Lognormal and Moving Window Methods of Estimating Acid Deposition
酸沉降估计的对数正态方法与移动窗口方法AI 解读 ↓
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酸沉降估计的对数正态方法与移动窗口方法
- 研究问题
- 在酸沉降具有明显空间趋势、协方差结构也可能随位置变化时，如何利用不规则分布的观测估计区域沉降及其不确定性？
- 方法与思路
- 作者比较四种克里金方法，分别采用整体或局部变异函数，并在移动窗口内结合普通克里金、对数变换或平面趋势回归。
- 材料陈述的贡献
- 摘要称移动窗口方法是新提出的；局部平面回归后进行残差克里金，其区间宽度最能抵抗所述趋势效应引起的膨胀。
- 阅读关注点
- 应核对窗口与变异函数的选择、对数变换的适用性，以及趋势校正如何影响区间宽度、覆盖表现和负下界的解释。
- 阅读边界
- 仅据版本未注明的 OpenAlex 索引摘要；区间宽度的比较不能代替覆盖率评价，摘要未给出详细条件、数值或刊本差异。
原文摘要
The deposition of heightened levels of sulfuric and nitric acid through rainfall in the United States may adversely affect the environment. For example, soils may become toxic to native tree species because of soil acidification. Ecological effects models being built to study these potential problems have a need for regional deposition estimates with associated measures of uncertainty. However, statistical estimation of the deposition process is complicated by a strong spatial trend (mean nonstationarity) and apparently a spatial covariance structure dependent on location (covariance nonstationarity). The available data for calculating deposition estimates consist of several hundred point observations at irregularly spaced sampling locations across the United States. The spatial estimation technique of kriging is the foundation of four deposition estimation methods evaluated in this study. These are lognormal kriging with a single model of the spatial covariance structure (the variogram); single-estimate lognormal kriging within a moving window using a local model of the variogram; ordinary kriging within a moving window, also with a local variogram model; and planar regression with spatially correlated errors within a moving window used to estimate residuals that are then input to the moving window ordinary kriging algorithm to calculate a (local) trend-adjusted estimate. Each of these four methods has some capacity for accommodating mean and covariance nonstationarity. The moving window methods are new. It is shown that the log transform may not be the correct transform for the deposition process. However, confidence intervals found from a lognormal kriging method do not include a negative interval, as can frequently occur with intervals found from ordinary kriging. Assuming that a partially negative confidence interval for deposition is interpretable, the method of local planar regressions followed by residual kriging gives confidence interval widths that are the most resistant to inflation due to trend effects on the variogram and trend-dependent variance.