Prediction of soil moisture scarcity using sequential Gaussian simulation in an arid region of China
文献类型：期刊论文
| 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.; 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
 |
| 出版日期 | 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 |
| DOI | 10.1016/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 |
| WOS记录号 | WOS:000398651100012 |
| 出版者 | ELSEVIER SCIENCE BV |
| 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] |
| 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 |
| 推荐引用方式 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. |
入库方式： OAI收割
来源：水土保持研究所
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