Beck Marcus W, Murphy Rebecca R
US Environmental Protection Agency, National Health and Environmental Effects Research Laboratory, Gulf Ecology Division, 1 Sabine Island Drive, Gulf Breeze, FL 32561 (Beck:
University of Maryland Center for Environmental Science at Chesapeake Bay Program, 410 Severn Avenue, Suite 112, Annapolis, MD 21403.
J Am Water Resour Assoc. 2017 Jan 2;53(1):197-219.
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- (chl-) 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- 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- in the last 10 years. Qualitative comparisons highlighted important differences in the statistical structure, available products, and characteristics of the data and desired analysis.
最近，两种统计方法，即基于时间、流量和季节的加权回归法（WRTDS）和广义相加模型（GAMs），已被用于评估河口水质趋势。尽管这两种模型在统计基础和结果方面存在差异，但它们都被用于类似的情况。本研究使用帕塔克森特河河口叶绿素（chl-）两个离散时间序列的29年数据，对这两种模型进行了实证和定性比较。每个模型的实证描述基于对观测数据的预测性能、用模拟数据再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，并且两种模型在从模拟时间序列中消除流量影响方面具有相当的能力。两种模型对具有不同特征的缺失数据的预测相似。每个模型的趋势都揭示了切萨皮克湾明显的干流影响，两种模型都预测下游河口的chl-随时间大致增加65%，而上游河口的流量归一化预测显示出更动态的模式，在过去10年中chl-增加了近100%。定性比较突出了统计结构、可用结果以及数据特征和所需分析方面的重要差异。
