Department of Civil and Environmental Engineering, University of Massachusetts, Amherst, MA 01003, USA.
Department of Civil and Environmental Engineering, University of Massachusetts, Amherst, MA 01003, USA.
Sci Total Environ. 2022 Apr 20;818:151729. doi: 10.1016/j.scitotenv.2021.151729. Epub 2021 Nov 18.
Water quality monitoring programs are developed to meet goals including attaining regulatory compliance, evaluating long-term environmental changes, or quantifying the impact of an emergency event. Methods for developing these programs often fail to address multiple aspects of development (hazard identification, parameter selection, monitoring locations/frequency) simultaneously. We develop a framework for monitoring program development that is both versatile and systematic, the Hazard Based Water Quality Monitoring Planning framework, and apply it to the Quabbin watershed in Massachusetts, USA. We use a novel application of dataset deconstruction of long-term water quality datasets and the Seasonal Kendall test for trends to evaluate the effects of sampling frequency on long-term trend detection at several watershed sites. Results showed that when sampling frequency is decreased, ability to detect statistically significant trends often decreases. Absolute error in trend slopes between biweekly (twice monthly) and reduced sampling frequencies was relatively small for specific conductance and turbidity but was high for total coliform, likely due to interannual variation in rainfall and temperature We found that no one sampling reduction method resulted in a consistently lower absolute error compared to the "truth" (biweekly sampling), highlighting the importance of evaluating conditions that may affect water quality at sites in different parts of a watershed. We demonstrate the framework's usefulness, particularly for parameter and sampling frequency selection, using methods that can be readily applied to other watershed systems.
水质监测计划旨在实现多个目标，包括达到法规要求、评估长期环境变化或量化紧急事件的影响。制定这些计划的方法往往无法同时解决多个方面的问题（危害识别、参数选择、监测地点/频率）。我们开发了一种灵活且系统的监测计划制定框架，即基于危害的水质监测规划框架，并将其应用于美国马萨诸塞州的 Quabbin 流域。我们使用长期水质数据集的数据集分解和季节性 Kendall 趋势检验的新颖应用来评估采样频率对几个流域站点长期趋势检测的影响。结果表明，当采样频率降低时，检测统计显著趋势的能力通常会降低。对于电导率和浊度，两次每月（biweekly）和减少的采样频率之间的趋势斜率的绝对误差相对较小，但对于总大肠菌群，绝对误差较大，这可能是由于降雨量和温度的年际变化。我们发现，与“真相”（biweekly 采样）相比，没有一种采样减少方法始终导致绝对误差较低，这突出了评估可能影响流域不同部分站点水质的条件的重要性。我们使用可以很容易应用于其他流域系统的方法，展示了该框架的有用性，特别是在参数和采样频率选择方面。
