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DOI: 10.1371/journal.pone.0151283
论文题名:
Uncertainty in Ecohydrological Modeling in an Arid Region Determined with Bayesian Methods
作者: Junjun Yang; Zhibin He; Jun Du; Longfei Chen; Xi Zhu
刊名: PLOS ONE
ISSN: 1932-6203
出版年: 2016
发表日期: 2016-3-10
卷: 11, 期:3
语种: 英语
英文关键词: Rain ; Simulation and modeling ; Probability distribution ; Ecosystems ; Evaporation ; Bayesian method ; Soil ecology ; Thermal conductivity
英文摘要: In arid regions, water resources are a key forcing factor in ecosystem circulation, and soil moisture is the critical link that constrains plant and animal life on the soil surface and underground. Simulation of soil moisture in arid ecosystems is inherently difficult due to high variability. We assessed the applicability of the process-oriented CoupModel for forecasting of soil water relations in arid regions. We used vertical soil moisture profiling for model calibration. We determined that model-structural uncertainty constituted the largest error; the model did not capture the extremes of low soil moisture in the desert-oasis ecotone (DOE), particularly below 40 cm soil depth. Our results showed that total uncertainty in soil moisture prediction was improved when input and output data, parameter value array, and structure errors were characterized explicitly. Bayesian analysis was applied with prior information to reduce uncertainty. The need to provide independent descriptions of uncertainty analysis (UA) in the input and output data was demonstrated. Application of soil moisture simulation in arid regions will be useful for dune-stabilization and revegetation efforts in the DOE.
URL: http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0151283&type=printable
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/23242
Appears in Collections:过去全球变化的重建
影响、适应和脆弱性
科学计划与规划
气候变化与战略
全球变化的国际研究计划
气候减缓与适应
气候变化事实与影响

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作者单位: Linze Inland River Basin Research Station, Chinese Ecosystem Research Network, Key Laboratory of Eco-hydrology of Inland River Basin, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China;Linze Inland River Basin Research Station, Chinese Ecosystem Research Network, Key Laboratory of Eco-hydrology of Inland River Basin, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China;Linze Inland River Basin Research Station, Chinese Ecosystem Research Network, Key Laboratory of Eco-hydrology of Inland River Basin, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China;Linze Inland River Basin Research Station, Chinese Ecosystem Research Network, Key Laboratory of Eco-hydrology of Inland River Basin, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China;Linze Inland River Basin Research Station, Chinese Ecosystem Research Network, Key Laboratory of Eco-hydrology of Inland River Basin, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China

Recommended Citation:
Junjun Yang,Zhibin He,Jun Du,et al. Uncertainty in Ecohydrological Modeling in an Arid Region Determined with Bayesian Methods[J]. PLOS ONE,2016-01-01,11(3)
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