rates. Given the spatial probability threshold of 0.6,13-3.8% of the cultivated land, 2.6-5.2% of the forest land, 3.2-4.6% of the grassland, and 2.7-7.4% of the shrub land were of SMS during the measuring period. The newly cultivated land and the ecotone of desert and oasis were the major regions SMS occurred. Some soil moisture conservation measures such as precision irrigation should be taken to prevent the probable land degradation and agricultural disasters in these areas. The prediction of SMS using stochastic simulation contributes to improving soil water management in the oasis and provides a methodology reference for similar studies in risk analysis. (C) 2017 Elsevier B.V. All rights reserved.
关键词	Soil Moisture Scarcity Spatial Pattern Risk Analysis Stochastic Simulation Uncertainty
学科领域	Agriculture
DOI	10.1016/j.geoderma.2017.02.003
URL	查看原文
收录类别	SCI
出版地	AMSTERDAM
语种	英语
WOS记录号	WOS:000398651100012
出版者	ELSEVIER SCIENCE BV
项目资助者	National Natural Science Foundation of China [91025018] ; National Natural Science Foundation of China [91025018]
引用统计	被引频次：22[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	sbir.nwafu.edu.cn/handle/361005/7991
专题	水保所科研产出--SCI_2017--SCI
通讯作者	Shao, MG (reprint author), Northwest A&F Univ, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shaanxi, Peoples R China.; Shao, MG (reprint author), Chinese Acad Sci, Key Lab Ecosyst Network Observat & Modeling, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.
作者单位	1.Northwest A&F Univ, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shaanxi, Peoples R China 2.Chinese Acad Sci, Key Lab Ecosyst Network Observat & Modeling, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 3.Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Shuaipu,Shao, Mingan,Li, Danfeng,et al. Prediction of soil moisture scarcity using sequential Gaussian simulation in an arid region of China[J]. GEODERMA,2017,295:119-128.
APA	Zhang, Shuaipu,Shao, Mingan,Li, Danfeng,Shao, MG ,&Shao, MG .(2017).Prediction of soil moisture scarcity using sequential Gaussian simulation in an arid region of China.GEODERMA,295,119-128.
MLA	Zhang, Shuaipu,et al."Prediction of soil moisture scarcity using sequential Gaussian simulation in an arid region of China".GEODERMA 295(2017):119-128.