使用规范化部分导数方法估计和归因水利用效率的非线性趋势
Shahid Naeem1, Yongqiang Zhang1, Congcong Li1
1Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Journal of environmental management
|November 17, 2024
概括
这项研究开发了一种非线性模型,以准确地归因于用水效率 (WUE) 的变化. 这种使用集体实证模式分解 (EEMD) 的新模型在识别叶面积指数和CO2等关键驱动因素方面超过了线性方法.
科学领域:
- 生态生态学 生态生态学
- 环境科学 环境科学
- 气候变化研究 气候变化研究
背景情况:
- 水利用效率 (WUE) 在全球范围内表现出非线性趋势,但大多数研究都关注线性变化.
- 准确地归因WUE变异对于理解生态系统动态和管理至关重要.
研究的目的:
- 开发和验证一个能够归因线性和非线性WUE变化的规范化部分导数模型 (NPD模型).
- 量化各种驱动因素对2000-2018年中国WUE变化的影响.
主要方法:
- 开发了一种新的规范化部分导数模型 (NPD模型),结合了线性 (线性回归,非参数) 和非线性 (集体实证模式分解 - EEMD) 趋势.
- 利用PML-V2蒸发转化率和中国的初级生产率总值数据来分析驱动因素.
- 诸如叶面积指数,二氧化碳和气候等因素对WUE变化的量化个体和相对贡献.
主要成果:
- 与线性模型 (R2=0.64-0.7) 相比,非线性基于EMD的NPD模型表现出更高的性能 (R2=0.83).
- 叶面积指数被确定为中国WUE的主要驱动因素,其次是CO2和气候.
- 植被和环境因素共同解释了中国大部分地区80%以上的WUE增加,观察到显著的非线性变化.
结论:
- 基于非线性EEMD的NPD模型为WUE变化及其驱动因素提供了卓越的时空归因.
- 这种方法对于理解生态系统对环境变化的反应和为水资源管理提供信息至关重要.
- 研究结果强调了在WUE研究中考虑非线性动态对于准确的生态系统评估的重要性.
相关概念视频
Design Example: Designing a Residential Plumbing System
389
The design of residential plumbing systems requires carefully evaluating water demand, flow rates, and pressure dynamics to ensure both efficiency and reliability. The nature of water flow within pipes is defined by its Reynolds number, which classifies flow as either laminar (smooth) or turbulent.
389
Dimensional Analysis
303
Dimensional analysis is a valuable technique in fluid mechanics for simplifying complex problems by reducing them into dimensionless groups. These groups capture the essential relationships between the variables involved, allowing researchers and engineers to analyze fluid flow without dealing with each variable individually. This approach reduces the number of independent variables, allowing for easier analysis and better understanding of physical phenomena.
In fluid mechanics, dimensional...
In fluid mechanics, dimensional...
303
Multiple Regression
2.9K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
2.9K
Design Example: Creating a Hydraulic Model of a Dam Spillway
127
Scaled hydraulic models of dam spillways provide a practical way to replicate and study the intricate flow dynamics of these structures. Often built to a 1:15 ratio, these models allow for observing critical water behavior, such as velocity distribution, flow patterns, and energy dissipation.
127
Gradually Varying Flow
34
Gradually varying flow (GVF) in open channels describes situations where water depth changes slowly along the channel due to factors like non-uniform bed slope, channel shape variations, or obstructions. This flow type occurs when the depth adjusts gradually to balance gravitational forces, shear forces, and energy requirements, resulting in a low rate of depth change.Characteristics of Gradually Varying FlowGVF is commonly observed in natural streams, rivers, and canals, where flow depth...
34
Typical Model Studies
340
Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
340


