Prediction of soil moisture scarcity using sequential Gaussian simulation in an arid region of China
Shao, MG (reprint author), Northwest A&F Univ, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shaanxi, Peoples R China.; Zhang, Shuaipu3; Shao, Mingan1,3; Li, Danfeng2; Shao, MG (reprint author), Chinese Acad Sci, Key Lab Ecosyst Network Observat & Modeling, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.
刊名GEODERMA
2017
卷号295页码:119-128
关键词Soil Moisture Scarcity Spatial Pattern Risk Analysis Stochastic Simulation Uncertainty
ISSN号0016-7061
DOI10.1016/j.geoderma.2017.02.003
文献子类Article
英文摘要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.
学科主题Agriculture
URL标识查看原文
出版地AMSTERDAM
语种英语
出版者ELSEVIER SCIENCE BV
WOS记录号WOS:000398651100012
资助机构National Natural Science Foundation of China [91025018] ; National Natural Science Foundation of China [91025018] ; National Natural Science Foundation of China [91025018] ; National Natural Science Foundation of China [91025018]
内容类型期刊论文
源URL[http://ir.iswc.ac.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.Chinese Acad Sci, Key Lab Ecosyst Network Observat & Modeling, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
2.Chinese Acad Sci, Key Lab Water Cycle & Related Land Surface Proc, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
3.Northwest A&F Univ, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shaanxi, Peoples R China
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GB/T 7714
Shao, MG ,Zhang, Shuaipu,Shao, Mingan,et al. Prediction of soil moisture scarcity using sequential Gaussian simulation in an arid region of China[J]. GEODERMA,2017,295:119-128.
APA Shao, MG ,Zhang, Shuaipu,Shao, Mingan,Li, Danfeng,&Shao, MG .(2017).Prediction of soil moisture scarcity using sequential Gaussian simulation in an arid region of China.GEODERMA,295,119-128.
MLA Shao, MG ,et al."Prediction of soil moisture scarcity using sequential Gaussian simulation in an arid region of China".GEODERMA 295(2017):119-128.
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