Two statistical approaches, weighted regression on time, discharge, and season (WRTDS) and generalized additive models (GAMs), have recently been used to evaluate water quality trends in estuaries. Both models have been used in similar contexts despite differences in statistical foundations and products. This study provided an empirical and qualitative comparison of both models using 29 years of data for two discrete time series of chlorophyll-a (chl-a) in the Patuxent River Estuary. Empirical descriptions of each model were based on predictive performance against the observed data, ability to reproduce flow-normalized trends with simulated data, and comparisons of performance with validation datasets. Between-model differences were apparent but minor and both models had comparable abilities to remove flow effects from simulated time series. Both models similarly predicted observations for missing data with different characteristics. Trends from each model revealed distinct mainstem influences of the Chesapeake Bay with both models predicting a roughly 65% increase in chl-a over time in the lower estuary, whereas flow-normalized predictions for the upper estuary showed a more dynamic pattern, with a nearly 100% increase in chl-a in the last 10 years. Qualitative comparisons highlighted important differences in the statistical structure, available products, and characteristics of the data and desired analysis.

中文翻译：

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潮汐水域水质变化的两种统计模型的数值和定性对比。


最近使用两种统计方法，即时间、流量和季节的加权回归（WRTDS）和广义加性模型（GAM）来评估河口的水质趋势。尽管统计基础和产品存在差异，但这两种模型都在类似的环境中使用。本研究使用帕图森特河口叶绿素-a (chl-a) 两个离散时间序列的 29 年数据对这两个模型进行了实证和定性比较。每个模型的经验描述基于对观察数据的预测性能、利用模拟数据重现流量归一化趋势的能力以及与验证数据集的性能比较。模型之间的差异很明显但很小，并且两个模型都具有从模拟时间序列中消除流动效应的类似能力。两种模型都类似地预测了具有不同特征的缺失数据的观测结果。每个模型的趋势都揭示了切萨皮克湾的不同主流影响，两个模型都预测下河口的 chl-a 随着时间的推移会增加约 65%，而上河口的流量归一化预测则显示出更加动态的模式，几乎过去 10 年，叶绿素 A 增加了 100%。定性比较强调了统计结构、可用产品以及数据特征和所需分析方面的重要差异。