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Browsing by Author Zhu, Y.

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  • Capacity and Distribution of Water Stored in the Vadose Zone of the Chinese Loess Plateau

    • Authors: Zhu, Y.;  Advisor: -;  Participants: Jia, X.; Qiao, J.; Binley, A.; Horton, R.; Hu, W.; Wang, Y.; Shao, M. (2019)

  • Water stored in the vadose (unsaturated) zone provides the majority of water required by plants and buffers water resources; thus, it is central to understanding ecological and hydrological processes in the Chinese Loess Plateau (CLP) with its thick loess deposits. We used multisource data on soil water content (SWC) and vadose zone thickness, combined with a spatial interpolation method, to quantify the vadose zone water and further deduce the water resource composition in the CLP. Vadose zone water is approximately 3.1 × 1012 m3 (±27.5%) in the CLP, 92.4% of which is stored in the deep vadose zone (>5 m and above the groundwater table). The water resources composition of the CLP com...
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  • Estimating the Contribution of Groundwater to the Root Zone of Winter Wheat Using Root Density Distribution Functions

    • Authors: Zhu, Y.;  Advisor: -;  Participants: Ren, L.; Horton, R.; Lü, H.; Wang, Z.; Yuan, F. (2018)

  • Based on field observations and local weather data for 2004–2005 and 2005–2006, HYDRUS‐1D was evaluated with different root density distribution functions by comparing simulated and measured root zone soil water contents. The evaluated model with the most suitable distribution function was used to estimate the daily CGWR for six winter wheat hydrological growth seasons. For all seasons, winter wheat growth was assumed to be at its optimal state. The main results were: (i) a piecewise root density distribution function was the most suitable for winter wheat; (ii) simulated seasonal CGWRs were 154, 128, and 136 mm in the dry, normal, and wet seasons, respectively; and (iii) the CGWR for...
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  • Impacts of Climate Changes on Water Resources in Yellow River Basin, China

    • Authors: Lin, Z.; Zhu, Y.;  Advisor: -;  Participants: - (2016)

  • This study examined the impacts of future climate changes on water resources and extreme flows in Yellow River Basin (YRB), China, using the Coupled Land surface and Hydrology Model System (CLHMS) driven by the IPCC scenarios RCP 2.6, 4.5 and 8.5. First, the skill of 14 IPCC AR5 GCMS for simulating temporal and spatial temperature and precipitation in Yellow River Basin has been evaluated. Using the bias-corrected result of RCP storylines, the CLHMS model was developed to predict the 21 century climate and water cycle change. All the three simulation results indicate a reduction in water resources. The current situation of water shortage since 1980s will keep continue, the water resou...
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  • Tripartite Active Learning for Interactive Anomaly Discovery

    • Authors: Zhu, Y.;  Advisor: -;  Participants: Yang, K. (2019)

  • Most existing approaches to anomaly detection focus on statistical features of the data. However, in many cases, users are merely interested in a subset of the statistical outliers depending on the speci c domain of interest, e.g., network attacks or nancial fraud. The instruction from human experts is therefore indispensable in building predictive models in such applications. However, obtaining labels from human experts is time-consuming and expensive. Obtaining labels from nonexpert labelers are relatively easy and cost-effective. However, the labeling accuracy of a nonexpert is usually dif cult to assess. Therefore, it remains open to leverage both the machine intelligence and the...